observe_result_per_participant.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import data_utils\n",
    "import matplotlib.pyplot as plt\n",
    "from plot_results import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_05_37.76460_2000_1_3_ECONOMICS.result\n",
      "Means\n",
      "carries\n",
      "0    4.262500\n",
      "1    4.539100\n",
      "2    4.871200\n",
      "3    6.515778\n",
      "4    7.336375\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     6.363694\n",
      "1     5.966924\n",
      "2     7.727570\n",
      "3     8.879238\n",
      "4    10.269353\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index           answer  carries  solving_time\n",
      "22  [0, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 1, 1, 1]        0         2.711\n",
      "37  [0, 1, 1, 1, 1, 0, 0, 0]  [0, 1, 1, 1, 1]        0         3.320\n",
      "38  [0, 1, 0, 1, 0, 0, 0, 0]  [0, 0, 1, 0, 1]        0         3.574\n",
      "17  [0, 1, 0, 0, 0, 0, 1, 0]  [0, 0, 1, 1, 0]        0         3.663\n",
      "9   [1, 1, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 0, 1]        0         3.961\n",
      "6   [0, 1, 1, 0, 1, 0, 0, 0]  [0, 1, 1, 1, 0]        0         4.227\n",
      "28  [0, 0, 0, 1, 0, 0, 0, 0]  [0, 0, 0, 0, 1]        0         4.444\n",
      "1   [0, 1, 0, 1, 1, 0, 0, 0]  [0, 1, 1, 0, 1]        0         4.992\n",
      "36  [0, 0, 0, 1, 1, 0, 1, 0]  [0, 1, 0, 1, 1]        0         5.835\n",
      "5   [1, 0, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 0, 1]        0         5.898\n",
      "                  data_index           answer  carries  solving_time\n",
      "45  [1, 0, 0, 0, 1, 0, 1, 1]  [1, 0, 0, 1, 1]        1         3.741\n",
      "30  [0, 0, 0, 1, 0, 0, 0, 1]  [0, 0, 0, 1, 0]        1         3.960\n",
      "47  [1, 1, 0, 1, 1, 0, 1, 0]  [1, 0, 1, 1, 1]        1         4.085\n",
      "11  [1, 1, 1, 1, 1, 0, 0, 0]  [1, 0, 1, 1, 1]        1         4.113\n",
      "23  [1, 0, 0, 0, 1, 0, 0, 1]  [1, 0, 0, 0, 1]        1         4.132\n",
      "7   [0, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 0, 1, 1]        1         4.148\n",
      "3   [1, 0, 0, 0, 1, 1, 0, 1]  [1, 0, 1, 0, 1]        1         4.678\n",
      "39  [0, 0, 0, 1, 0, 1, 0, 1]  [0, 0, 1, 1, 0]        1         5.380\n",
      "18  [0, 0, 0, 1, 1, 0, 0, 1]  [0, 1, 0, 1, 0]        1         5.460\n",
      "35  [1, 0, 1, 0, 0, 0, 1, 0]  [0, 1, 1, 0, 0]        1         5.694\n",
      "                  data_index           answer  carries  solving_time\n",
      "14  [1, 1, 0, 1, 0, 1, 1, 0]  [1, 0, 0, 1, 1]        2         3.711\n",
      "13  [0, 1, 0, 0, 1, 1, 1, 1]  [1, 0, 0, 1, 1]        2         4.086\n",
      "20  [1, 1, 0, 0, 1, 1, 1, 0]  [1, 1, 0, 1, 0]        2         4.147\n",
      "25  [1, 1, 0, 0, 1, 1, 0, 0]  [1, 1, 0, 0, 0]        2         4.226\n",
      "16  [1, 0, 1, 1, 1, 0, 1, 0]  [1, 0, 1, 0, 1]        2         4.383\n",
      "34  [0, 1, 1, 0, 1, 1, 0, 0]  [1, 0, 0, 1, 0]        2         4.413\n",
      "0   [1, 1, 1, 1, 0, 1, 0, 0]  [1, 0, 0, 1, 1]        2         4.445\n",
      "41  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0, 0]        2         4.492\n",
      "10  [0, 1, 0, 0, 1, 1, 0, 1]  [1, 0, 0, 0, 1]        2         6.444\n",
      "49  [0, 1, 1, 1, 0, 1, 1, 0]  [0, 1, 1, 0, 1]        2         8.365\n",
      "                  data_index           answer  carries  solving_time\n",
      "43  [1, 0, 1, 0, 1, 1, 1, 0]  [1, 1, 0, 0, 0]        3         5.178\n",
      "27  [1, 1, 1, 0, 1, 0, 1, 0]  [1, 1, 0, 0, 0]        3         5.273\n",
      "15  [1, 1, 1, 0, 0, 0, 1, 0]  [1, 0, 0, 0, 0]        3         5.632\n",
      "24  [0, 1, 0, 1, 1, 1, 0, 1]  [1, 0, 0, 1, 0]        3         5.663\n",
      "29  [1, 1, 1, 0, 0, 1, 1, 1]  [1, 0, 1, 0, 1]        3         6.351\n",
      "12  [0, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 1, 0]        3         6.699\n",
      "19  [1, 1, 1, 1, 1, 0, 1, 0]  [1, 1, 0, 0, 1]        3         7.726\n",
      "31  [1, 0, 0, 1, 1, 0, 1, 1]  [1, 0, 1, 0, 0]        3         7.928\n",
      "44  [1, 0, 1, 1, 1, 0, 0, 1]  [1, 0, 1, 0, 0]        3         8.192\n",
      "                  data_index           answer  carries  solving_time\n",
      "42  [0, 0, 1, 1, 1, 1, 0, 1]  [1, 0, 0, 0, 0]        4         5.304\n",
      "21  [1, 0, 1, 1, 0, 1, 1, 1]  [1, 0, 0, 1, 0]        4         6.459\n",
      "33  [1, 1, 0, 1, 1, 0, 1, 1]  [1, 1, 0, 0, 0]        4         6.709\n",
      "4   [1, 1, 1, 1, 1, 0, 0, 1]  [1, 1, 0, 0, 0]        4         6.757\n",
      "32  [1, 0, 1, 1, 0, 1, 0, 1]  [1, 0, 0, 0, 0]        4         7.100\n",
      "8   [1, 1, 1, 1, 1, 1, 0, 1]  [1, 1, 1, 0, 0]        4         7.475\n",
      "40  [1, 0, 0, 1, 1, 1, 1, 1]  [1, 1, 0, 0, 0]        4         8.959\n",
      "48  [0, 0, 1, 1, 1, 1, 1, 1]  [1, 0, 0, 1, 0]        4         9.928\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_22_00.03103_2001_2_2_ENGLISH LANGUAGE EDUCATION.result\n",
      "Means\n",
      "carries\n",
      "0     5.2468\n",
      "1     8.0708\n",
      "2     7.7374\n",
      "3     7.9340\n",
      "4    12.8749\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     8.928343\n",
      "1    19.504897\n",
      "2    16.047677\n",
      "3    16.147781\n",
      "4    28.988267\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index           answer  carries  solving_time\n",
      "35  [1, 0, 0, 0, 0, 0, 0, 0]  [0, 1, 0, 0, 0]        0         2.959\n",
      "47  [0, 1, 1, 1, 1, 0, 0, 0]  [0, 1, 1, 1, 1]        0         3.648\n",
      "20  [0, 0, 1, 0, 0, 1, 0, 0]  [0, 0, 1, 1, 0]        0         3.865\n",
      "45  [0, 0, 0, 1, 1, 1, 0, 0]  [0, 1, 1, 0, 1]        0         3.867\n",
      "26  [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1, 1]        0         4.319\n",
      "21  [0, 0, 1, 1, 0, 1, 0, 0]  [0, 0, 1, 1, 1]        0         5.318\n",
      "19  [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 1, 0]        0         5.427\n",
      "1   [1, 1, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1, 1]        0         7.523\n",
      "4   [0, 1, 0, 0, 0, 0, 1, 0]  [0, 0, 1, 1, 0]        0         7.584\n",
      "40  [0, 0, 0, 1, 1, 0, 0, 0]  [0, 1, 0, 0, 1]        0         7.958\n",
      "                  data_index           answer  carries  solving_time\n",
      "49  [0, 1, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0, 0]        1         3.195\n",
      "18  [1, 0, 1, 1, 1, 0, 0, 0]  [1, 0, 0, 1, 1]        1         4.914\n",
      "32  [1, 0, 0, 1, 1, 0, 1, 0]  [1, 0, 0, 1, 1]        1         4.992\n",
      "14  [1, 0, 0, 0, 1, 1, 0, 1]  [1, 0, 1, 0, 1]        1         5.757\n",
      "5   [1, 0, 1, 0, 1, 0, 0, 0]  [1, 0, 0, 1, 0]        1         5.898\n",
      "3   [0, 0, 1, 1, 1, 0, 1, 0]  [0, 1, 1, 0, 1]        1         6.711\n",
      "2   [0, 1, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1, 1]        1         7.476\n",
      "15  [0, 0, 1, 1, 0, 0, 1, 0]  [0, 0, 1, 0, 1]        1         7.959\n",
      "17  [0, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 0, 1, 1]        1        10.475\n",
      "39  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 0, 1]        1        23.331\n",
      "                  data_index           answer  carries  solving_time\n",
      "46  [0, 1, 1, 0, 1, 1, 0, 0]  [1, 0, 0, 1, 0]        2         4.491\n",
      "44  [0, 0, 0, 1, 1, 0, 1, 1]  [0, 1, 1, 0, 0]        2         4.663\n",
      "48  [1, 1, 0, 1, 1, 0, 0, 1]  [1, 0, 1, 1, 0]        2         5.210\n",
      "24  [0, 1, 1, 0, 0, 0, 1, 0]  [0, 1, 0, 0, 0]        2         5.366\n",
      "7   [1, 0, 0, 1, 1, 1, 0, 1]  [1, 0, 1, 1, 0]        2         5.570\n",
      "10  [1, 1, 0, 1, 1, 1, 0, 0]  [1, 1, 0, 0, 1]        2         6.522\n",
      "25  [1, 1, 1, 1, 0, 1, 0, 0]  [1, 0, 0, 1, 1]        2         7.738\n",
      "0   [1, 1, 0, 0, 0, 1, 0, 0]  [1, 0, 0, 0, 0]        2         7.789\n",
      "31  [1, 0, 1, 1, 0, 0, 0, 1]  [0, 1, 1, 0, 0]        2        12.630\n",
      "11  [0, 0, 1, 0, 0, 1, 1, 1]  [0, 1, 0, 0, 1]        2        17.395\n",
      "                  data_index           answer  carries  solving_time\n",
      "28  [1, 0, 1, 0, 0, 1, 1, 0]  [1, 0, 0, 0, 0]        3         4.221\n",
      "42  [1, 1, 1, 1, 1, 0, 1, 0]  [1, 1, 0, 0, 1]        3         4.304\n",
      "41  [0, 1, 1, 0, 1, 1, 1, 1]  [1, 0, 1, 0, 1]        3         5.506\n",
      "37  [1, 0, 1, 1, 1, 0, 1, 1]  [1, 0, 1, 1, 0]        3         5.757\n",
      "12  [1, 1, 1, 1, 0, 1, 1, 0]  [1, 0, 1, 0, 1]        3         6.085\n",
      "38  [1, 1, 1, 0, 1, 0, 1, 1]  [1, 1, 0, 0, 1]        3         6.101\n",
      "43  [0, 1, 1, 0, 1, 0, 1, 1]  [1, 0, 0, 0, 1]        3         6.802\n",
      "23  [1, 1, 0, 1, 0, 1, 0, 1]  [1, 0, 0, 1, 0]        3        10.675\n",
      "33  [0, 1, 0, 1, 1, 1, 0, 1]  [1, 0, 0, 1, 0]        3        14.536\n",
      "29  [1, 1, 1, 1, 0, 0, 1, 0]  [1, 0, 0, 0, 1]        3        15.353\n",
      "                  data_index           answer  carries  solving_time\n",
      "30  [1, 0, 0, 1, 1, 1, 1, 1]  [1, 1, 0, 0, 0]        4         5.283\n",
      "9   [0, 1, 1, 1, 1, 1, 0, 1]  [1, 0, 1, 0, 0]        4         6.335\n",
      "22  [0, 0, 1, 1, 1, 1, 1, 1]  [1, 0, 0, 1, 0]        4         7.175\n",
      "8   [0, 1, 1, 1, 1, 1, 1, 1]  [1, 0, 1, 1, 0]        4         7.679\n",
      "34  [1, 1, 0, 1, 0, 1, 1, 1]  [1, 0, 1, 0, 0]        4         8.817\n",
      "6   [1, 0, 1, 1, 1, 1, 1, 1]  [1, 1, 0, 1, 0]        4         9.601\n",
      "27  [0, 0, 1, 1, 1, 1, 0, 1]  [1, 0, 0, 0, 0]        4        11.490\n",
      "36  [1, 1, 1, 1, 0, 0, 0, 1]  [1, 0, 0, 0, 0]        4        22.347\n",
      "13  [1, 1, 0, 1, 1, 0, 1, 1]  [1, 1, 0, 0, 0]        4        22.676\n",
      "16  [1, 1, 1, 1, 1, 1, 1, 1]  [1, 1, 1, 1, 0]        4        27.346\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_13_56_26.71195_1994_1_3_ARCHITECTURAL ENGENEERING.result\n",
      "Means\n",
      "carries\n",
      "0    3.2840\n",
      "1    3.7801\n",
      "2    4.6818\n",
      "3    4.9963\n",
      "4    5.7803\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0    4.139612\n",
      "1    4.860778\n",
      "2    7.050579\n",
      "3    7.166381\n",
      "4    8.352203\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index           answer  carries  solving_time\n",
      "42  [0, 0, 0, 0, 0, 0, 0, 1]  [0, 0, 0, 0, 1]        0         2.507\n",
      "33  [0, 0, 0, 0, 1, 1, 1, 1]  [0, 1, 1, 1, 1]        0         2.710\n",
      "40  [0, 0, 0, 0, 1, 1, 1, 0]  [0, 1, 1, 1, 0]        0         3.242\n",
      "35  [1, 0, 0, 1, 0, 0, 0, 0]  [0, 1, 0, 0, 1]        0         3.288\n",
      "32  [0, 1, 0, 1, 0, 0, 1, 0]  [0, 0, 1, 1, 1]        0         3.304\n",
      "28  [0, 1, 1, 1, 1, 0, 0, 0]  [0, 1, 1, 1, 1]        0         3.383\n",
      "2   [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 1, 0]        0         3.384\n",
      "7   [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1, 1]        0         3.461\n",
      "48  [0, 0, 0, 1, 0, 0, 0, 0]  [0, 0, 0, 0, 1]        0         3.491\n",
      "45  [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 0, 1]        0         4.070\n",
      "                  data_index           answer  carries  solving_time\n",
      "34  [1, 1, 0, 1, 1, 0, 1, 0]  [1, 0, 1, 1, 1]        1         2.802\n",
      "49  [1, 0, 0, 0, 1, 0, 0, 0]  [1, 0, 0, 0, 0]        1         3.236\n",
      "5   [0, 1, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0, 0]        1         3.351\n",
      "11  [1, 0, 1, 1, 1, 1, 0, 0]  [1, 0, 1, 1, 1]        1         3.695\n",
      "18  [0, 1, 1, 1, 0, 1, 0, 0]  [0, 1, 0, 1, 1]        1         3.711\n",
      "38  [1, 0, 0, 1, 0, 0, 0, 1]  [0, 1, 0, 1, 0]        1         3.914\n",
      "10  [1, 0, 1, 1, 1, 0, 0, 0]  [1, 0, 0, 1, 1]        1         4.054\n",
      "25  [1, 0, 0, 1, 1, 1, 0, 0]  [1, 0, 1, 0, 1]        1         4.101\n",
      "16  [1, 1, 1, 0, 1, 0, 0, 1]  [1, 0, 1, 1, 1]        1         4.336\n",
      "17  [0, 0, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 0, 1]        1         4.601\n",
      "                  data_index           answer  carries  solving_time\n",
      "36  [1, 0, 1, 1, 1, 0, 1, 0]  [1, 0, 1, 0, 1]        2         3.304\n",
      "44  [1, 1, 0, 0, 1, 1, 1, 0]  [1, 1, 0, 1, 0]        2         4.038\n",
      "41  [1, 1, 0, 1, 1, 1, 1, 0]  [1, 1, 0, 1, 1]        2         4.070\n",
      "43  [0, 0, 1, 1, 1, 0, 0, 1]  [0, 1, 1, 0, 0]        2         4.242\n",
      "6   [1, 1, 1, 1, 0, 1, 0, 0]  [1, 0, 0, 1, 1]        2         4.336\n",
      "31  [0, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 0, 1]        2         4.476\n",
      "27  [0, 1, 0, 0, 1, 1, 0, 1]  [1, 0, 0, 0, 1]        2         4.507\n",
      "37  [1, 1, 0, 0, 1, 1, 0, 0]  [1, 1, 0, 0, 0]        2         4.862\n",
      "0   [1, 1, 0, 0, 0, 1, 0, 1]  [1, 0, 0, 0, 1]        2         5.273\n",
      "19  [1, 1, 0, 1, 1, 1, 0, 0]  [1, 1, 0, 0, 1]        2         7.710\n",
      "                  data_index           answer  carries  solving_time\n",
      "39  [1, 0, 1, 0, 0, 1, 1, 0]  [1, 0, 0, 0, 0]        3         3.570\n",
      "9   [0, 1, 1, 0, 1, 0, 1, 1]  [1, 0, 0, 0, 1]        3         4.351\n",
      "12  [1, 1, 1, 1, 1, 0, 1, 0]  [1, 1, 0, 0, 1]        3         4.492\n",
      "26  [1, 0, 0, 1, 1, 0, 1, 1]  [1, 0, 1, 0, 0]        3         4.585\n",
      "24  [0, 1, 1, 1, 0, 1, 1, 1]  [0, 1, 1, 1, 0]        3         4.632\n",
      "3   [1, 1, 1, 0, 0, 1, 1, 1]  [1, 0, 1, 0, 1]        3         4.663\n",
      "20  [0, 0, 1, 1, 1, 1, 1, 0]  [1, 0, 0, 0, 1]        3         4.913\n",
      "30  [1, 0, 1, 0, 1, 1, 1, 1]  [1, 1, 0, 0, 1]        3         4.992\n",
      "1   [1, 0, 1, 1, 1, 0, 1, 1]  [1, 0, 1, 1, 0]        3         6.461\n",
      "21  [0, 0, 1, 0, 1, 1, 1, 1]  [1, 0, 0, 0, 1]        3         7.304\n",
      "                  data_index           answer  carries  solving_time\n",
      "47  [1, 0, 1, 1, 0, 1, 0, 1]  [1, 0, 0, 0, 0]        4         3.617\n",
      "14  [0, 1, 1, 1, 1, 1, 1, 1]  [1, 0, 1, 1, 0]        4         4.507\n",
      "46  [1, 0, 0, 1, 0, 1, 1, 1]  [1, 0, 0, 0, 0]        4         4.991\n",
      "13  [0, 1, 1, 1, 1, 1, 0, 1]  [1, 0, 1, 0, 0]        4         5.429\n",
      "22  [0, 1, 0, 1, 1, 1, 1, 1]  [1, 0, 1, 0, 0]        4         5.569\n",
      "8   [1, 0, 0, 1, 1, 1, 1, 1]  [1, 1, 0, 0, 0]        4         5.773\n",
      "29  [0, 1, 1, 1, 1, 0, 1, 1]  [1, 0, 0, 1, 0]        4         6.459\n",
      "15  [1, 1, 0, 1, 1, 1, 1, 1]  [1, 1, 1, 0, 0]        4         6.585\n",
      "23  [0, 1, 0, 1, 1, 0, 1, 1]  [1, 0, 0, 0, 0]        4         6.663\n",
      "4   [1, 1, 1, 1, 0, 1, 0, 1]  [1, 0, 1, 0, 0]        4         8.210\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_16_09_48.18666_1999_2_3_PREMEDICINE.result\n",
      "Means\n",
      "carries\n",
      "0    3.5880\n",
      "1    4.2574\n",
      "2    4.9886\n",
      "3    5.0286\n",
      "4    4.8081\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0    4.394693\n",
      "1    5.682031\n",
      "2    7.196444\n",
      "3    8.274391\n",
      "4    5.799063\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index           answer  carries  solving_time\n",
      "24  [1, 1, 1, 0, 0, 0, 0, 0]  [0, 1, 1, 1, 0]        0         3.132\n",
      "20  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 1, 0, 0]        0         3.143\n",
      "39  [0, 0, 1, 0, 0, 1, 0, 1]  [0, 0, 1, 1, 1]        0         3.307\n",
      "46  [0, 0, 0, 1, 0, 1, 0, 0]  [0, 0, 1, 0, 1]        0         3.334\n",
      "42  [0, 0, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1, 1]        0         3.351\n",
      "36  [0, 0, 1, 0, 1, 0, 0, 0]  [0, 1, 0, 1, 0]        0         3.583\n",
      "40  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 0, 1, 1, 1]        0         3.726\n",
      "13  [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 1, 0]        0         3.945\n",
      "26  [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 0, 1]        0         4.101\n",
      "8   [0, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 0, 1]        0         4.258\n",
      "                  data_index           answer  carries  solving_time\n",
      "23  [1, 0, 0, 1, 1, 1, 1, 0]  [1, 0, 1, 1, 1]        1         3.367\n",
      "33  [1, 0, 0, 0, 1, 0, 1, 1]  [1, 0, 0, 1, 1]        1         3.523\n",
      "35  [1, 0, 0, 1, 1, 0, 1, 0]  [1, 0, 0, 1, 1]        1         3.742\n",
      "29  [1, 1, 1, 1, 1, 0, 0, 0]  [1, 0, 1, 1, 1]        1         3.866\n",
      "10  [0, 1, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0, 0]        1         3.992\n",
      "28  [1, 0, 1, 0, 0, 0, 1, 0]  [0, 1, 1, 0, 0]        1         4.132\n",
      "18  [1, 0, 0, 1, 1, 1, 0, 0]  [1, 0, 1, 0, 1]        1         4.554\n",
      "3   [1, 0, 1, 0, 1, 1, 0, 0]  [1, 0, 1, 1, 0]        1         4.711\n",
      "14  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 0, 1]        1         5.148\n",
      "1   [1, 1, 0, 1, 1, 0, 0, 0]  [1, 0, 1, 0, 1]        1         5.539\n",
      "                  data_index           answer  carries  solving_time\n",
      "49  [0, 1, 1, 0, 1, 1, 0, 1]  [1, 0, 0, 1, 1]        2         3.694\n",
      "11  [1, 1, 0, 0, 0, 1, 0, 0]  [1, 0, 0, 0, 0]        2         3.727\n",
      "47  [1, 0, 0, 1, 1, 1, 0, 1]  [1, 0, 1, 1, 0]        2         3.976\n",
      "48  [1, 0, 0, 1, 1, 0, 0, 1]  [1, 0, 0, 1, 0]        2         4.383\n",
      "30  [0, 1, 1, 1, 0, 0, 1, 0]  [0, 1, 0, 0, 1]        2         4.710\n",
      "19  [0, 0, 1, 0, 0, 1, 1, 1]  [0, 1, 0, 0, 1]        2         4.994\n",
      "6   [0, 1, 1, 0, 0, 0, 1, 0]  [0, 1, 0, 0, 0]        2         5.445\n",
      "31  [1, 1, 0, 1, 0, 1, 0, 0]  [1, 0, 0, 0, 1]        2         5.851\n",
      "44  [0, 0, 1, 1, 0, 0, 0, 1]  [0, 0, 1, 0, 0]        2         6.115\n",
      "7   [1, 0, 1, 1, 0, 0, 1, 1]  [0, 1, 1, 1, 0]        2         6.991\n",
      "                  data_index           answer  carries  solving_time\n",
      "45  [1, 1, 1, 0, 0, 0, 1, 0]  [1, 0, 0, 0, 0]        3         3.491\n",
      "27  [1, 1, 1, 0, 0, 1, 1, 0]  [1, 0, 1, 0, 0]        3         3.569\n",
      "17  [0, 1, 1, 0, 1, 1, 1, 1]  [1, 0, 1, 0, 1]        3         3.820\n",
      "15  [1, 0, 1, 0, 1, 1, 1, 1]  [1, 1, 0, 0, 1]        3         4.163\n",
      "21  [1, 0, 0, 1, 1, 0, 1, 1]  [1, 0, 1, 0, 0]        3         4.679\n",
      "25  [1, 0, 1, 1, 1, 0, 1, 1]  [1, 0, 1, 1, 0]        3         4.868\n",
      "0   [1, 1, 1, 0, 1, 1, 1, 1]  [1, 1, 1, 0, 1]        3         4.990\n",
      "22  [0, 1, 1, 1, 1, 1, 1, 0]  [1, 0, 1, 0, 1]        3         5.257\n",
      "32  [0, 1, 1, 1, 0, 0, 0, 1]  [0, 1, 0, 0, 0]        3         6.661\n",
      "2   [1, 0, 1, 1, 1, 0, 0, 1]  [1, 0, 1, 0, 0]        3         8.788\n",
      "                  data_index           answer  carries  solving_time\n",
      "41  [1, 1, 1, 1, 0, 0, 0, 1]  [1, 0, 0, 0, 0]        4         3.892\n",
      "37  [1, 0, 1, 1, 0, 1, 1, 1]  [1, 0, 0, 1, 0]        4         4.245\n",
      "43  [0, 1, 0, 1, 1, 1, 1, 1]  [1, 0, 1, 0, 0]        4         4.647\n",
      "16  [1, 1, 1, 1, 1, 0, 1, 1]  [1, 1, 0, 1, 0]        4         4.726\n",
      "4   [1, 0, 1, 1, 1, 1, 0, 1]  [1, 1, 0, 0, 0]        4         4.742\n",
      "38  [1, 1, 1, 1, 1, 0, 0, 1]  [1, 1, 0, 0, 0]        4         4.879\n",
      "34  [1, 0, 0, 1, 0, 1, 1, 1]  [1, 0, 0, 0, 0]        4         4.913\n",
      "12  [0, 1, 1, 1, 1, 1, 1, 1]  [1, 0, 1, 1, 0]        4         5.085\n",
      "5   [0, 1, 1, 1, 1, 1, 0, 1]  [1, 0, 1, 0, 0]        4         5.351\n",
      "9   [0, 0, 0, 1, 1, 1, 1, 1]  [1, 0, 0, 0, 0]        4         5.601\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_00_41.35484_1998_2_3_HUMANITIES.result\n",
      "Means\n",
      "carries\n",
      "0    3.784200\n",
      "1    4.226100\n",
      "2    4.436500\n",
      "3    6.034889\n",
      "4    5.350900\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0    5.141415\n",
      "1    6.368277\n",
      "2    6.777782\n",
      "3    9.281191\n",
      "4    7.882334\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index           answer  carries  solving_time\n",
      "33  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 1, 1, 1]        0         3.100\n",
      "28  [0, 0, 1, 0, 1, 0, 0, 0]  [0, 1, 0, 1, 0]        0         3.195\n",
      "17  [1, 1, 1, 0, 0, 0, 0, 0]  [0, 1, 1, 1, 0]        0         3.242\n",
      "3   [1, 0, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1, 1]        0         3.321\n",
      "22  [1, 1, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1, 1]        0         3.633\n",
      "1   [0, 1, 1, 1, 1, 0, 0, 0]  [0, 1, 1, 1, 1]        0         3.730\n",
      "15  [1, 0, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1, 1]        0         3.883\n",
      "12  [1, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 1, 1, 1]        0         4.148\n",
      "13  [0, 1, 0, 1, 0, 0, 0, 0]  [0, 0, 1, 0, 1]        0         4.243\n",
      "36  [0, 0, 0, 0, 1, 1, 1, 0]  [0, 1, 1, 1, 0]        0         5.347\n",
      "                  data_index           answer  carries  solving_time\n",
      "34  [1, 1, 0, 0, 1, 0, 0, 1]  [1, 0, 1, 0, 1]        1         2.992\n",
      "40  [1, 0, 1, 0, 1, 1, 0, 0]  [1, 0, 1, 1, 0]        1         3.179\n",
      "32  [1, 1, 1, 0, 1, 0, 0, 1]  [1, 0, 1, 1, 1]        1         3.445\n",
      "29  [1, 0, 0, 0, 1, 0, 1, 1]  [1, 0, 0, 1, 1]        1         3.508\n",
      "8   [1, 0, 0, 0, 1, 0, 1, 0]  [1, 0, 0, 1, 0]        1         4.086\n",
      "7   [0, 0, 1, 0, 1, 0, 1, 0]  [0, 1, 1, 0, 0]        1         4.133\n",
      "44  [1, 1, 1, 0, 1, 0, 0, 0]  [1, 0, 1, 1, 0]        1         4.490\n",
      "2   [1, 0, 0, 1, 1, 0, 1, 0]  [1, 0, 0, 1, 1]        1         4.492\n",
      "10  [1, 0, 0, 1, 0, 0, 0, 1]  [0, 1, 0, 1, 0]        1         5.554\n",
      "37  [0, 1, 1, 1, 0, 1, 0, 0]  [0, 1, 0, 1, 1]        1         6.382\n",
      "                  data_index           answer  carries  solving_time\n",
      "47  [0, 1, 1, 1, 1, 1, 0, 0]  [1, 0, 0, 1, 1]        2         3.554\n",
      "23  [0, 1, 1, 0, 0, 0, 1, 0]  [0, 1, 0, 0, 0]        2         3.616\n",
      "31  [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1, 1]        2         3.741\n",
      "16  [1, 1, 0, 0, 1, 1, 0, 0]  [1, 1, 0, 0, 0]        2         3.742\n",
      "5   [1, 0, 1, 1, 1, 0, 1, 0]  [1, 0, 1, 0, 1]        2         3.820\n",
      "4   [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0, 0]        2         4.083\n",
      "42  [0, 1, 0, 1, 1, 1, 0, 0]  [1, 0, 0, 0, 1]        2         4.210\n",
      "19  [1, 0, 1, 1, 0, 0, 0, 1]  [0, 1, 1, 0, 0]        2         4.539\n",
      "45  [0, 0, 1, 1, 0, 0, 1, 1]  [0, 0, 1, 1, 0]        2         5.990\n",
      "14  [0, 1, 0, 1, 1, 1, 1, 0]  [1, 0, 0, 1, 1]        2         7.070\n",
      "                  data_index           answer  carries  solving_time\n",
      "35  [1, 1, 1, 0, 0, 1, 1, 0]  [1, 0, 1, 0, 0]        3         4.007\n",
      "25  [1, 1, 1, 0, 1, 0, 1, 1]  [1, 1, 0, 0, 1]        3         4.648\n",
      "41  [0, 1, 1, 0, 1, 0, 1, 1]  [1, 0, 0, 0, 1]        3         4.804\n",
      "21  [0, 1, 1, 1, 1, 0, 1, 0]  [1, 0, 0, 0, 1]        3         4.867\n",
      "26  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 0, 0, 1]        3         5.992\n",
      "0   [0, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 0, 0, 0]        3         6.414\n",
      "49  [0, 1, 1, 1, 0, 1, 1, 1]  [0, 1, 1, 1, 0]        3         7.069\n",
      "9   [1, 0, 0, 1, 1, 0, 1, 1]  [1, 0, 1, 0, 0]        3         7.523\n",
      "24  [0, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0, 0]        3         8.990\n",
      "                  data_index           answer  carries  solving_time\n",
      "48  [1, 1, 1, 1, 1, 1, 0, 1]  [1, 1, 1, 0, 0]        4         3.679\n",
      "46  [0, 0, 0, 1, 1, 1, 1, 1]  [1, 0, 0, 0, 0]        4         4.163\n",
      "39  [1, 1, 0, 1, 1, 1, 1, 1]  [1, 1, 1, 0, 0]        4         4.491\n",
      "20  [0, 0, 1, 1, 1, 1, 1, 1]  [1, 0, 0, 1, 0]        4         4.632\n",
      "38  [1, 0, 1, 1, 0, 1, 0, 1]  [1, 0, 0, 0, 0]        4         4.929\n",
      "18  [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 0, 0, 0]        4         5.070\n",
      "6   [0, 1, 0, 1, 1, 1, 1, 1]  [1, 0, 1, 0, 0]        4         5.492\n",
      "27  [1, 0, 0, 1, 1, 1, 1, 1]  [1, 1, 0, 0, 0]        4         6.616\n",
      "30  [0, 0, 1, 1, 1, 1, 0, 1]  [1, 0, 0, 0, 0]        4         6.992\n",
      "11  [1, 1, 1, 1, 0, 1, 1, 1]  [1, 0, 1, 1, 0]        4         7.445\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_16_12_04.15214_1997_2_2_POLITICAL SCIENCE.result\n",
      "Means\n",
      "carries\n",
      "0    4.6512\n",
      "1    5.7269\n",
      "2    7.7107\n",
      "3    8.3424\n",
      "4    9.8000\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     6.699285\n",
      "1     7.765018\n",
      "2    16.827999\n",
      "3    14.122795\n",
      "4    14.483594\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index           answer  carries  solving_time\n",
      "27  [0, 0, 0, 0, 0, 1, 0, 0]  [0, 0, 1, 0, 0]        0         3.461\n",
      "48  [1, 1, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1, 1]        0         3.773\n",
      "37  [1, 1, 0, 1, 0, 0, 0, 0]  [0, 1, 1, 0, 1]        0         4.039\n",
      "39  [0, 0, 0, 1, 1, 0, 0, 0]  [0, 1, 0, 0, 1]        0         4.085\n",
      "26  [1, 0, 1, 0, 0, 0, 0, 0]  [0, 1, 0, 1, 0]        0         4.117\n",
      "43  [0, 0, 1, 1, 0, 1, 0, 0]  [0, 0, 1, 1, 1]        0         4.429\n",
      "20  [1, 1, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 0, 1]        0         5.023\n",
      "34  [0, 0, 0, 0, 1, 1, 0, 1]  [0, 1, 1, 0, 1]        0         5.102\n",
      "14  [0, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 0, 1]        0         5.601\n",
      "16  [0, 0, 0, 0, 0, 0, 0, 1]  [0, 0, 0, 0, 1]        0         6.882\n",
      "                  data_index           answer  carries  solving_time\n",
      "19  [1, 1, 0, 0, 1, 0, 0, 1]  [1, 0, 1, 0, 1]        1         4.367\n",
      "47  [1, 0, 0, 0, 1, 1, 1, 1]  [1, 0, 1, 1, 1]        1         4.710\n",
      "42  [1, 1, 0, 0, 1, 0, 1, 1]  [1, 0, 1, 1, 1]        1         4.991\n",
      "15  [0, 0, 0, 1, 0, 0, 0, 1]  [0, 0, 0, 1, 0]        1         5.273\n",
      "49  [0, 0, 0, 1, 1, 0, 0, 1]  [0, 1, 0, 1, 0]        1         5.319\n",
      "18  [1, 0, 1, 0, 0, 0, 1, 0]  [0, 1, 1, 0, 0]        1         5.910\n",
      "25  [0, 0, 0, 1, 0, 1, 0, 1]  [0, 0, 1, 1, 0]        1         5.913\n",
      "32  [1, 0, 0, 1, 0, 0, 0, 1]  [0, 1, 0, 1, 0]        1         6.054\n",
      "13  [1, 0, 0, 1, 1, 1, 1, 0]  [1, 0, 1, 1, 1]        1         7.350\n",
      "8   [1, 0, 0, 1, 1, 1, 0, 0]  [1, 0, 1, 0, 1]        1         7.382\n",
      "                  data_index           answer  carries  solving_time\n",
      "11  [1, 1, 1, 0, 1, 1, 0, 1]  [1, 1, 0, 1, 1]        2         4.539\n",
      "3   [1, 0, 1, 0, 1, 0, 1, 0]  [1, 0, 1, 0, 0]        2         4.583\n",
      "40  [0, 1, 1, 1, 1, 1, 0, 0]  [1, 0, 0, 1, 1]        2         5.007\n",
      "9   [0, 1, 0, 0, 1, 1, 1, 1]  [1, 0, 0, 1, 1]        2         5.473\n",
      "12  [0, 1, 0, 0, 1, 1, 0, 1]  [1, 0, 0, 0, 1]        2         6.302\n",
      "36  [1, 0, 1, 1, 0, 0, 1, 1]  [0, 1, 1, 1, 0]        2         6.648\n",
      "10  [0, 1, 1, 1, 0, 0, 1, 0]  [0, 1, 0, 0, 1]        2         6.960\n",
      "5   [1, 0, 1, 1, 1, 0, 1, 0]  [1, 0, 1, 0, 1]        2         7.396\n",
      "6   [1, 1, 0, 1, 1, 0, 0, 1]  [1, 0, 1, 1, 0]        2        10.522\n",
      "0   [0, 0, 1, 1, 1, 0, 0, 1]  [0, 1, 1, 0, 0]        2        19.677\n",
      "                  data_index           answer  carries  solving_time\n",
      "41  [1, 1, 1, 0, 1, 0, 1, 0]  [1, 1, 0, 0, 0]        3         5.288\n",
      "21  [1, 1, 1, 0, 1, 1, 1, 1]  [1, 1, 1, 0, 1]        3         6.085\n",
      "46  [1, 1, 1, 0, 1, 0, 1, 1]  [1, 1, 0, 0, 1]        3         6.116\n",
      "38  [0, 1, 1, 0, 1, 1, 1, 1]  [1, 0, 1, 0, 1]        3         6.288\n",
      "29  [1, 0, 1, 0, 0, 1, 1, 1]  [1, 0, 0, 0, 1]        3         7.740\n",
      "23  [1, 0, 1, 0, 1, 1, 1, 0]  [1, 1, 0, 0, 0]        3         8.382\n",
      "33  [0, 1, 1, 0, 1, 1, 1, 0]  [1, 0, 1, 0, 0]        3         8.850\n",
      "1   [1, 1, 1, 1, 0, 1, 1, 0]  [1, 0, 1, 0, 1]        3         8.992\n",
      "2   [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 0, 0, 1]        3        10.600\n",
      "22  [1, 0, 0, 1, 1, 0, 1, 1]  [1, 0, 1, 0, 0]        3        15.083\n",
      "                  data_index           answer  carries  solving_time\n",
      "17  [1, 0, 1, 1, 1, 1, 1, 1]  [1, 1, 0, 1, 0]        4         6.757\n",
      "44  [0, 1, 1, 1, 1, 0, 1, 1]  [1, 0, 0, 1, 0]        4         7.553\n",
      "35  [1, 1, 1, 1, 1, 1, 1, 1]  [1, 1, 1, 1, 0]        4         7.788\n",
      "4   [0, 1, 1, 1, 1, 1, 1, 1]  [1, 0, 1, 1, 0]        4         9.398\n",
      "24  [1, 1, 0, 1, 1, 0, 1, 1]  [1, 1, 0, 0, 0]        4         9.537\n",
      "30  [0, 1, 0, 1, 1, 1, 1, 1]  [1, 0, 1, 0, 0]        4        10.021\n",
      "7   [1, 1, 1, 1, 0, 0, 1, 1]  [1, 0, 0, 1, 0]        4        10.085\n",
      "45  [1, 0, 0, 1, 1, 1, 1, 1]  [1, 1, 0, 0, 0]        4        10.350\n",
      "28  [1, 1, 1, 1, 1, 0, 0, 1]  [1, 1, 0, 0, 0]        4        11.459\n",
      "31  [0, 1, 0, 1, 1, 0, 1, 1]  [1, 0, 0, 0, 0]        4        15.052\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_19_58.38902_2000_1_4_MEDICINE.result\n",
      "Means\n",
      "carries\n",
      "0    2.9148\n",
      "1    3.3406\n",
      "2    4.0240\n",
      "3    4.4054\n",
      "4    5.1063\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0    3.950475\n",
      "1    4.680553\n",
      "2    6.287486\n",
      "3    6.848632\n",
      "4    8.252119\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index           answer  carries  solving_time\n",
      "22  [0, 1, 1, 1, 0, 0, 0, 0]  [0, 0, 1, 1, 1]        0         2.347\n",
      "19  [0, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 0, 1]        0         2.429\n",
      "49  [0, 0, 1, 1, 0, 1, 0, 0]  [0, 0, 1, 1, 1]        0         2.554\n",
      "20  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 0, 0, 1]        0         2.664\n",
      "47  [0, 0, 0, 0, 1, 0, 1, 0]  [0, 1, 0, 1, 0]        0         2.726\n",
      "15  [0, 0, 0, 0, 1, 0, 0, 1]  [0, 1, 0, 0, 1]        0         2.727\n",
      "29  [0, 1, 0, 0, 0, 0, 1, 0]  [0, 0, 1, 1, 0]        0         3.054\n",
      "40  [0, 0, 1, 0, 1, 1, 0, 1]  [0, 1, 1, 1, 1]        0         3.163\n",
      "9   [0, 1, 1, 0, 0, 0, 0, 0]  [0, 0, 1, 1, 0]        0         3.476\n",
      "7   [0, 0, 0, 1, 1, 0, 1, 0]  [0, 1, 0, 1, 1]        0         4.008\n",
      "                  data_index           answer  carries  solving_time\n",
      "18  [0, 0, 1, 1, 0, 0, 1, 0]  [0, 0, 1, 0, 1]        1         2.558\n",
      "46  [0, 1, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0, 0]        1         2.785\n",
      "44  [1, 0, 0, 1, 1, 0, 1, 0]  [1, 0, 0, 1, 1]        1         2.789\n",
      "5   [1, 0, 0, 0, 1, 0, 0, 1]  [1, 0, 0, 0, 1]        1         3.055\n",
      "37  [1, 1, 0, 0, 1, 0, 0, 0]  [1, 0, 1, 0, 0]        1         3.145\n",
      "24  [1, 0, 1, 0, 1, 1, 0, 1]  [1, 0, 1, 1, 1]        1         3.398\n",
      "25  [0, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 0, 0, 1]        1         3.432\n",
      "45  [0, 1, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 0, 1]        1         3.538\n",
      "10  [0, 0, 0, 1, 0, 0, 0, 1]  [0, 0, 0, 1, 0]        1         3.808\n",
      "30  [1, 0, 1, 1, 0, 0, 1, 0]  [0, 1, 1, 0, 1]        1         4.898\n",
      "                  data_index           answer  carries  solving_time\n",
      "17  [1, 1, 0, 1, 0, 1, 0, 0]  [1, 0, 0, 0, 1]        2         3.148\n",
      "43  [0, 1, 1, 1, 1, 1, 0, 0]  [1, 0, 0, 1, 1]        2         3.312\n",
      "48  [0, 1, 1, 0, 0, 1, 1, 0]  [0, 1, 1, 0, 0]        2         3.397\n",
      "16  [1, 1, 0, 1, 0, 1, 1, 0]  [1, 0, 0, 1, 1]        2         3.585\n",
      "27  [1, 1, 1, 1, 1, 1, 0, 0]  [1, 1, 0, 1, 1]        2         3.585\n",
      "21  [0, 1, 1, 0, 1, 1, 0, 1]  [1, 0, 0, 1, 1]        2         3.621\n",
      "38  [0, 0, 1, 1, 1, 0, 0, 1]  [0, 1, 1, 0, 0]        2         3.898\n",
      "26  [1, 1, 0, 1, 1, 1, 0, 0]  [1, 1, 0, 0, 1]        2         4.211\n",
      "14  [0, 0, 0, 1, 1, 0, 1, 1]  [0, 1, 1, 0, 0]        2         4.445\n",
      "13  [1, 0, 1, 1, 0, 0, 0, 1]  [0, 1, 1, 0, 0]        2         7.038\n",
      "                  data_index           answer  carries  solving_time\n",
      "23  [1, 1, 0, 1, 0, 1, 0, 1]  [1, 0, 0, 1, 0]        3         3.254\n",
      "36  [0, 1, 1, 0, 1, 0, 1, 0]  [1, 0, 0, 0, 0]        3         3.713\n",
      "8   [1, 1, 1, 1, 1, 1, 1, 0]  [1, 1, 1, 0, 1]        3         3.728\n",
      "6   [1, 0, 1, 0, 1, 1, 1, 1]  [1, 1, 0, 0, 1]        3         3.789\n",
      "41  [1, 1, 0, 1, 1, 1, 0, 1]  [1, 1, 0, 1, 0]        3         3.930\n",
      "28  [1, 0, 1, 1, 1, 0, 0, 1]  [1, 0, 1, 0, 0]        3         4.065\n",
      "11  [1, 1, 1, 1, 0, 0, 1, 0]  [1, 0, 0, 0, 1]        3         4.288\n",
      "0   [0, 1, 1, 0, 1, 0, 1, 1]  [1, 0, 0, 0, 1]        3         4.523\n",
      "32  [1, 1, 1, 0, 0, 1, 1, 0]  [1, 0, 1, 0, 0]        3         5.241\n",
      "2   [1, 1, 1, 0, 1, 1, 1, 1]  [1, 1, 1, 0, 1]        3         7.523\n",
      "                  data_index           answer  carries  solving_time\n",
      "34  [1, 1, 1, 1, 1, 0, 0, 1]  [1, 1, 0, 0, 0]        4         3.458\n",
      "39  [0, 0, 1, 1, 1, 1, 0, 1]  [1, 0, 0, 0, 0]        4         3.711\n",
      "33  [1, 0, 1, 1, 1, 1, 0, 1]  [1, 1, 0, 0, 0]        4         3.882\n",
      "31  [1, 0, 1, 1, 0, 1, 0, 1]  [1, 0, 0, 0, 0]        4         4.643\n",
      "42  [0, 0, 1, 1, 1, 1, 1, 1]  [1, 0, 0, 1, 0]        4         4.725\n",
      "4   [0, 0, 0, 1, 1, 1, 1, 1]  [1, 0, 0, 0, 0]        4         4.976\n",
      "12  [0, 1, 1, 1, 1, 0, 0, 1]  [1, 0, 0, 0, 0]        4         5.008\n",
      "3   [1, 1, 0, 1, 1, 0, 1, 1]  [1, 1, 0, 0, 0]        4         5.490\n",
      "35  [0, 1, 1, 1, 1, 1, 0, 1]  [1, 0, 1, 0, 0]        4         6.304\n",
      "1   [1, 1, 1, 1, 0, 1, 1, 1]  [1, 0, 1, 1, 0]        4         8.866\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_15_00_44.27406_2000_1_3_MATHEMATICS.result\n",
      "Means\n",
      "carries\n",
      "0    3.1150\n",
      "1    3.5857\n",
      "2    3.9536\n",
      "3    4.9708\n",
      "4    4.7402\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0    3.914880\n",
      "1    4.966659\n",
      "2    4.842405\n",
      "3    7.970615\n",
      "4    7.052906\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index           answer  carries  solving_time\n",
      "18  [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 0, 1, 1]        0         2.617\n",
      "9   [0, 0, 1, 0, 1, 1, 0, 0]  [0, 1, 1, 1, 0]        0         2.633\n",
      "37  [0, 0, 1, 0, 0, 1, 0, 1]  [0, 0, 1, 1, 1]        0         2.800\n",
      "39  [0, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1, 1]        0         2.897\n",
      "6   [0, 0, 1, 1, 1, 1, 0, 0]  [0, 1, 1, 1, 1]        0         2.977\n",
      "38  [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 0, 1]        0         3.132\n",
      "17  [0, 1, 1, 0, 1, 0, 0, 0]  [0, 1, 1, 1, 0]        0         3.304\n",
      "31  [0, 0, 0, 0, 1, 0, 0, 1]  [0, 1, 0, 0, 1]        0         3.446\n",
      "11  [1, 0, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1, 1]        0         3.555\n",
      "30  [0, 0, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1, 1]        0         3.789\n",
      "                  data_index           answer  carries  solving_time\n",
      "14  [0, 1, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1, 1]        1         2.617\n",
      "10  [0, 1, 0, 1, 1, 0, 0, 1]  [0, 1, 1, 1, 0]        1         2.711\n",
      "19  [0, 0, 1, 0, 0, 0, 1, 0]  [0, 0, 1, 0, 0]        1         3.210\n",
      "16  [1, 1, 0, 1, 1, 0, 1, 0]  [1, 0, 1, 1, 1]        1         3.383\n",
      "21  [1, 0, 1, 1, 0, 0, 1, 0]  [0, 1, 1, 0, 1]        1         3.510\n",
      "40  [0, 1, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0, 0]        1         3.663\n",
      "28  [0, 0, 1, 1, 0, 0, 1, 0]  [0, 0, 1, 0, 1]        1         3.695\n",
      "44  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 0, 1]        1         3.726\n",
      "43  [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 1, 1, 0]        1         4.616\n",
      "27  [1, 0, 0, 0, 1, 0, 0, 1]  [1, 0, 0, 0, 1]        1         4.726\n",
      "                  data_index           answer  carries  solving_time\n",
      "12  [0, 0, 0, 1, 1, 0, 1, 1]  [0, 1, 1, 0, 0]        2         3.272\n",
      "0   [1, 0, 0, 1, 1, 0, 0, 1]  [1, 0, 0, 1, 0]        2         3.414\n",
      "15  [1, 0, 0, 1, 1, 1, 0, 1]  [1, 0, 1, 1, 0]        2         3.601\n",
      "47  [1, 1, 0, 1, 1, 1, 0, 0]  [1, 1, 0, 0, 1]        2         3.755\n",
      "5   [1, 0, 1, 0, 1, 0, 1, 1]  [1, 0, 1, 0, 1]        2         3.849\n",
      "1   [0, 1, 1, 1, 0, 0, 1, 0]  [0, 1, 0, 0, 1]        2         4.117\n",
      "33  [1, 1, 0, 1, 1, 0, 0, 1]  [1, 0, 1, 1, 0]        2         4.163\n",
      "49  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 1, 0, 0, 1]        2         4.365\n",
      "41  [0, 0, 1, 0, 0, 1, 1, 0]  [0, 1, 0, 0, 0]        2         4.429\n",
      "42  [0, 1, 1, 0, 0, 0, 1, 0]  [0, 1, 0, 0, 0]        2         4.571\n",
      "                  data_index           answer  carries  solving_time\n",
      "25  [0, 1, 1, 0, 1, 1, 1, 0]  [1, 0, 1, 0, 0]        3         3.725\n",
      "22  [0, 1, 1, 1, 0, 0, 1, 1]  [0, 1, 0, 1, 0]        3         3.914\n",
      "3   [0, 1, 0, 1, 1, 1, 0, 1]  [1, 0, 0, 1, 0]        3         3.915\n",
      "24  [1, 0, 1, 0, 0, 1, 1, 0]  [1, 0, 0, 0, 0]        3         4.133\n",
      "48  [1, 1, 1, 1, 1, 0, 1, 0]  [1, 1, 0, 0, 1]        3         4.224\n",
      "20  [0, 1, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0, 0]        3         4.694\n",
      "46  [1, 0, 1, 1, 1, 0, 0, 1]  [1, 0, 1, 0, 0]        3         4.736\n",
      "23  [1, 1, 1, 1, 0, 1, 1, 0]  [1, 0, 1, 0, 1]        3         5.710\n",
      "2   [0, 1, 1, 0, 1, 1, 1, 1]  [1, 0, 1, 0, 1]        3         6.023\n",
      "13  [1, 0, 1, 1, 1, 1, 1, 0]  [1, 1, 0, 0, 1]        3         8.634\n",
      "                  data_index           answer  carries  solving_time\n",
      "34  [0, 0, 0, 1, 1, 1, 1, 1]  [1, 0, 0, 0, 0]        4         3.615\n",
      "45  [0, 0, 1, 1, 1, 1, 1, 1]  [1, 0, 0, 1, 0]        4         3.648\n",
      "35  [1, 0, 1, 1, 1, 1, 1, 1]  [1, 1, 0, 1, 0]        4         3.835\n",
      "7   [0, 1, 1, 1, 1, 1, 1, 1]  [1, 0, 1, 1, 0]        4         4.070\n",
      "29  [1, 0, 0, 1, 0, 1, 1, 1]  [1, 0, 0, 0, 0]        4         4.397\n",
      "4   [1, 0, 1, 1, 0, 1, 0, 1]  [1, 0, 0, 0, 0]        4         4.476\n",
      "32  [0, 1, 1, 1, 1, 1, 0, 1]  [1, 0, 1, 0, 0]        4         4.682\n",
      "36  [1, 0, 1, 1, 0, 1, 1, 1]  [1, 0, 0, 1, 0]        4         5.494\n",
      "26  [1, 1, 1, 1, 0, 0, 1, 1]  [1, 0, 0, 1, 0]        4         6.007\n",
      "8   [1, 1, 0, 1, 1, 0, 1, 1]  [1, 1, 0, 0, 0]        4         7.178\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_15_01_44.57692_1997_1_4_CHEMICAL AND BIOLOGICAL ENGINEERING.result\n",
      "Means\n",
      "carries\n",
      "0    4.402500\n",
      "1    3.656667\n",
      "2    4.590889\n",
      "3    5.911800\n",
      "4    6.236200\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     7.807906\n",
      "1     5.340715\n",
      "2     7.737362\n",
      "3    11.950716\n",
      "4    11.814155\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index           answer  carries  solving_time\n",
      "8   [0, 0, 0, 0, 1, 0, 0, 1]  [0, 1, 0, 0, 1]        0         3.086\n",
      "35  [0, 0, 0, 0, 1, 1, 1, 0]  [0, 1, 1, 1, 0]        0         3.292\n",
      "11  [0, 1, 0, 1, 0, 0, 0, 0]  [0, 0, 1, 0, 1]        0         3.429\n",
      "48  [0, 0, 1, 1, 0, 0, 0, 0]  [0, 0, 0, 1, 1]        0         3.444\n",
      "28  [0, 1, 0, 0, 1, 0, 1, 1]  [0, 1, 1, 1, 1]        0         3.445\n",
      "17  [1, 0, 1, 0, 0, 0, 0, 0]  [0, 1, 0, 1, 0]        0         3.741\n",
      "4   [0, 0, 1, 0, 1, 0, 0, 0]  [0, 1, 0, 1, 0]        0         4.301\n",
      "0   [1, 0, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 1, 0]        0         4.445\n",
      "41  [1, 0, 1, 1, 0, 0, 0, 0]  [0, 1, 0, 1, 1]        0         6.507\n",
      "44  [0, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 1, 1, 1]        0         8.335\n",
      "                  data_index           answer  carries  solving_time\n",
      "34  [1, 0, 0, 0, 1, 0, 0, 0]  [1, 0, 0, 0, 0]        1         2.586\n",
      "36  [1, 0, 0, 0, 1, 0, 0, 1]  [1, 0, 0, 0, 1]        1         2.773\n",
      "5   [1, 0, 0, 0, 1, 1, 0, 1]  [1, 0, 1, 0, 1]        1         2.961\n",
      "26  [0, 1, 0, 1, 1, 0, 0, 1]  [0, 1, 1, 1, 0]        1         3.288\n",
      "3   [0, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 0, 0, 1]        1         3.820\n",
      "23  [1, 0, 1, 0, 0, 0, 1, 0]  [0, 1, 1, 0, 0]        1         3.898\n",
      "47  [1, 0, 1, 1, 1, 0, 0, 0]  [1, 0, 0, 1, 1]        1         3.898\n",
      "27  [1, 0, 1, 0, 1, 0, 0, 0]  [1, 0, 0, 1, 0]        1         4.554\n",
      "18  [0, 1, 1, 1, 0, 1, 0, 0]  [0, 1, 0, 1, 1]        1         5.132\n",
      "                  data_index           answer  carries  solving_time\n",
      "33  [1, 0, 1, 0, 1, 0, 1, 1]  [1, 0, 1, 0, 1]        2         3.007\n",
      "6   [0, 1, 1, 0, 1, 1, 0, 1]  [1, 0, 0, 1, 1]        2         3.477\n",
      "32  [1, 1, 0, 1, 1, 1, 0, 0]  [1, 1, 0, 0, 1]        2         3.805\n",
      "24  [0, 0, 1, 1, 0, 1, 1, 0]  [0, 1, 0, 0, 1]        2         4.023\n",
      "7   [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1, 1]        2         4.055\n",
      "49  [1, 0, 1, 1, 1, 0, 1, 0]  [1, 0, 1, 0, 1]        2         4.148\n",
      "31  [1, 1, 0, 0, 1, 1, 0, 0]  [1, 1, 0, 0, 0]        2         5.070\n",
      "40  [1, 1, 0, 0, 1, 1, 0, 1]  [1, 1, 0, 0, 1]        2         5.445\n",
      "16  [0, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 0, 1]        2         8.288\n",
      "                  data_index           answer  carries  solving_time\n",
      "9   [0, 1, 1, 0, 1, 0, 1, 0]  [1, 0, 0, 0, 0]        3         3.554\n",
      "45  [0, 1, 1, 1, 1, 0, 1, 0]  [1, 0, 0, 0, 1]        3         3.586\n",
      "10  [1, 0, 1, 1, 1, 0, 1, 1]  [1, 0, 1, 1, 0]        3         3.820\n",
      "30  [0, 0, 1, 1, 1, 1, 1, 0]  [1, 0, 0, 0, 1]        3         4.023\n",
      "29  [1, 0, 1, 1, 1, 0, 0, 1]  [1, 0, 1, 0, 0]        3         4.460\n",
      "20  [1, 0, 1, 0, 0, 1, 1, 0]  [1, 0, 0, 0, 0]        3         5.288\n",
      "37  [0, 1, 1, 1, 0, 0, 0, 1]  [0, 1, 0, 0, 0]        3         5.648\n",
      "12  [0, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0, 0]        3         6.101\n",
      "25  [0, 0, 0, 1, 0, 1, 1, 1]  [0, 1, 0, 0, 0]        3        10.303\n",
      "1   [0, 1, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0, 0]        3        12.335\n",
      "                  data_index           answer  carries  solving_time\n",
      "13  [1, 0, 1, 1, 1, 1, 0, 1]  [1, 1, 0, 0, 0]        4         3.788\n",
      "42  [0, 1, 1, 1, 1, 1, 1, 1]  [1, 0, 1, 1, 0]        4         3.835\n",
      "43  [1, 0, 0, 1, 1, 1, 1, 1]  [1, 1, 0, 0, 0]        4         4.428\n",
      "21  [1, 0, 1, 1, 0, 1, 1, 1]  [1, 0, 0, 1, 0]        4         4.506\n",
      "46  [0, 1, 1, 1, 1, 0, 1, 1]  [1, 0, 0, 1, 0]        4         4.695\n",
      "39  [1, 1, 1, 1, 0, 0, 1, 1]  [1, 0, 0, 1, 0]        4         4.975\n",
      "22  [1, 0, 0, 1, 0, 1, 1, 1]  [1, 0, 0, 0, 0]        4         7.334\n",
      "15  [0, 1, 0, 1, 1, 1, 1, 1]  [1, 0, 1, 0, 0]        4         7.835\n",
      "19  [0, 1, 0, 1, 1, 0, 1, 1]  [1, 0, 0, 0, 0]        4         8.460\n",
      "2   [1, 1, 0, 1, 0, 1, 1, 1]  [1, 0, 1, 0, 0]        4        12.506\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_15_09_52.99332_2000_1_3_MECHANICAL ENGINEERING.result\n",
      "Means\n",
      "carries\n",
      "0    3.5419\n",
      "1    4.5370\n",
      "2    6.4484\n",
      "3    6.0212\n",
      "4    8.7409\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     4.375063\n",
      "1     7.376074\n",
      "2    12.816684\n",
      "3     8.691094\n",
      "4    15.938564\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index           answer  carries  solving_time\n",
      "21  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 1, 0, 0]        0         2.976\n",
      "6   [0, 0, 0, 0, 0, 0, 0, 1]  [0, 0, 0, 0, 1]        0         3.004\n",
      "27  [0, 0, 0, 0, 1, 0, 0, 0]  [0, 1, 0, 0, 0]        0         3.153\n",
      "25  [1, 0, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1, 1]        0         3.289\n",
      "29  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 1, 0]        0         3.476\n",
      "49  [0, 0, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1, 1]        0         3.710\n",
      "0   [1, 0, 0, 0, 0, 0, 0, 0]  [0, 1, 0, 0, 0]        0         3.852\n",
      "3   [1, 0, 1, 0, 0, 0, 0, 0]  [0, 1, 0, 1, 0]        0         3.913\n",
      "30  [0, 1, 0, 1, 0, 0, 1, 0]  [0, 0, 1, 1, 1]        0         3.961\n",
      "48  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1, 1]        0         4.085\n",
      "                  data_index           answer  carries  solving_time\n",
      "26  [1, 1, 1, 1, 1, 0, 0, 0]  [1, 0, 1, 1, 1]        1         2.742\n",
      "7   [1, 0, 0, 0, 1, 0, 0, 0]  [1, 0, 0, 0, 0]        1         3.117\n",
      "13  [0, 0, 1, 1, 0, 0, 1, 0]  [0, 0, 1, 0, 1]        1         3.758\n",
      "5   [1, 0, 1, 0, 1, 0, 0, 1]  [1, 0, 0, 1, 1]        1         3.773\n",
      "18  [1, 1, 1, 0, 1, 0, 0, 1]  [1, 0, 1, 1, 1]        1         4.192\n",
      "8   [0, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 0, 1, 1]        1         4.464\n",
      "24  [1, 0, 1, 1, 1, 0, 0, 0]  [1, 0, 0, 1, 1]        1         4.865\n",
      "33  [1, 0, 1, 0, 0, 0, 1, 0]  [0, 1, 1, 0, 0]        1         5.069\n",
      "38  [1, 0, 1, 0, 1, 0, 0, 0]  [1, 0, 0, 1, 0]        1         5.726\n",
      "20  [0, 0, 0, 1, 1, 1, 0, 1]  [0, 1, 1, 1, 0]        1         7.664\n",
      "                  data_index           answer  carries  solving_time\n",
      "19  [1, 0, 1, 0, 1, 0, 1, 1]  [1, 0, 1, 0, 1]        2         3.785\n",
      "11  [0, 0, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0, 0]        2         4.085\n",
      "32  [1, 0, 1, 1, 1, 0, 1, 0]  [1, 0, 1, 0, 1]        2         4.271\n",
      "46  [0, 1, 0, 0, 1, 1, 1, 1]  [1, 0, 0, 1, 1]        2         4.678\n",
      "43  [0, 0, 1, 1, 0, 0, 1, 1]  [0, 0, 1, 1, 0]        2         5.147\n",
      "40  [0, 0, 1, 0, 0, 1, 1, 1]  [0, 1, 0, 0, 1]        2         5.945\n",
      "28  [0, 1, 1, 0, 0, 1, 1, 0]  [0, 1, 1, 0, 0]        2         6.321\n",
      "39  [0, 1, 1, 1, 0, 1, 1, 0]  [0, 1, 1, 0, 1]        2         6.601\n",
      "23  [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1, 1]        2         9.493\n",
      "37  [1, 1, 0, 1, 1, 1, 1, 0]  [1, 1, 0, 1, 1]        2        14.158\n",
      "                  data_index           answer  carries  solving_time\n",
      "12  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 0, 0, 1]        3         4.351\n",
      "16  [1, 1, 1, 0, 1, 1, 1, 0]  [1, 1, 1, 0, 0]        3         4.726\n",
      "4   [0, 1, 1, 1, 0, 0, 1, 1]  [0, 1, 0, 1, 0]        3         5.164\n",
      "45  [1, 1, 1, 0, 1, 0, 1, 0]  [1, 1, 0, 0, 0]        3         5.366\n",
      "1   [1, 0, 1, 1, 1, 1, 1, 0]  [1, 1, 0, 0, 1]        3         5.414\n",
      "10  [1, 1, 1, 0, 0, 1, 1, 1]  [1, 0, 1, 0, 1]        3         5.846\n",
      "17  [0, 1, 1, 1, 1, 0, 1, 0]  [1, 0, 0, 0, 1]        3         6.382\n",
      "34  [0, 1, 0, 1, 1, 1, 0, 1]  [1, 0, 0, 1, 0]        3         6.538\n",
      "14  [0, 1, 1, 0, 1, 0, 1, 1]  [1, 0, 0, 0, 1]        3         8.152\n",
      "31  [0, 1, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0, 0]        3         8.273\n",
      "                  data_index           answer  carries  solving_time\n",
      "47  [0, 1, 1, 1, 1, 0, 0, 1]  [1, 0, 0, 0, 0]        4         4.648\n",
      "35  [0, 1, 1, 1, 1, 1, 1, 1]  [1, 0, 1, 1, 0]        4         5.710\n",
      "41  [1, 1, 0, 1, 1, 1, 1, 1]  [1, 1, 1, 0, 0]        4         6.179\n",
      "15  [0, 1, 0, 1, 1, 1, 1, 1]  [1, 0, 1, 0, 0]        4         6.851\n",
      "44  [1, 0, 0, 1, 0, 1, 1, 1]  [1, 0, 0, 0, 0]        4         7.288\n",
      "42  [1, 1, 1, 1, 0, 1, 1, 1]  [1, 0, 1, 1, 0]        4         7.741\n",
      "36  [1, 1, 0, 1, 0, 1, 1, 1]  [1, 0, 1, 0, 0]        4         9.350\n",
      "2   [1, 1, 1, 1, 0, 0, 0, 1]  [1, 0, 0, 0, 0]        4        11.303\n",
      "22  [0, 0, 1, 1, 1, 1, 1, 1]  [1, 0, 0, 1, 0]        4        11.771\n",
      "9   [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 0, 0, 0]        4        16.568\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_16_09_04.89144_1995_1_4_ELECTRICAL AND COMPUTER ENGINEERING.result\n",
      "Means\n",
      "carries\n",
      "0    4.006100\n",
      "1    4.175700\n",
      "2    5.753700\n",
      "3    7.066000\n",
      "4    9.604875\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     6.518996\n",
      "1     5.304543\n",
      "2     8.075921\n",
      "3     9.698705\n",
      "4    13.474850\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index           answer  carries  solving_time\n",
      "40  [0, 1, 1, 1, 0, 0, 0, 0]  [0, 0, 1, 1, 1]        0         3.007\n",
      "16  [0, 0, 1, 0, 1, 1, 0, 0]  [0, 1, 1, 1, 0]        0         3.023\n",
      "23  [1, 1, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 1, 0]        0         3.180\n",
      "7   [0, 0, 0, 0, 0, 1, 0, 0]  [0, 0, 1, 0, 0]        0         3.212\n",
      "15  [0, 0, 1, 0, 0, 1, 0, 0]  [0, 0, 1, 1, 0]        0         3.382\n",
      "20  [0, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 1, 1, 1]        0         3.882\n",
      "8   [0, 0, 0, 0, 1, 1, 0, 0]  [0, 1, 1, 0, 0]        0         4.227\n",
      "3   [1, 0, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1, 1]        0         4.258\n",
      "9   [1, 1, 1, 0, 0, 0, 0, 0]  [0, 1, 1, 1, 0]        0         4.742\n",
      "0   [0, 1, 1, 0, 1, 0, 0, 0]  [0, 1, 1, 1, 0]        0         7.148\n",
      "                  data_index           answer  carries  solving_time\n",
      "44  [1, 0, 0, 0, 1, 0, 0, 1]  [1, 0, 0, 0, 1]        1         3.444\n",
      "19  [1, 0, 0, 0, 1, 1, 1, 0]  [1, 0, 1, 1, 0]        1         3.457\n",
      "27  [1, 0, 1, 0, 1, 1, 0, 1]  [1, 0, 1, 1, 1]        1         3.789\n",
      "48  [0, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 0, 1, 1]        1         3.820\n",
      "13  [1, 1, 0, 1, 1, 0, 1, 0]  [1, 0, 1, 1, 1]        1         3.945\n",
      "6   [1, 0, 1, 0, 1, 0, 0, 0]  [1, 0, 0, 1, 0]        1         4.211\n",
      "1   [0, 0, 0, 1, 0, 1, 0, 1]  [0, 0, 1, 1, 0]        1         4.586\n",
      "31  [0, 0, 0, 1, 1, 0, 0, 1]  [0, 1, 0, 1, 0]        1         4.756\n",
      "12  [0, 0, 1, 1, 0, 0, 1, 0]  [0, 0, 1, 0, 1]        1         4.836\n",
      "18  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 0, 1]        1         4.913\n",
      "                  data_index           answer  carries  solving_time\n",
      "46  [1, 1, 0, 0, 1, 1, 0, 0]  [1, 1, 0, 0, 0]        2         3.878\n",
      "10  [1, 1, 0, 1, 1, 1, 0, 0]  [1, 1, 0, 0, 1]        2         4.741\n",
      "17  [0, 1, 0, 0, 1, 1, 0, 0]  [1, 0, 0, 0, 0]        2         4.912\n",
      "42  [0, 1, 1, 0, 0, 1, 1, 0]  [0, 1, 1, 0, 0]        2         4.996\n",
      "14  [1, 0, 1, 1, 0, 0, 1, 1]  [0, 1, 1, 1, 0]        2         5.508\n",
      "21  [0, 1, 1, 1, 0, 1, 1, 0]  [0, 1, 1, 0, 1]        2         5.992\n",
      "29  [0, 1, 0, 0, 1, 1, 0, 1]  [1, 0, 0, 0, 1]        2         6.429\n",
      "34  [0, 1, 1, 1, 1, 1, 0, 0]  [1, 0, 0, 1, 1]        2         6.521\n",
      "25  [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1, 1]        2         6.787\n",
      "2   [1, 1, 1, 1, 1, 1, 0, 0]  [1, 1, 0, 1, 1]        2         7.773\n",
      "                  data_index           answer  carries  solving_time\n",
      "47  [0, 1, 1, 1, 0, 1, 1, 1]  [0, 1, 1, 1, 0]        3         5.192\n",
      "37  [1, 1, 1, 0, 1, 0, 1, 1]  [1, 1, 0, 0, 1]        3         5.831\n",
      "41  [1, 1, 1, 0, 1, 1, 1, 0]  [1, 1, 1, 0, 0]        3         6.163\n",
      "49  [1, 0, 0, 1, 1, 0, 1, 1]  [1, 0, 1, 0, 0]        3         6.363\n",
      "32  [0, 1, 1, 0, 1, 1, 1, 1]  [1, 0, 1, 0, 1]        3         6.616\n",
      "39  [1, 0, 1, 1, 1, 1, 1, 0]  [1, 1, 0, 0, 1]        3         6.912\n",
      "43  [0, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 1, 0]        3         7.521\n",
      "30  [0, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0, 0]        3         8.003\n",
      "22  [0, 1, 1, 0, 1, 1, 1, 0]  [1, 0, 1, 0, 0]        3         8.693\n",
      "5   [1, 0, 1, 0, 0, 1, 1, 1]  [1, 0, 0, 0, 1]        3         9.366\n",
      "                  data_index           answer  carries  solving_time\n",
      "45  [1, 0, 0, 1, 1, 1, 1, 1]  [1, 1, 0, 0, 0]        4         7.194\n",
      "26  [1, 0, 1, 1, 1, 1, 1, 1]  [1, 1, 0, 1, 0]        4         7.849\n",
      "35  [1, 1, 1, 1, 0, 0, 1, 1]  [1, 0, 0, 1, 0]        4         7.956\n",
      "4   [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 0, 0, 0]        4         8.382\n",
      "28  [1, 1, 1, 1, 1, 1, 0, 1]  [1, 1, 1, 0, 0]        4        10.750\n",
      "11  [1, 0, 1, 1, 0, 1, 1, 1]  [1, 0, 0, 1, 0]        4        11.367\n",
      "38  [0, 1, 1, 1, 1, 1, 1, 1]  [1, 0, 1, 1, 0]        4        11.397\n",
      "24  [1, 0, 0, 1, 0, 1, 1, 1]  [1, 0, 0, 0, 0]        4        11.944\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_09_48.05041_1997_2_2_KOREAN EDUCATION.result\n",
      "Means\n",
      "carries\n",
      "0    3.9131\n",
      "1    4.2328\n",
      "2    4.4503\n",
      "3    5.4166\n",
      "4    6.1632\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     4.474475\n",
      "1     5.771122\n",
      "2     5.463808\n",
      "3     8.469127\n",
      "4    10.487715\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index           answer  carries  solving_time\n",
      "20  [0, 0, 0, 0, 0, 0, 0, 0]  [0, 0, 0, 0, 0]        0         3.222\n",
      "31  [0, 0, 0, 0, 0, 1, 0, 0]  [0, 0, 1, 0, 0]        0         3.741\n",
      "22  [1, 1, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 1, 0]        0         3.851\n",
      "38  [0, 0, 1, 0, 1, 1, 0, 1]  [0, 1, 1, 1, 1]        0         3.863\n",
      "21  [1, 1, 0, 1, 0, 0, 0, 0]  [0, 1, 1, 0, 1]        0         3.961\n",
      "32  [1, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 1, 1, 1]        0         3.976\n",
      "36  [0, 1, 0, 1, 1, 0, 0, 0]  [0, 1, 1, 0, 1]        0         4.089\n",
      "25  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 1, 1, 1]        0         4.132\n",
      "12  [0, 1, 0, 0, 0, 0, 0, 0]  [0, 0, 1, 0, 0]        0         4.148\n",
      "14  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 1, 0, 0]        0         4.148\n",
      "                  data_index           answer  carries  solving_time\n",
      "49  [1, 0, 0, 0, 1, 0, 0, 1]  [1, 0, 0, 0, 1]        1         3.585\n",
      "33  [1, 0, 1, 0, 0, 0, 1, 0]  [0, 1, 1, 0, 0]        1         3.602\n",
      "42  [0, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 0, 1, 1]        1         3.616\n",
      "27  [1, 1, 0, 0, 1, 0, 1, 1]  [1, 0, 1, 1, 1]        1         3.929\n",
      "29  [1, 0, 0, 0, 1, 0, 1, 0]  [1, 0, 0, 1, 0]        1         3.976\n",
      "19  [1, 0, 0, 0, 1, 1, 1, 0]  [1, 0, 1, 1, 0]        1         4.103\n",
      "4   [1, 1, 0, 1, 0, 0, 0, 1]  [0, 1, 1, 1, 0]        1         4.289\n",
      "9   [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 1, 1, 0]        1         4.386\n",
      "18  [0, 1, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 0, 1]        1         4.679\n",
      "24  [0, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 0, 0, 1]        1         6.163\n",
      "                  data_index           answer  carries  solving_time\n",
      "28  [1, 0, 0, 1, 1, 1, 0, 1]  [1, 0, 1, 1, 0]        2         3.710\n",
      "6   [1, 1, 1, 1, 0, 1, 0, 0]  [1, 0, 0, 1, 1]        2         3.867\n",
      "5   [0, 0, 1, 1, 0, 0, 0, 1]  [0, 0, 1, 0, 0]        2         4.069\n",
      "16  [0, 0, 1, 1, 1, 0, 0, 1]  [0, 1, 1, 0, 0]        2         4.268\n",
      "40  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0, 0]        2         4.351\n",
      "2   [0, 1, 1, 1, 0, 0, 1, 0]  [0, 1, 0, 0, 1]        2         4.554\n",
      "41  [1, 1, 0, 1, 1, 1, 0, 0]  [1, 1, 0, 0, 1]        2         4.585\n",
      "26  [1, 0, 1, 1, 0, 0, 0, 1]  [0, 1, 1, 0, 0]        2         4.680\n",
      "47  [0, 1, 1, 1, 0, 1, 1, 0]  [0, 1, 1, 0, 1]        2         5.209\n",
      "35  [1, 0, 1, 1, 0, 0, 1, 1]  [0, 1, 1, 1, 0]        2         5.210\n",
      "                  data_index           answer  carries  solving_time\n",
      "39  [1, 0, 1, 0, 1, 1, 1, 0]  [1, 1, 0, 0, 0]        3         4.023\n",
      "8   [1, 1, 0, 1, 0, 1, 0, 1]  [1, 0, 0, 1, 0]        3         4.117\n",
      "15  [0, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 1, 0]        3         4.335\n",
      "30  [0, 1, 1, 0, 1, 1, 1, 0]  [1, 0, 1, 0, 0]        3         4.679\n",
      "7   [1, 1, 1, 1, 0, 1, 1, 0]  [1, 0, 1, 0, 1]        3         4.758\n",
      "1   [1, 1, 1, 0, 1, 0, 1, 0]  [1, 1, 0, 0, 0]        3         4.851\n",
      "34  [0, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 0, 0, 0]        3         5.507\n",
      "0   [0, 1, 1, 0, 1, 1, 1, 1]  [1, 0, 1, 0, 1]        3         5.633\n",
      "45  [0, 0, 1, 0, 1, 1, 1, 0]  [1, 0, 0, 0, 0]        3         7.944\n",
      "17  [1, 1, 1, 0, 0, 0, 1, 0]  [1, 0, 0, 0, 0]        3         8.319\n",
      "                  data_index           answer  carries  solving_time\n",
      "10  [0, 1, 1, 1, 1, 0, 1, 1]  [1, 0, 0, 1, 0]        4         4.180\n",
      "11  [1, 0, 1, 1, 1, 1, 0, 1]  [1, 1, 0, 0, 0]        4         4.336\n",
      "23  [0, 0, 1, 1, 1, 1, 1, 1]  [1, 0, 0, 1, 0]        4         4.898\n",
      "3   [1, 0, 1, 1, 1, 1, 1, 1]  [1, 1, 0, 1, 0]        4         4.930\n",
      "44  [1, 1, 1, 1, 0, 1, 0, 1]  [1, 0, 1, 0, 0]        4         5.694\n",
      "13  [1, 1, 1, 1, 1, 0, 1, 1]  [1, 1, 0, 1, 0]        4         5.804\n",
      "46  [1, 1, 1, 1, 0, 0, 1, 1]  [1, 0, 0, 1, 0]        4         5.944\n",
      "37  [1, 1, 0, 1, 1, 1, 1, 1]  [1, 1, 1, 0, 0]        4         5.960\n",
      "48  [1, 1, 1, 1, 0, 1, 1, 1]  [1, 0, 1, 1, 0]        4         8.787\n",
      "43  [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 0, 0, 0]        4        11.099\n"
     ]
    }
   ],
   "source": [
    "operator = 'add'\n",
    "df_results = list()\n",
    "result_files = get_all_result_files()\n",
    "cols = ['data_index', 'answer', 'carries', 'solving_time']\n",
    "for f in result_files:\n",
    "    if get_operator(f) == operator:\n",
    "\n",
    "        df_result = read_result_file(f)\n",
    "        df_result = filter_for_mean_solving_time(df_result, rm_carry_outlier=False, outlier_std=2)\n",
    "        df_result = df_result[df_result['correct'] == True]\n",
    "        #df_result = df_result[df_result['solving_time'] < 30]\n",
    "        df_result = df_result[cols]\n",
    "        df_results.append(df_result)\n",
    "        \n",
    "        st_means = df_result.groupby(['carries'])['solving_time'].mean()\n",
    "        st_stds = df_result.groupby(['carries'])['solving_time'].std()\n",
    "        print_all = True\n",
    "        if print_all:\n",
    "            df_result.boxplot(column=['solving_time'], by='carries')\n",
    "            plt.show()\n",
    "            print(f)\n",
    "            print('Means')\n",
    "            print(st_means)\n",
    "            print('STDs')\n",
    "            print(st_means + 2 * st_stds)\n",
    "            print(df_result[df_result['carries'] == 0].sort_values(by=['solving_time']))\n",
    "            print(df_result[df_result['carries'] == 1].sort_values(by=['solving_time']))\n",
    "            print(df_result[df_result['carries'] == 2].sort_values(by=['solving_time']))\n",
    "            print(df_result[df_result['carries'] == 3].sort_values(by=['solving_time']))\n",
    "            print(df_result[df_result['carries'] == 4].sort_values(by=['solving_time']))\n",
    "        if st_means[2] > st_means[3] and (not print_all):\n",
    "            print(f)\n",
    "            print(st_means)\n",
    "            print(st_means + 2 * st_stds)\n",
    "            print(df_result[df_result['carries'] == 2].sort_values(by=['solving_time']))\n",
    "            print(df_result[df_result['carries'] == 3].sort_values(by=['solving_time']))\n",
    "            pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_20_04.37773_1997_2_2_KOREAN EDUCATION.result\n",
      "Means\n",
      "carries\n",
      "0    3.440500\n",
      "1    4.010900\n",
      "2    6.157800\n",
      "3    9.367333\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     4.139259\n",
      "1     5.020969\n",
      "2     9.688352\n",
      "3    10.907274\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "34  [0, 1, 0, 0, 0, 1, 0, 0]  [0, 0, 0, 0]        0         2.900\n",
      "37  [1, 1, 0, 1, 1, 0, 0, 1]  [0, 1, 0, 0]        0         3.120\n",
      "22  [1, 0, 1, 1, 0, 0, 1, 1]  [1, 0, 0, 0]        0         3.213\n",
      "6   [1, 1, 1, 1, 1, 0, 1, 0]  [0, 1, 0, 1]        0         3.322\n",
      "16  [1, 0, 1, 1, 1, 0, 0, 1]  [0, 0, 1, 0]        0         3.338\n",
      "29  [1, 1, 1, 1, 0, 0, 1, 1]  [1, 1, 0, 0]        0         3.416\n",
      "21  [0, 1, 0, 0, 0, 0, 0, 0]  [0, 1, 0, 0]        0         3.541\n",
      "10  [0, 0, 1, 1, 0, 0, 1, 0]  [0, 0, 0, 1]        0         3.585\n",
      "19  [0, 1, 1, 1, 0, 0, 0, 1]  [0, 1, 1, 0]        0         3.947\n",
      "23  [1, 1, 0, 1, 0, 0, 0, 1]  [1, 1, 0, 0]        0         4.023\n",
      "                  data_index        answer  carries  solving_time\n",
      "7   [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 0, 0]        1         3.104\n",
      "30  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         3.650\n",
      "11  [1, 1, 0, 1, 1, 0, 1, 1]  [0, 0, 1, 0]        1         3.697\n",
      "9   [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         3.793\n",
      "20  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         3.867\n",
      "28  [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 0]        1         4.087\n",
      "25  [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1         4.134\n",
      "31  [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         4.367\n",
      "32  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         4.525\n",
      "4   [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         4.885\n",
      "                  data_index        answer  carries  solving_time\n",
      "8   [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         4.650\n",
      "38  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         5.115\n",
      "26  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         5.774\n",
      "27  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         6.100\n",
      "13  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2         9.150\n",
      "                  data_index        answer  carries  solving_time\n",
      "1   [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         8.554\n",
      "39  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         9.463\n",
      "36  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3        10.085\n",
      "Empty DataFrame\n",
      "Columns: [data_index, answer, carries, solving_time]\n",
      "Index: []\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_02_30.60523_1994_1_3_ARCHITECTURAL ENGINEERING.result\n",
      "Means\n",
      "carries\n",
      "0    3.048900\n",
      "1    4.156500\n",
      "2    6.437333\n",
      "3    6.132400\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     4.416138\n",
      "1     5.805001\n",
      "2    11.242603\n",
      "3     9.763031\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "35  [0, 0, 0, 0, 0, 0, 0, 0]  [0, 0, 0, 0]        0         2.306\n",
      "8   [0, 0, 1, 1, 0, 0, 1, 1]  [0, 0, 0, 0]        0         2.354\n",
      "21  [1, 1, 0, 1, 0, 0, 0, 0]  [1, 1, 0, 1]        0         2.556\n",
      "23  [0, 0, 0, 1, 0, 0, 0, 0]  [0, 0, 0, 1]        0         2.573\n",
      "3   [1, 1, 1, 0, 1, 1, 1, 0]  [0, 0, 0, 0]        0         2.776\n",
      "36  [0, 1, 1, 1, 0, 1, 1, 0]  [0, 0, 0, 1]        0         2.994\n",
      "30  [0, 1, 1, 0, 0, 1, 0, 0]  [0, 0, 1, 0]        0         3.041\n",
      "29  [1, 0, 0, 1, 0, 0, 0, 1]  [1, 0, 0, 0]        0         3.713\n",
      "6   [1, 1, 0, 1, 1, 0, 0, 0]  [0, 1, 0, 1]        0         3.979\n",
      "20  [1, 0, 1, 1, 1, 0, 1, 0]  [0, 0, 0, 1]        0         4.197\n",
      "                  data_index        answer  carries  solving_time\n",
      "5   [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         2.885\n",
      "0   [1, 0, 1, 0, 0, 1, 1, 0]  [0, 1, 0, 0]        1         3.557\n",
      "37  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         3.634\n",
      "4   [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1         3.666\n",
      "27  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         4.087\n",
      "2   [0, 1, 0, 1, 0, 0, 1, 0]  [0, 0, 1, 1]        1         4.181\n",
      "26  [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1]        1         4.416\n",
      "25  [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 0, 0]        1         4.603\n",
      "32  [0, 1, 1, 0, 0, 1, 0, 1]  [0, 0, 0, 1]        1         4.604\n",
      "22  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         5.932\n",
      "                  data_index        answer  carries  solving_time\n",
      "39  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2         3.447\n",
      "28  [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         4.524\n",
      "33  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         4.848\n",
      "31  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         4.869\n",
      "17  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         6.153\n",
      "18  [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2         6.290\n",
      "34  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         7.571\n",
      "19  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         9.867\n",
      "10  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2        10.367\n",
      "                  data_index        answer  carries  solving_time\n",
      "9   [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         3.102\n",
      "24  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         3.571\n",
      "16  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.416\n",
      "11  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         5.572\n",
      "1   [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         6.072\n",
      "12  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         6.587\n",
      "7   [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         6.634\n",
      "13  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         7.431\n",
      "15  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         8.384\n",
      "38  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         8.555\n",
      "Empty DataFrame\n",
      "Columns: [data_index, answer, carries, solving_time]\n",
      "Index: []\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_15_06_33.60021_1997_1_4_CHEMICAL AND BIOLOGICAL ENGINEERING.result\n",
      "Means\n",
      "carries\n",
      "0    2.693400\n",
      "1    3.215111\n",
      "2    4.597125\n",
      "3    4.958000\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0    3.190376\n",
      "1    4.289180\n",
      "2    6.356149\n",
      "3    9.364648\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "17  [1, 1, 0, 1, 0, 1, 0, 1]  [1, 0, 0, 0]        0         2.386\n",
      "27  [1, 1, 1, 1, 0, 0, 1, 1]  [1, 1, 0, 0]        0         2.416\n",
      "7   [1, 0, 1, 0, 0, 0, 0, 0]  [1, 0, 1, 0]        0         2.431\n",
      "22  [1, 1, 1, 1, 1, 1, 1, 1]  [0, 0, 0, 0]        0         2.572\n",
      "23  [1, 1, 0, 1, 0, 0, 0, 1]  [1, 1, 0, 0]        0         2.665\n",
      "25  [0, 1, 1, 1, 0, 1, 1, 0]  [0, 0, 0, 1]        0         2.695\n",
      "35  [1, 0, 1, 1, 0, 0, 0, 0]  [1, 0, 1, 1]        0         2.806\n",
      "29  [1, 1, 1, 0, 0, 0, 0, 0]  [1, 1, 1, 0]        0         2.854\n",
      "37  [1, 0, 1, 1, 1, 0, 1, 1]  [0, 0, 0, 0]        0         3.037\n",
      "39  [0, 1, 1, 1, 0, 0, 0, 0]  [0, 1, 1, 1]        0         3.072\n",
      "                  data_index        answer  carries  solving_time\n",
      "6   [1, 0, 1, 0, 0, 1, 1, 0]  [0, 1, 0, 0]        1         2.526\n",
      "16  [0, 1, 0, 0, 0, 0, 1, 0]  [0, 0, 1, 0]        1         2.635\n",
      "4   [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         2.822\n",
      "21  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         2.846\n",
      "2   [1, 1, 1, 0, 1, 1, 0, 1]  [0, 0, 0, 1]        1         3.366\n",
      "5   [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         3.432\n",
      "33  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         3.475\n",
      "20  [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         3.714\n",
      "0   [1, 0, 1, 0, 1, 0, 0, 1]  [0, 0, 0, 1]        1         4.120\n",
      "                  data_index        answer  carries  solving_time\n",
      "12  [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 1]        2         3.525\n",
      "31  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         3.603\n",
      "11  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         3.775\n",
      "24  [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2         4.541\n",
      "30  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         4.776\n",
      "10  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         5.416\n",
      "19  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         5.554\n",
      "32  [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         5.587\n",
      "                  data_index        answer  carries  solving_time\n",
      "8   [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         3.041\n",
      "14  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         3.072\n",
      "1   [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         3.995\n",
      "36  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         4.071\n",
      "15  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         4.115\n",
      "26  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         4.538\n",
      "34  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         4.836\n",
      "13  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         7.024\n",
      "3   [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         9.930\n",
      "Empty DataFrame\n",
      "Columns: [data_index, answer, carries, solving_time]\n",
      "Index: []\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_16_18_42.39139_1999_2_3_PREMEDICINE.result\n",
      "Means\n",
      "carries\n",
      "0     2.6281\n",
      "1     5.7638\n",
      "2    10.4346\n",
      "3     8.7369\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     3.551001\n",
      "1     9.787533\n",
      "2    16.336614\n",
      "3    13.303469\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "21  [0, 1, 1, 0, 0, 1, 1, 0]  [0, 0, 0, 0]        0         2.009\n",
      "17  [1, 0, 1, 0, 1, 0, 1, 0]  [0, 0, 0, 0]        0         2.134\n",
      "37  [1, 0, 1, 1, 0, 0, 1, 1]  [1, 0, 0, 0]        0         2.306\n",
      "5   [1, 1, 1, 0, 1, 1, 1, 0]  [0, 0, 0, 0]        0         2.448\n",
      "39  [1, 0, 1, 0, 0, 0, 1, 0]  [1, 0, 0, 0]        0         2.634\n",
      "10  [1, 1, 1, 1, 0, 1, 1, 1]  [1, 0, 0, 0]        0         2.635\n",
      "16  [1, 1, 0, 0, 0, 1, 0, 0]  [1, 0, 0, 0]        0         2.666\n",
      "7   [0, 1, 0, 1, 0, 1, 0, 0]  [0, 0, 0, 1]        0         2.866\n",
      "4   [0, 1, 1, 1, 0, 1, 0, 0]  [0, 0, 1, 1]        0         2.964\n",
      "26  [0, 1, 0, 1, 0, 0, 0, 1]  [0, 1, 0, 0]        0         3.619\n",
      "                  data_index        answer  carries  solving_time\n",
      "24  [0, 1, 0, 0, 0, 0, 1, 0]  [0, 0, 1, 0]        1         3.525\n",
      "22  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         3.619\n",
      "32  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         3.837\n",
      "9   [0, 1, 0, 1, 0, 0, 1, 0]  [0, 0, 1, 1]        1         4.931\n",
      "11  [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1         5.603\n",
      "19  [1, 0, 1, 0, 1, 0, 0, 1]  [0, 0, 0, 1]        1         5.619\n",
      "36  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         5.790\n",
      "3   [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1         7.150\n",
      "8   [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         7.728\n",
      "2   [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         9.836\n",
      "                  data_index        answer  carries  solving_time\n",
      "38  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         6.181\n",
      "23  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         6.587\n",
      "20  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         8.348\n",
      "34  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2         9.555\n",
      "15  [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2         9.961\n",
      "14  [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2        10.212\n",
      "1   [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2        12.149\n",
      "0   [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2        12.947\n",
      "29  [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 1]        2        13.102\n",
      "13  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2        15.304\n",
      "                  data_index        answer  carries  solving_time\n",
      "33  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.665\n",
      "18  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         6.606\n",
      "30  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         6.634\n",
      "28  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         7.368\n",
      "27  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         8.039\n",
      "35  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         8.383\n",
      "12  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        10.415\n",
      "25  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3        10.883\n",
      "6   [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3        10.915\n",
      "31  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        12.461\n",
      "Empty DataFrame\n",
      "Columns: [data_index, answer, carries, solving_time]\n",
      "Index: []\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_15_07_38.02637_2000_1_3_MATHEMATICS.result\n",
      "Means\n",
      "carries\n",
      "0    2.8324\n",
      "1    4.5402\n",
      "2    4.7696\n",
      "3    5.6346\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     3.627081\n",
      "1     6.717088\n",
      "2     6.969485\n",
      "3    10.445369\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "15  [0, 1, 1, 1, 0, 0, 1, 1]  [0, 1, 0, 0]        0         2.307\n",
      "23  [1, 1, 1, 0, 1, 1, 0, 0]  [0, 0, 1, 0]        0         2.477\n",
      "39  [1, 0, 1, 0, 0, 0, 1, 0]  [1, 0, 0, 0]        0         2.541\n",
      "2   [1, 0, 1, 1, 1, 0, 0, 1]  [0, 0, 1, 0]        0         2.604\n",
      "37  [1, 1, 0, 0, 0, 1, 0, 0]  [1, 0, 0, 0]        0         2.633\n",
      "35  [1, 1, 1, 1, 0, 0, 1, 0]  [1, 1, 0, 1]        0         2.647\n",
      "19  [0, 1, 1, 1, 0, 0, 1, 0]  [0, 1, 0, 1]        0         3.198\n",
      "7   [1, 1, 1, 1, 1, 0, 1, 1]  [0, 1, 0, 0]        0         3.276\n",
      "22  [1, 1, 1, 0, 1, 0, 1, 0]  [0, 1, 0, 0]        0         3.306\n",
      "1   [0, 0, 1, 1, 0, 0, 0, 1]  [0, 0, 1, 0]        0         3.335\n",
      "                  data_index        answer  carries  solving_time\n",
      "12  [1, 0, 1, 0, 1, 0, 0, 1]  [0, 0, 0, 1]        1         3.635\n",
      "11  [1, 0, 1, 1, 0, 1, 1, 0]  [0, 1, 0, 1]        1         3.790\n",
      "18  [0, 1, 1, 0, 0, 1, 0, 1]  [0, 0, 0, 1]        1         3.853\n",
      "14  [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 1, 0]        1         3.947\n",
      "27  [1, 1, 0, 1, 1, 0, 1, 1]  [0, 0, 1, 0]        1         4.040\n",
      "6   [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1]        1         4.072\n",
      "34  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         4.462\n",
      "36  [0, 1, 0, 1, 0, 0, 1, 0]  [0, 0, 1, 1]        1         4.775\n",
      "31  [1, 1, 1, 0, 1, 1, 0, 1]  [0, 0, 0, 1]        1         5.742\n",
      "20  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         7.086\n",
      "                  data_index        answer  carries  solving_time\n",
      "38  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         3.304\n",
      "5   [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2         3.432\n",
      "16  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         3.695\n",
      "30  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         4.150\n",
      "28  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         4.650\n",
      "17  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         4.957\n",
      "13  [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2         5.557\n",
      "21  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         5.557\n",
      "0   [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2         6.041\n",
      "8   [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         6.353\n",
      "                  data_index        answer  carries  solving_time\n",
      "33  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         3.197\n",
      "25  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         3.371\n",
      "3   [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         4.033\n",
      "24  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         4.150\n",
      "26  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         4.689\n",
      "4   [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         4.728\n",
      "29  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         5.992\n",
      "9   [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         7.384\n",
      "32  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         8.184\n",
      "10  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        10.618\n",
      "Empty DataFrame\n",
      "Columns: [data_index, answer, carries, solving_time]\n",
      "Index: []\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_15_17_38.07868_2000_1_3_MECHANICAL ENGINEERING.result\n",
      "Means\n",
      "carries\n",
      "0    3.273800\n",
      "1    5.301400\n",
      "2    7.005222\n",
      "3    8.455286\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     4.145429\n",
      "1     9.376523\n",
      "2    11.902208\n",
      "3    13.824581\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "20  [0, 1, 0, 0, 0, 1, 0, 0]  [0, 0, 0, 0]        0         2.604\n",
      "6   [1, 0, 0, 1, 0, 0, 0, 1]  [1, 0, 0, 0]        0         2.682\n",
      "25  [0, 1, 1, 0, 0, 1, 1, 0]  [0, 0, 0, 0]        0         2.774\n",
      "0   [0, 1, 0, 1, 0, 1, 0, 1]  [0, 0, 0, 0]        0         3.197\n",
      "30  [0, 1, 1, 1, 0, 0, 0, 1]  [0, 1, 1, 0]        0         3.370\n",
      "32  [1, 0, 1, 1, 1, 0, 0, 0]  [0, 0, 1, 1]        0         3.525\n",
      "24  [1, 0, 1, 1, 1, 0, 1, 0]  [0, 0, 0, 1]        0         3.556\n",
      "16  [1, 1, 0, 1, 1, 0, 0, 1]  [0, 1, 0, 0]        0         3.603\n",
      "12  [0, 1, 0, 1, 0, 0, 0, 0]  [0, 1, 0, 1]        0         3.651\n",
      "26  [1, 1, 0, 1, 0, 1, 0, 0]  [1, 0, 0, 1]        0         3.776\n",
      "                  data_index        answer  carries  solving_time\n",
      "1   [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         3.135\n",
      "34  [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         3.572\n",
      "38  [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         4.056\n",
      "5   [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         4.166\n",
      "13  [1, 0, 1, 0, 0, 1, 1, 0]  [0, 1, 0, 0]        1         4.228\n",
      "17  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         5.040\n",
      "28  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         5.228\n",
      "2   [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1         5.978\n",
      "19  [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1         8.258\n",
      "10  [0, 1, 0, 0, 0, 0, 1, 0]  [0, 0, 1, 0]        1         9.353\n",
      "                  data_index        answer  carries  solving_time\n",
      "33  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         4.040\n",
      "27  [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2         5.275\n",
      "15  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         5.713\n",
      "31  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2         5.836\n",
      "35  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         5.851\n",
      "39  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         6.665\n",
      "29  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2         7.790\n",
      "3   [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2        10.681\n",
      "4   [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2        11.196\n",
      "                  data_index        answer  carries  solving_time\n",
      "14  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         4.884\n",
      "22  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         6.478\n",
      "18  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         7.743\n",
      "21  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         8.290\n",
      "36  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         8.837\n",
      "23  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         9.524\n",
      "11  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3        13.431\n",
      "Empty DataFrame\n",
      "Columns: [data_index, answer, carries, solving_time]\n",
      "Index: []\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_16_15_28.77170_1995_1_4_ELECTRICAL AND COMPUTER ENGINEERING.result\n",
      "Means\n",
      "carries\n",
      "0    3.923000\n",
      "1    4.908889\n",
      "2    6.706125\n",
      "3    6.255667\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     6.022691\n",
      "1     7.243873\n",
      "2    10.731360\n",
      "3     9.031204\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "27  [1, 1, 1, 0, 0, 0, 0, 0]  [1, 1, 1, 0]        0         2.541\n",
      "19  [1, 1, 1, 1, 1, 0, 0, 1]  [0, 1, 1, 0]        0         3.165\n",
      "24  [1, 1, 0, 1, 0, 0, 0, 1]  [1, 1, 0, 0]        0         3.322\n",
      "17  [0, 0, 1, 0, 0, 0, 0, 0]  [0, 0, 1, 0]        0         3.430\n",
      "34  [0, 0, 1, 1, 0, 0, 1, 0]  [0, 0, 0, 1]        0         3.460\n",
      "36  [1, 1, 1, 1, 1, 0, 1, 0]  [0, 1, 0, 1]        0         3.650\n",
      "0   [1, 1, 1, 1, 0, 1, 0, 1]  [1, 0, 1, 0]        0         4.072\n",
      "10  [1, 0, 0, 1, 0, 0, 0, 1]  [1, 0, 0, 0]        0         4.150\n",
      "39  [1, 0, 1, 1, 0, 0, 0, 1]  [1, 0, 1, 0]        0         5.650\n",
      "2   [1, 1, 0, 1, 1, 0, 0, 0]  [0, 1, 0, 1]        0         5.790\n",
      "                  data_index        answer  carries  solving_time\n",
      "31  [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         3.416\n",
      "23  [1, 0, 1, 1, 0, 1, 1, 0]  [0, 1, 0, 1]        1         3.994\n",
      "6   [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         4.011\n",
      "38  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         4.088\n",
      "8   [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         5.025\n",
      "35  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         5.025\n",
      "15  [0, 1, 0, 1, 0, 0, 1, 0]  [0, 0, 1, 1]        1         5.291\n",
      "26  [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1         6.571\n",
      "11  [1, 1, 0, 1, 1, 0, 1, 1]  [0, 0, 1, 0]        1         6.759\n",
      "                  data_index        answer  carries  solving_time\n",
      "28  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         4.478\n",
      "3   [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         4.681\n",
      "25  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         5.322\n",
      "4   [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         6.009\n",
      "20  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         6.040\n",
      "16  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2         8.774\n",
      "18  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         9.149\n",
      "14  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         9.196\n",
      "                  data_index        answer  carries  solving_time\n",
      "32  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         4.791\n",
      "21  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         5.166\n",
      "30  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         5.243\n",
      "29  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.259\n",
      "33  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         5.525\n",
      "22  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         6.259\n",
      "13  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         7.665\n",
      "5   [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         8.165\n",
      "7   [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         8.228\n",
      "Empty DataFrame\n",
      "Columns: [data_index, answer, carries, solving_time]\n",
      "Index: []\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_16_21_57.11743_1997_2_3_POLITICAL SCIENCE.result\n",
      "Means\n",
      "carries\n",
      "0     4.309500\n",
      "1     6.534200\n",
      "2     8.646667\n",
      "3    12.555000\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     5.977044\n",
      "1     9.387149\n",
      "2    13.814826\n",
      "3    25.478768\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "14  [1, 1, 0, 0, 1, 1, 0, 0]  [0, 0, 0, 0]        0         3.166\n",
      "19  [1, 1, 1, 0, 1, 0, 1, 0]  [0, 1, 0, 0]        0         3.478\n",
      "29  [0, 0, 0, 1, 0, 0, 0, 0]  [0, 0, 0, 1]        0         3.728\n",
      "21  [1, 0, 0, 1, 1, 0, 0, 1]  [0, 0, 0, 0]        0         3.838\n",
      "39  [1, 1, 1, 1, 1, 0, 0, 1]  [0, 1, 1, 0]        0         3.900\n",
      "36  [1, 1, 1, 0, 0, 1, 0, 0]  [1, 0, 1, 0]        0         4.243\n",
      "33  [1, 0, 1, 1, 0, 0, 1, 0]  [1, 0, 0, 1]        0         4.666\n",
      "4   [0, 1, 1, 0, 0, 1, 0, 0]  [0, 0, 1, 0]        0         5.151\n",
      "17  [1, 1, 1, 1, 1, 1, 0, 0]  [0, 0, 1, 1]        0         5.338\n",
      "34  [1, 1, 1, 1, 1, 1, 1, 0]  [0, 0, 0, 1]        0         5.587\n",
      "                  data_index        answer  carries  solving_time\n",
      "10  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         4.634\n",
      "24  [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         5.368\n",
      "9   [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         5.369\n",
      "31  [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 0, 0]        1         6.197\n",
      "5   [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1         6.200\n",
      "6   [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1]        1         6.306\n",
      "22  [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1         6.477\n",
      "18  [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         7.009\n",
      "26  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         8.461\n",
      "15  [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1         9.321\n",
      "                  data_index        answer  carries  solving_time\n",
      "30  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         5.744\n",
      "2   [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2         6.806\n",
      "27  [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2         6.869\n",
      "38  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         7.149\n",
      "3   [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2         7.466\n",
      "37  [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         8.605\n",
      "0   [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         9.759\n",
      "1   [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2        12.195\n",
      "23  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2        13.227\n",
      "                  data_index        answer  carries  solving_time\n",
      "32  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         6.119\n",
      "28  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         7.415\n",
      "25  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         7.618\n",
      "11  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3        10.181\n",
      "16  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        14.117\n",
      "7   [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        20.929\n",
      "13  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3        21.506\n",
      "Empty DataFrame\n",
      "Columns: [data_index, answer, carries, solving_time]\n",
      "Index: []\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_37_28.75707_2001_2_2_ENGLISH LANGUAGE EDUCATION.result\n",
      "Means\n",
      "carries\n",
      "0     3.4001\n",
      "1     6.1996\n",
      "2     8.5694\n",
      "3    13.4712\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     5.315459\n",
      "1     9.705478\n",
      "2    17.212014\n",
      "3    33.837057\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "12  [1, 1, 0, 1, 0, 0, 0, 1]  [1, 1, 0, 0]        0         2.619\n",
      "34  [1, 1, 1, 1, 0, 1, 1, 1]  [1, 0, 0, 0]        0         2.619\n",
      "38  [0, 1, 1, 1, 0, 0, 1, 1]  [0, 1, 0, 0]        0         2.728\n",
      "10  [1, 1, 1, 0, 0, 1, 1, 0]  [1, 0, 0, 0]        0         2.932\n",
      "16  [0, 1, 0, 1, 0, 1, 0, 1]  [0, 0, 0, 0]        0         2.963\n",
      "7   [0, 1, 0, 1, 0, 0, 0, 1]  [0, 1, 0, 0]        0         3.011\n",
      "19  [0, 1, 0, 0, 0, 0, 0, 0]  [0, 1, 0, 0]        0         3.244\n",
      "3   [1, 0, 1, 1, 1, 0, 0, 0]  [0, 0, 1, 1]        0         4.105\n",
      "37  [1, 0, 1, 1, 0, 0, 1, 0]  [1, 0, 0, 1]        0         4.162\n",
      "4   [1, 1, 1, 1, 0, 1, 0, 1]  [1, 0, 1, 0]        0         5.618\n",
      "                  data_index        answer  carries  solving_time\n",
      "11  [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         3.791\n",
      "8   [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         4.276\n",
      "39  [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         4.650\n",
      "36  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         5.272\n",
      "21  [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1]        1         5.775\n",
      "23  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         6.462\n",
      "6   [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 1, 0]        1         6.774\n",
      "2   [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1         7.822\n",
      "9   [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1         8.212\n",
      "35  [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1         8.962\n",
      "                  data_index        answer  carries  solving_time\n",
      "30  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         4.978\n",
      "17  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         5.603\n",
      "26  [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2         5.681\n",
      "22  [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2         6.166\n",
      "25  [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2         6.915\n",
      "29  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         7.538\n",
      "14  [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2         8.649\n",
      "5   [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         8.790\n",
      "15  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2        12.008\n",
      "33  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2        19.366\n",
      "                  data_index        answer  carries  solving_time\n",
      "32  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         6.509\n",
      "24  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         6.742\n",
      "28  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         8.229\n",
      "20  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         9.461\n",
      "18  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        10.723\n",
      "1   [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3        11.930\n",
      "31  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        12.554\n",
      "0   [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3        13.149\n",
      "13  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        13.929\n",
      "27  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3        41.486\n",
      "Empty DataFrame\n",
      "Columns: [data_index, answer, carries, solving_time]\n",
      "Index: []\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_27_31.68209_2000_1_4_MEDICINE.result\n",
      "Means\n",
      "carries\n",
      "0    2.8220\n",
      "1    5.1645\n",
      "2    6.3309\n",
      "3    7.7425\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     4.086850\n",
      "1     7.793951\n",
      "2     8.964025\n",
      "3    15.862574\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "28  [1, 1, 1, 1, 1, 1, 1, 1]  [0, 0, 0, 0]        0         2.072\n",
      "29  [1, 0, 0, 0, 0, 0, 0, 0]  [1, 0, 0, 0]        0         2.213\n",
      "27  [0, 1, 0, 0, 0, 1, 0, 0]  [0, 0, 0, 0]        0         2.541\n",
      "32  [1, 1, 0, 0, 0, 0, 0, 0]  [1, 1, 0, 0]        0         2.619\n",
      "21  [1, 1, 0, 1, 1, 0, 0, 0]  [0, 1, 0, 1]        0         2.697\n",
      "39  [1, 1, 1, 1, 0, 0, 1, 1]  [1, 1, 0, 0]        0         2.713\n",
      "18  [1, 1, 1, 0, 1, 0, 0, 0]  [0, 1, 1, 0]        0         2.774\n",
      "34  [0, 0, 0, 1, 0, 0, 0, 0]  [0, 0, 0, 1]        0         2.822\n",
      "6   [1, 1, 0, 1, 0, 1, 0, 1]  [1, 0, 0, 0]        0         3.525\n",
      "19  [0, 1, 1, 0, 0, 0, 1, 0]  [0, 1, 0, 0]        0         4.244\n",
      "                  data_index        answer  carries  solving_time\n",
      "8   [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         3.650\n",
      "24  [1, 1, 0, 1, 1, 0, 1, 1]  [0, 0, 1, 0]        1         3.915\n",
      "38  [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 0]        1         4.368\n",
      "12  [1, 0, 1, 0, 0, 1, 1, 0]  [0, 1, 0, 0]        1         4.447\n",
      "17  [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         4.509\n",
      "30  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         5.150\n",
      "9   [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1         5.165\n",
      "5   [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         5.783\n",
      "13  [1, 0, 1, 0, 1, 0, 0, 1]  [0, 0, 0, 1]        1         6.899\n",
      "3   [1, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0]        1         7.759\n",
      "                  data_index        answer  carries  solving_time\n",
      "15  [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         4.697\n",
      "16  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         4.854\n",
      "35  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         5.541\n",
      "22  [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2         5.587\n",
      "1   [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         5.806\n",
      "7   [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         6.088\n",
      "10  [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2         6.916\n",
      "0   [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         7.353\n",
      "33  [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2         7.681\n",
      "11  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         8.786\n",
      "                  data_index        answer  carries  solving_time\n",
      "26  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         3.431\n",
      "37  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         3.728\n",
      "36  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         4.509\n",
      "14  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         4.775\n",
      "2   [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         5.991\n",
      "25  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         8.524\n",
      "31  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         8.663\n",
      "20  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         9.352\n",
      "4   [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        12.961\n",
      "23  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3        15.491\n",
      "Empty DataFrame\n",
      "Columns: [data_index, answer, carries, solving_time]\n",
      "Index: []\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_07_03.71068_1998_2_3_HUMANITIES.result\n",
      "Means\n",
      "carries\n",
      "0    3.228100\n",
      "1    4.013667\n",
      "2    4.959500\n",
      "3    7.594143\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     4.320566\n",
      "1     5.423678\n",
      "2     7.259454\n",
      "3    13.210697\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "22  [1, 1, 1, 1, 0, 0, 0, 0]  [1, 1, 1, 1]        0         2.447\n",
      "2   [1, 1, 1, 1, 1, 0, 0, 0]  [0, 1, 1, 1]        0         2.479\n",
      "17  [1, 0, 0, 0, 0, 0, 0, 0]  [1, 0, 0, 0]        0         2.666\n",
      "6   [1, 1, 1, 1, 1, 1, 1, 1]  [0, 0, 0, 0]        0         2.995\n",
      "18  [1, 1, 1, 1, 1, 1, 1, 0]  [0, 0, 0, 1]        0         3.336\n",
      "10  [0, 0, 1, 0, 0, 0, 1, 0]  [0, 0, 0, 0]        0         3.416\n",
      "16  [1, 0, 1, 0, 1, 0, 0, 0]  [0, 0, 1, 0]        0         3.602\n",
      "3   [0, 1, 1, 0, 0, 1, 0, 0]  [0, 0, 1, 0]        0         3.635\n",
      "11  [0, 1, 1, 1, 0, 1, 1, 0]  [0, 0, 0, 1]        0         3.776\n",
      "37  [1, 1, 1, 1, 1, 0, 1, 0]  [0, 1, 0, 1]        0         3.929\n",
      "                  data_index        answer  carries  solving_time\n",
      "15  [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         3.305\n",
      "31  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         3.306\n",
      "34  [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         3.447\n",
      "25  [0, 1, 1, 0, 0, 1, 0, 1]  [0, 0, 0, 1]        1         3.619\n",
      "24  [1, 0, 1, 1, 0, 1, 1, 0]  [0, 1, 0, 1]        1         3.873\n",
      "1   [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         4.041\n",
      "7   [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1         4.451\n",
      "26  [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1]        1         4.744\n",
      "27  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         5.337\n",
      "                  data_index        answer  carries  solving_time\n",
      "23  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2         3.603\n",
      "38  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         3.697\n",
      "12  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         3.978\n",
      "19  [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2         4.587\n",
      "39  [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         4.715\n",
      "30  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         4.806\n",
      "0   [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2         5.134\n",
      "13  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2         5.400\n",
      "5   [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2         6.791\n",
      "29  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         6.884\n",
      "                  data_index        answer  carries  solving_time\n",
      "32  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         5.103\n",
      "35  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         5.325\n",
      "14  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.650\n",
      "8   [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         5.666\n",
      "36  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         9.305\n",
      "33  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        10.165\n",
      "21  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        11.945\n",
      "Empty DataFrame\n",
      "Columns: [data_index, answer, carries, solving_time]\n",
      "Index: []\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_12_47.38854_2000_1_3_ECONOMICS.result\n",
      "Means\n",
      "carries\n",
      "0    4.439300\n",
      "1    5.000200\n",
      "2    6.570800\n",
      "3    8.244714\n",
      "Name: solving_time, dtype: float64\n",
      "STDs\n",
      "carries\n",
      "0     6.650909\n",
      "1     8.726309\n",
      "2     9.164288\n",
      "3    11.605780\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "9   [1, 0, 0, 1, 0, 0, 0, 1]  [1, 0, 0, 0]        0         3.213\n",
      "29  [1, 1, 0, 1, 1, 1, 0, 1]  [0, 0, 0, 0]        0         3.292\n",
      "22  [1, 1, 1, 1, 0, 0, 1, 0]  [1, 1, 0, 1]        0         3.540\n",
      "16  [1, 0, 1, 1, 0, 0, 1, 1]  [1, 0, 0, 0]        0         4.041\n",
      "1   [1, 1, 0, 1, 1, 1, 0, 0]  [0, 0, 0, 1]        0         4.166\n",
      "32  [0, 1, 1, 1, 0, 0, 1, 0]  [0, 1, 0, 1]        0         4.197\n",
      "14  [1, 0, 1, 1, 1, 0, 1, 0]  [0, 0, 0, 1]        0         4.619\n",
      "23  [1, 1, 1, 0, 1, 0, 1, 0]  [0, 1, 0, 0]        0         4.869\n",
      "20  [0, 1, 0, 0, 0, 1, 0, 0]  [0, 0, 0, 0]        0         5.744\n",
      "13  [1, 0, 1, 0, 0, 0, 0, 0]  [1, 0, 1, 0]        0         6.712\n",
      "                  data_index        answer  carries  solving_time\n",
      "8   [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         3.401\n",
      "28  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         3.462\n",
      "18  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         3.837\n",
      "34  [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         3.853\n",
      "12  [1, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0]        1         4.326\n",
      "33  [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         4.635\n",
      "21  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         4.962\n",
      "17  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         5.556\n",
      "39  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         6.415\n",
      "11  [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1         9.555\n",
      "                  data_index        answer  carries  solving_time\n",
      "4   [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         4.946\n",
      "26  [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2         5.040\n",
      "3   [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 1]        2         5.724\n",
      "36  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         5.930\n",
      "0   [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         6.118\n",
      "38  [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         6.649\n",
      "10  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         7.212\n",
      "15  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         7.337\n",
      "35  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         7.571\n",
      "7   [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         9.181\n",
      "                  data_index        answer  carries  solving_time\n",
      "5   [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         6.072\n",
      "27  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         6.759\n",
      "31  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         7.305\n",
      "2   [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         8.272\n",
      "24  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         9.039\n",
      "37  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         9.305\n",
      "25  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        10.961\n",
      "Empty DataFrame\n",
      "Columns: [data_index, answer, carries, solving_time]\n",
      "Index: []\n"
     ]
    }
   ],
   "source": [
    "operator = 'subtract'\n",
    "df_results = list()\n",
    "result_files = get_all_result_files()\n",
    "cols = ['data_index', 'answer', 'carries', 'solving_time']\n",
    "for f in result_files:\n",
    "    if get_operator(f) == operator:\n",
    "\n",
    "        df_result = read_result_file(f)\n",
    "        df_result = filter_for_mean_solving_time(df_result, rm_carry_outlier=False, outlier_std=2)\n",
    "        df_result = df_result[df_result['correct'] == True]\n",
    "        #df_result = df_result[df_result['solving_time'] < 30]\n",
    "        df_result = df_result[cols]\n",
    "        df_results.append(df_result)\n",
    "        \n",
    "        st_means = df_result.groupby(['carries'])['solving_time'].mean()\n",
    "        st_stds = df_result.groupby(['carries'])['solving_time'].std()\n",
    "        print_all = True\n",
    "        if print_all:\n",
    "            df_result.boxplot(column=['solving_time'], by='carries')\n",
    "            plt.show()\n",
    "            print(f)\n",
    "            print('Means')\n",
    "            print(st_means)\n",
    "            print('STDs')\n",
    "            print(st_means + 2 * st_stds)\n",
    "            print(df_result[df_result['carries'] == 0].sort_values(by=['solving_time']))\n",
    "            print(df_result[df_result['carries'] == 1].sort_values(by=['solving_time']))\n",
    "            print(df_result[df_result['carries'] == 2].sort_values(by=['solving_time']))\n",
    "            print(df_result[df_result['carries'] == 3].sort_values(by=['solving_time']))\n",
    "            print(df_result[df_result['carries'] == 4].sort_values(by=['solving_time']))\n",
    "        if st_means[2] > st_means[3] and (not print_all):\n",
    "            print(f)\n",
    "            print(st_means)\n",
    "            print(st_means + 2 * st_stds)\n",
    "            print(df_result[df_result['carries'] == 2].sort_values(by=['solving_time']))\n",
    "            print(df_result[df_result['carries'] == 3].sort_values(by=['solving_time']))\n",
    "            pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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WMzOrU2WJIyJeWtWxzcxs9HzmuJmZFeLEYWZmhThxmJlZIU4cZmZWiBOHmZkV4sRhZmaF+A6AZmYFSaq/7Bn1lavq8k+j4R6HmVlBEVHXo7u7u+6yrcSJw8zMCnHiMDOzQpw4zMysECcOMzMrxInDzMwKceIwM7NCnDjMzKwQJw4zMyvEicPMzApx4jAzs0IqSxyS/lPSDZKWS1okaYuqYjEzs/pVkjgk7Qr8B9AZETOACcCbq4jFzMyKqXKoaiKwpaSJwFbA3RXGYmZmdaokcUTEXcBngduBe4A1EbGkiljMzKwYVXE5X0nbARcDbwJWA98BLoqIbw0oNxeYC9DR0XHg4sWLxzvUUenr62PKlClVh9F23K6N47ZtjFZq11mzZi2LiM56ylZ1I6eXA7dGxP0Aki4BXgI8JXFExNnA2QCdnZ3R1dU1zmGOTk9PD60SaytxuzaO27Yx2rVdq5rjuB04RNJWSrfSOhxYUVEsZmZWQFVzHFcDFwHXAL/PcZxdRSxmZlZMZfccj4hTgFOqOr6ZmY2Ozxw3M7NCnDjMzKwQJw4zMyvEicPMzApx4jAzs0KcOMzMrBAnDjMzK6TuxKHkrZI+kbefLenFjQvNzMyaUZEex1eAQ4Fj8/Za4MulR2RmZk2tyJnjB0fEAZKuBYiIVZI2a1BcZmbWpIr0ODZImgAEgKSdgL81JCozM2taRRLHmcB3gWdKmg8sBf6rIVGZmVnTqnuoKiK+LWkZ6RLoAl4TEb4UupnZJqbo1XHvBX7Ok/cLPyAirik/LDMza1Z1Jw5JnwRmAzeT5znyv4eVH5aZmTWrIj2ONwJ7RsRjjQrGzMyaX5HJ8eXAto0KxMzMWkORHsengWslLQce7d8ZEf9UelRmZta0iiSOhcAZpHuEj+n8DUl7AxfU7Hou8ImI+PxY6jUzs8YrkjgeiYgzyzhoRPwB2A8gn1R4F+kcETMza3JFEsfPJX0auJSnDlWNdTnu4cDNEbFyjPWYmdk4KJI49s//HlKzr4zluG8GFo2xDjMzGyeKiJFLNerg6SKJdwMvjIh7B3l9LjAXoKOj48DFixePc4Sj09fXx5QpU6oOo+24XRvHbdsYrdSus2bNWhYRnfWUHTFxSHprRHxL0vsHez0iPjeKGPvrPgZ4T0QcMVLZzs7O6O3tHe2hxlVPTw9dXV1Vh9F23K6N47ZtjFZqV0l1J456hqom53+nDvLaWLsrx+JhKjOzljJi4oiIs/LTn0TEL2pfk/T3oz2wpMnAK4B3jLYOMzMbf0XOHP9infvqEhHrImKHiFgz2jrMzGz8jdjjkHQo8BJgpwHzHFsDExoVmJmZNad65jg2A6bksrXzHA8Dr29EUGZm1rzqmeO4ErhS0rnDnaQn6YsRcUKp0ZmZWdOpe46jjjO7Rz1RbmZmraPI5LiZmZkTh5mZFVNm4lCJdZmZWZMqM3F8ocS6zMysSdV9dVxJP+DplxhZA/QCZ0XEuSXGZWZmTapIj+MWoA84Jz8eBtYCz8/bZma2CShyP46XRMRBNds/kPTbiDhI0g1lB2ZmZs2pSI9jiqRn92/k5/0Xmn+s1KjMzKxpFelxfABYKulm0gqq5wDvzle5XdiI4MzMrPnUnTgi4oeS9gL+Lu/6Q0T8NT//fOmRmZlZUyrS4wA4EJiW37evJCLivNKjMjOzplVkOe43gT2B64CNeXcAThxmZpuQIj2OTuAFMdJNys3MrK0VWVW1HHhWowIxM7PWUKTHsSNwo6TfAI/274yIfyo9KjMza1pFEsepZR5Y0rbA14AZpLmSf4+IX5V5DDMzK1+R5bhXlnzsLwBXRMTrJW0GbFVy/WZta9/TlrBm/YYRy6084+hSj7vHSZeNWGabLSdx/SlHlHpcay4jJg5JSyNipqS1PPUihwIiIrYuelBJ2wAvA2aTKnkMn31uVrc16zdw2+lHjVzw9PrWsvT09NDV1TW2oLJp8y4vpR5rXvXcc3xm/ndqicd9DnA/8A1J+wLLgBMjYl1tIUlzgbkAHR0d9PT0lBhC4/T19bVMrK3E7fpUZbZF2W3r/6ekbX9mI6KuB3AmcGi95UeoqxN4HDg4b38B+ORw7znwwAOjVXR3d1cdQltyuz5pj5MuK7W+Mtu27NhaWSv9zAK9Ued3eJHluMuAj0u6WdJnJXWOIV/dCdwZEVfn7YuAA8ZQn5mZjZO6E0dELIyIVwMHAX8AzpD0p9EcNCL+Atwhae+863DgxtHUZWZm46votaoAnke60OEewIoxHPsE4Nt5RdUtwL+NoS4zMxsnRa5V9RngtcDNwAWkOYnVoz1wRFxHmuswM7MWUqTHcTNpcvyBRgVjZvWZOn0e+yycV26lJd1VZ+p0gDqWClvLquc8jv5J698Cz669CyBARFzTiMDMbGhrV5xe33kcdfJ5HFZEPT2O/x7mtQAOKykWMzNrAfWcADhrPAIxM7PWUGRyfBLwLtKlQgB6gLMiYuQL5piZWdsoMjn+VWAS8JW8fVze97aygzIzs+ZVJHEcFBH71mz/TNL1ZQdkZmbNrcglRzZK2rN/Q9JzefLe42Zmtoko0uP4INAt6Za8PQ2f7W1mtskpkjh2IN2tbxrwGuBQYE0DYjIzsyZWZKjq4xHxMLA1MAv4Emly3MzMNiGF5jjyv0cB50TE5cBm5YdkZmbNrEjiuEvSWcCbgB9K2rzg+83MrA0U+eJ/I/Aj4JX5qrjbAx9qSFRmZta06p4cj4hHgEtqtu8B7mlEUGZm1rw81GRmZoU4cZiZWSFOHGZmVsho7jleCkm3AWtJy3wfjwjfRtasgNJvmHRFOfVts+WkUuqx5lVZ4shm+Va0ZsWVefc/SEmo7DqtfXmoyszMCqkycQSwRNIySXMrjMPMzAqocqhqZkTcJemZwI8l3RQRV9UWyAllLkBHRwc9PT0VhFlcX19fy8TaStyujeW2LV+7/swqIqqOAUmnAn0R8dmhynR2dkZvb+/4BTUGPT09dHV1VR1G23G7No7nOBqjlX5mJS2rd5FSJUNVkiZLmtr/HDgCWF5FLGZmVkxVQ1UdwHcl9cdwfkRcUVEs1gTyz0JpmqEnbdauKkkcEXELsO+IBW2TUc8XvYdTzJqDl+OamVkhThxmZlaIE4eZmRXixGFmZoVUfa0qM2ugIqvVdMbIZbxazcA9DrO2FhF1Pbq7u+sqZwZOHGZmVpATh5mZFeLEYWZmhThxmJlZIU4cZmZWiBOHmZkV4sRhZmaF+ARAa6h9T1vCmvUbSqtv2rzLS6trmy0ncf0pR5RWn9mmwonDGmrN+g2lXQq97LuplZmEzDYlHqoyM7NCnDjMzKwQJw4zMyuk0sQhaYKkayVdVmUcZmZWv6p7HCcCKyqOwczMCqgscUjaDTgK+FpVMZiZWXFVLsf9PPBhYGqFMRRS5KY49fI9Dsys1VSSOCQdDdwXEcskdQ1Tbi4wF6Cjo4Oenp7xCXAI3d3ddZWbfcU6zj1ycl1lq/5M46Gsz9jX11d6e20K7V+PRrSttW+7qoq/eCV9GjgOeBzYAtgauCQi3jrUezo7O6O3t3ecIhybafMuL+2kt1a3z8J9qg5hWL8//vdVh9AUyj650pJWaldJyyKis56ylfQ4IuIjwEcAco/jg8MlDWtda1ec7jPHzdpM1auqzMysxVR+raqI6AF6Kg7DzMzq5B6HmZkV4sRhZmaFOHGYmVkhlc9xWPsrdfXSFeXeyMnMinPisIYq83wWnx9j1hw8VGVmZoU4cZiZWSEeqgL2PW0Ja9ZvKLXOssb1t9lyEtefckQpdZmZlcGJA1izfkOpY+dlXhrDl8Uws2bjoSozMyvEicPMzApx4jAzs0I8xwFMnT6PfRbOK7fSheVUM3U6pDvsmpk1BycOyr1nBHhy3Mzam4eqzMysECcOMzMrxENVWelDQiVdjM8X4jOzZuPEQbkX4gNfjM/M2puHqszMrJBKehyStgCuAjbPMVwUEadUEYs1B0n1lTujvvoiYgzRmNlwqupxPAocFhH7AvsBR0o6pKJYrAlExIiP7u7uuso5aZg1ViU9jki/2X15c1J++LfdzKwFVDY5LmkCsAx4HvDliLh6kDJzgbkAHR0d9PT0jGuMY9FKsbaKvr4+t2uDuG0bo13bVVV36yVtC3wXOCEilg9VrrOzM3p7e8cvsDHwqqrGKPOMfHsqt21jtFK7SloWEZ31lK18VVVErAa6gSOrjsXMzEZW1aqqnYANEbFa0pbAK4A618tUp96VP+DVP2bWvqrqcewMdEv6HfBb4McRcVlFsdSt3hU9Xv1jZu2sqlVVvwP2r+LYZmY2NpXPcZiZWWtx4jAzs0KcOMzMrBAnDjMzK8SJw8zMCnHiMDOzQpw4zMyskMqvVVUvSfcDK6uOo047Ag9UHUQbcrs2jtu2MVqpXfeIiJ3qKdgyiaOVSOqt92JhVj+3a+O4bRujXdvVQ1VmZlaIE4eZmRXixNEYZ1cdQJtyuzaO27Yx2rJdPcdhZmaFuMdhZmaFOHGUSNKRkv4g6c+S5lUdT7uQ9HVJ90ka8tbCVpyk3SV1S7pR0g2STqw6pnYhaQtJv5F0fW7b06qOqUweqiqJpAnAH0l3M7yTdIOqYyPixkoDawOSXgb0AedFxIyq42kXknYGdo6IayRNBZYBr/HP7Ngp3S50ckT0SZoELAVOjIhfVxxaKdzjKM+LgT9HxC0R8RiwGDim4pjaQkRcBTxUdRztJiLuiYhr8vO1wApg12qjag+R9OXNSfnRNn+lO3GUZ1fgjprtO/EvobUISdNId+W8utpI2oekCZKuA+4j3R67bdrWicNsEydpCnAx8L6IeLjqeNpFRGyMiP2A3YAXS2qbYVYnjvLcBexes71b3mfWtPL4+8XAtyPikqrjaUcRsRroBo6sOpayOHGU57fAXpKeI2kz4M3ApRXHZDakPIG7AFgREZ+rOp52ImknSdvm51uSFs3cVG1U5XHiKElEPA68F/gRaZLxwoi4odqo2oOkRcCvgL0l3SlpTtUxtYm/B44DDpN0XX68uuqg2sTOQLek35H+qPxxRFxWcUyl8XJcMzMrxD0OMzMrxInDzMwKceIwM7NCnDjMzKwQJw4zMyvEicOswSTtIumiquMwK4uX45qVSNLEfE7PoNtm7cCJw2wIkv4V+CDpqqa/Ay4EPgZsBjwIvCUi7pV0KrAn8FzgdtJJoK8DpgATgOOByyJiRr78/ulAF7A58OWIOCtf4vwCYGtgIvCuiPj5OH1Us0ImVh2AWTOS9EJSknhJRDwgaXtSAjkkIkLS24APAx/Ib3kBMDMi1kuaDRwAvCgiHspXnu03B1gTEQdJ2hz4haQlpETzo4iYn5PLVuPwMc1GxYnDbHCHAd+JiAcAcgLYB7gg9w42A26tKX9pRKyv2f5xRAx2D5EjgBdJen3e3gbYi3RZiq/niw5+LyKuK/nzmJXGk+Nm9fsi8KWI2Ad4B7BFzWvrBpQduN1PwAkRsV9+PCciluSbVb2MdEXlc/MwmVlTcuIwG9zPgDdI2gEgD1Vtw5OXyj9+lPX+CHhX7lkg6fmSJkvaA7g3Is4BvkYa6jJrSh6qMhtERNwgaT5wpaSNwLXAqcB3JK0iJZbnjKLqrwHTgGvyZc3vB15Dmiz/kKQNpPuru8dhTcurqszMrBAPVZmZWSFOHGZmVogTh5mZFeLEYWZmhThxmJlZIU4cZmZWiBOHmZkV4sRhZmaF/H9p8vNNKgWIVwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_20_04.37773_1997_2_2_KOREAN EDUCATION.result\n",
      "carries\n",
      "0    3.440500\n",
      "1    4.010900\n",
      "2    6.157800\n",
      "3    9.367333\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     4.139259\n",
      "1     5.020969\n",
      "2     9.688352\n",
      "3    10.907274\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "34  [0, 1, 0, 0, 0, 1, 0, 0]  [0, 0, 0, 0]        0         2.900\n",
      "37  [1, 1, 0, 1, 1, 0, 0, 1]  [0, 1, 0, 0]        0         3.120\n",
      "22  [1, 0, 1, 1, 0, 0, 1, 1]  [1, 0, 0, 0]        0         3.213\n",
      "6   [1, 1, 1, 1, 1, 0, 1, 0]  [0, 1, 0, 1]        0         3.322\n",
      "16  [1, 0, 1, 1, 1, 0, 0, 1]  [0, 0, 1, 0]        0         3.338\n",
      "29  [1, 1, 1, 1, 0, 0, 1, 1]  [1, 1, 0, 0]        0         3.416\n",
      "21  [0, 1, 0, 0, 0, 0, 0, 0]  [0, 1, 0, 0]        0         3.541\n",
      "10  [0, 0, 1, 1, 0, 0, 1, 0]  [0, 0, 0, 1]        0         3.585\n",
      "19  [0, 1, 1, 1, 0, 0, 0, 1]  [0, 1, 1, 0]        0         3.947\n",
      "23  [1, 1, 0, 1, 0, 0, 0, 1]  [1, 1, 0, 0]        0         4.023\n",
      "                  data_index        answer  carries  solving_time\n",
      "7   [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 0, 0]        1         3.104\n",
      "30  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         3.650\n",
      "11  [1, 1, 0, 1, 1, 0, 1, 1]  [0, 0, 1, 0]        1         3.697\n",
      "9   [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         3.793\n",
      "20  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         3.867\n",
      "28  [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 0]        1         4.087\n",
      "25  [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1         4.134\n",
      "31  [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         4.367\n",
      "32  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         4.525\n",
      "4   [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         4.885\n",
      "                  data_index        answer  carries  solving_time\n",
      "8   [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         4.650\n",
      "38  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         5.115\n",
      "26  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         5.774\n",
      "27  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         6.100\n",
      "13  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2         9.150\n",
      "                  data_index        answer  carries  solving_time\n",
      "1   [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         8.554\n",
      "39  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         9.463\n",
      "36  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3        10.085\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_02_30.60523_1994_1_3_ARCHITECTURAL ENGINEERING.result\n",
      "carries\n",
      "0    3.048900\n",
      "1    4.156500\n",
      "2    6.437333\n",
      "3    6.132400\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     4.416138\n",
      "1     5.805001\n",
      "2    11.242603\n",
      "3     9.763031\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "35  [0, 0, 0, 0, 0, 0, 0, 0]  [0, 0, 0, 0]        0         2.306\n",
      "8   [0, 0, 1, 1, 0, 0, 1, 1]  [0, 0, 0, 0]        0         2.354\n",
      "21  [1, 1, 0, 1, 0, 0, 0, 0]  [1, 1, 0, 1]        0         2.556\n",
      "23  [0, 0, 0, 1, 0, 0, 0, 0]  [0, 0, 0, 1]        0         2.573\n",
      "3   [1, 1, 1, 0, 1, 1, 1, 0]  [0, 0, 0, 0]        0         2.776\n",
      "36  [0, 1, 1, 1, 0, 1, 1, 0]  [0, 0, 0, 1]        0         2.994\n",
      "30  [0, 1, 1, 0, 0, 1, 0, 0]  [0, 0, 1, 0]        0         3.041\n",
      "29  [1, 0, 0, 1, 0, 0, 0, 1]  [1, 0, 0, 0]        0         3.713\n",
      "6   [1, 1, 0, 1, 1, 0, 0, 0]  [0, 1, 0, 1]        0         3.979\n",
      "20  [1, 0, 1, 1, 1, 0, 1, 0]  [0, 0, 0, 1]        0         4.197\n",
      "                  data_index        answer  carries  solving_time\n",
      "5   [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         2.885\n",
      "0   [1, 0, 1, 0, 0, 1, 1, 0]  [0, 1, 0, 0]        1         3.557\n",
      "37  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         3.634\n",
      "4   [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1         3.666\n",
      "27  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         4.087\n",
      "2   [0, 1, 0, 1, 0, 0, 1, 0]  [0, 0, 1, 1]        1         4.181\n",
      "26  [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1]        1         4.416\n",
      "25  [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 0, 0]        1         4.603\n",
      "32  [0, 1, 1, 0, 0, 1, 0, 1]  [0, 0, 0, 1]        1         4.604\n",
      "22  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         5.932\n",
      "                  data_index        answer  carries  solving_time\n",
      "39  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2         3.447\n",
      "28  [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         4.524\n",
      "33  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         4.848\n",
      "31  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         4.869\n",
      "17  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         6.153\n",
      "18  [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2         6.290\n",
      "34  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         7.571\n",
      "19  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         9.867\n",
      "10  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2        10.367\n",
      "                  data_index        answer  carries  solving_time\n",
      "9   [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         3.102\n",
      "24  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         3.571\n",
      "16  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.416\n",
      "11  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         5.572\n",
      "1   [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         6.072\n",
      "12  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         6.587\n",
      "7   [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         6.634\n",
      "13  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         7.431\n",
      "15  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         8.384\n",
      "38  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         8.555\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_15_06_33.60021_1997_1_4_CHEMICAL AND BIOLOGICAL ENGINEERING.result\n",
      "carries\n",
      "0    2.693400\n",
      "1    3.215111\n",
      "2    4.597125\n",
      "3    4.958000\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0    3.190376\n",
      "1    4.289180\n",
      "2    6.356149\n",
      "3    9.364648\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "17  [1, 1, 0, 1, 0, 1, 0, 1]  [1, 0, 0, 0]        0         2.386\n",
      "27  [1, 1, 1, 1, 0, 0, 1, 1]  [1, 1, 0, 0]        0         2.416\n",
      "7   [1, 0, 1, 0, 0, 0, 0, 0]  [1, 0, 1, 0]        0         2.431\n",
      "22  [1, 1, 1, 1, 1, 1, 1, 1]  [0, 0, 0, 0]        0         2.572\n",
      "23  [1, 1, 0, 1, 0, 0, 0, 1]  [1, 1, 0, 0]        0         2.665\n",
      "25  [0, 1, 1, 1, 0, 1, 1, 0]  [0, 0, 0, 1]        0         2.695\n",
      "35  [1, 0, 1, 1, 0, 0, 0, 0]  [1, 0, 1, 1]        0         2.806\n",
      "29  [1, 1, 1, 0, 0, 0, 0, 0]  [1, 1, 1, 0]        0         2.854\n",
      "37  [1, 0, 1, 1, 1, 0, 1, 1]  [0, 0, 0, 0]        0         3.037\n",
      "39  [0, 1, 1, 1, 0, 0, 0, 0]  [0, 1, 1, 1]        0         3.072\n",
      "                  data_index        answer  carries  solving_time\n",
      "6   [1, 0, 1, 0, 0, 1, 1, 0]  [0, 1, 0, 0]        1         2.526\n",
      "16  [0, 1, 0, 0, 0, 0, 1, 0]  [0, 0, 1, 0]        1         2.635\n",
      "4   [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         2.822\n",
      "21  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         2.846\n",
      "2   [1, 1, 1, 0, 1, 1, 0, 1]  [0, 0, 0, 1]        1         3.366\n",
      "5   [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         3.432\n",
      "33  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         3.475\n",
      "20  [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         3.714\n",
      "0   [1, 0, 1, 0, 1, 0, 0, 1]  [0, 0, 0, 1]        1         4.120\n",
      "                  data_index        answer  carries  solving_time\n",
      "12  [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 1]        2         3.525\n",
      "31  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         3.603\n",
      "11  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         3.775\n",
      "24  [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2         4.541\n",
      "30  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         4.776\n",
      "10  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         5.416\n",
      "19  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         5.554\n",
      "32  [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         5.587\n",
      "                  data_index        answer  carries  solving_time\n",
      "8   [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         3.041\n",
      "14  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         3.072\n",
      "1   [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         3.995\n",
      "36  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         4.071\n",
      "15  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         4.115\n",
      "26  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         4.538\n",
      "34  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         4.836\n",
      "13  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         7.024\n",
      "3   [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         9.930\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-01_14_13_41.56001_1996_1_2_BUSINESS.result\n",
      "carries\n",
      "0     3.16450\n",
      "1     4.05360\n",
      "2    10.45880\n",
      "3     9.42325\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     3.843760\n",
      "1     5.624157\n",
      "2    20.202898\n",
      "3    26.410415\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "34  [0, 1, 1, 1, 0, 0, 1, 1]  [0, 1, 0, 0]        0         2.556\n",
      "8   [0, 1, 0, 0, 0, 1, 0, 0]  [0, 0, 0, 0]        0         2.775\n",
      "29  [0, 1, 0, 1, 0, 0, 0, 1]  [0, 1, 0, 0]        0         2.978\n",
      "27  [1, 0, 1, 0, 0, 0, 0, 0]  [1, 0, 1, 0]        0         3.041\n",
      "23  [0, 1, 1, 1, 0, 0, 0, 1]  [0, 1, 1, 0]        0         3.119\n",
      "19  [1, 1, 1, 1, 0, 1, 0, 0]  [1, 0, 1, 1]        0         3.197\n",
      "2   [1, 1, 1, 1, 1, 0, 1, 1]  [0, 1, 0, 0]        0         3.385\n",
      "4   [1, 1, 1, 0, 1, 1, 0, 0]  [0, 0, 1, 0]        0         3.447\n",
      "9   [0, 1, 1, 0, 0, 1, 0, 0]  [0, 0, 1, 0]        0         3.572\n",
      "7   [1, 1, 1, 1, 1, 0, 1, 0]  [0, 1, 0, 1]        0         3.575\n",
      "                  data_index        answer  carries  solving_time\n",
      "10  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         2.635\n",
      "14  [1, 1, 0, 0, 1, 0, 1, 0]  [0, 0, 1, 0]        1         3.275\n",
      "18  [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         3.421\n",
      "11  [0, 1, 0, 1, 0, 0, 1, 0]  [0, 0, 1, 1]        1         3.868\n",
      "17  [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1         3.978\n",
      "22  [1, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0]        1         4.099\n",
      "25  [0, 1, 0, 0, 0, 0, 1, 0]  [0, 0, 1, 0]        1         4.555\n",
      "36  [1, 0, 1, 1, 0, 1, 1, 0]  [0, 1, 0, 1]        1         4.724\n",
      "13  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         4.863\n",
      "15  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         5.118\n",
      "                  data_index        answer  carries  solving_time\n",
      "6   [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         6.102\n",
      "5   [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         7.509\n",
      "21  [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2         7.520\n",
      "31  [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         8.372\n",
      "16  [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2         8.618\n",
      "35  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         8.929\n",
      "24  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         9.880\n",
      "20  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2        11.785\n",
      "0   [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2        12.774\n",
      "28  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2        23.099\n",
      "                  data_index        answer  carries  solving_time\n",
      "39  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         2.400\n",
      "32  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         4.759\n",
      "12  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         5.931\n",
      "30  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         6.661\n",
      "33  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         6.771\n",
      "1   [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         9.087\n",
      "38  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3        10.196\n",
      "37  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3        29.581\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-01_16_06_25.31283_1996_1_3_AEROSPACE ENGINEERING.result\n",
      "carries\n",
      "0    3.381400\n",
      "1    4.086300\n",
      "2    4.383444\n",
      "3    5.706875\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0    4.994790\n",
      "1    5.395679\n",
      "2    6.840138\n",
      "3    8.310461\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "7   [1, 1, 1, 1, 1, 1, 1, 1]  [0, 0, 0, 0]        0         2.245\n",
      "3   [1, 0, 1, 1, 1, 0, 1, 1]  [0, 0, 0, 0]        0         2.323\n",
      "2   [0, 0, 1, 0, 0, 0, 1, 0]  [0, 0, 0, 0]        0         2.764\n",
      "38  [1, 1, 0, 1, 0, 0, 0, 0]  [1, 1, 0, 1]        0         3.022\n",
      "30  [0, 0, 1, 1, 0, 0, 1, 1]  [0, 0, 0, 0]        0         3.204\n",
      "36  [1, 0, 0, 1, 0, 0, 0, 1]  [1, 0, 0, 0]        0         3.544\n",
      "37  [1, 0, 1, 1, 0, 0, 1, 0]  [1, 0, 0, 1]        0         3.788\n",
      "10  [0, 1, 0, 1, 0, 1, 0, 0]  [0, 0, 0, 1]        0         4.076\n",
      "13  [1, 1, 1, 1, 1, 0, 1, 1]  [0, 1, 0, 0]        0         4.258\n",
      "24  [0, 1, 1, 1, 0, 0, 0, 0]  [0, 1, 1, 1]        0         4.590\n",
      "                  data_index        answer  carries  solving_time\n",
      "1   [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         3.368\n",
      "18  [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1         3.414\n",
      "26  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         3.605\n",
      "25  [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 0]        1         3.821\n",
      "8   [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1         3.867\n",
      "0   [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1         3.948\n",
      "34  [1, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0]        1         4.335\n",
      "5   [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         4.400\n",
      "22  [0, 1, 0, 0, 0, 0, 1, 0]  [0, 0, 1, 0]        1         4.556\n",
      "33  [1, 0, 1, 0, 1, 0, 0, 1]  [0, 0, 0, 1]        1         5.549\n",
      "                  data_index        answer  carries  solving_time\n",
      "11  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         3.008\n",
      "14  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2         3.228\n",
      "15  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         3.368\n",
      "4   [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         4.008\n",
      "27  [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2         4.052\n",
      "29  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         4.449\n",
      "12  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         4.805\n",
      "21  [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2         5.887\n",
      "31  [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         6.646\n",
      "                  data_index        answer  carries  solving_time\n",
      "28  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         4.069\n",
      "9   [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         4.432\n",
      "16  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         4.587\n",
      "39  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         5.897\n",
      "32  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         6.145\n",
      "6   [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         6.213\n",
      "17  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         6.257\n",
      "20  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         8.055\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-01_13_23_19.14383_1997_2_2_CERAMIC ART.result\n",
      "carries\n",
      "0     4.538800\n",
      "1     7.046778\n",
      "2    11.017333\n",
      "3    13.294250\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     6.954059\n",
      "1    11.538391\n",
      "2    24.085167\n",
      "3    24.824373\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "7   [0, 0, 1, 0, 0, 0, 1, 0]  [0, 0, 0, 0]        0         2.998\n",
      "2   [0, 0, 0, 1, 0, 0, 0, 1]  [0, 0, 0, 0]        0         3.244\n",
      "9   [0, 1, 1, 0, 0, 0, 0, 0]  [0, 1, 1, 0]        0         3.382\n",
      "28  [0, 0, 1, 1, 0, 0, 1, 0]  [0, 0, 0, 1]        0         3.807\n",
      "6   [0, 1, 1, 1, 0, 0, 1, 1]  [0, 1, 0, 0]        0         4.350\n",
      "34  [1, 1, 0, 1, 0, 0, 0, 0]  [1, 1, 0, 1]        0         4.837\n",
      "33  [0, 1, 0, 1, 0, 1, 0, 0]  [0, 0, 0, 1]        0         4.884\n",
      "36  [1, 1, 0, 1, 1, 0, 0, 1]  [0, 1, 0, 0]        0         5.541\n",
      "20  [1, 1, 0, 0, 1, 0, 0, 0]  [0, 1, 0, 0]        0         5.618\n",
      "18  [0, 1, 1, 0, 0, 1, 0, 0]  [0, 0, 1, 0]        0         6.727\n",
      "                  data_index        answer  carries  solving_time\n",
      "13  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         4.131\n",
      "31  [1, 0, 1, 0, 0, 1, 1, 0]  [0, 1, 0, 0]        1         4.244\n",
      "15  [1, 1, 0, 0, 1, 0, 1, 0]  [0, 0, 1, 0]        1         5.025\n",
      "39  [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1         7.025\n",
      "26  [1, 1, 1, 0, 1, 1, 0, 1]  [0, 0, 0, 1]        1         7.087\n",
      "4   [1, 1, 0, 1, 1, 0, 1, 1]  [0, 0, 1, 0]        1         7.103\n",
      "14  [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1         9.180\n",
      "21  [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 1, 0]        1         9.664\n",
      "23  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         9.962\n",
      "                  data_index        answer  carries  solving_time\n",
      "5   [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2         4.790\n",
      "3   [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         5.650\n",
      "30  [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2         6.259\n",
      "25  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         7.369\n",
      "16  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         7.930\n",
      "27  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2        12.663\n",
      "17  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2        13.683\n",
      "24  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2        15.804\n",
      "1   [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2        25.008\n",
      "                  data_index        answer  carries  solving_time\n",
      "29  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         6.681\n",
      "22  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         7.416\n",
      "35  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        10.555\n",
      "38  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3        12.538\n",
      "19  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3        13.538\n",
      "32  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        14.711\n",
      "12  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3        15.897\n",
      "0   [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3        25.018\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_16_18_42.39139_1999_2_3_PREMEDICINE.result\n",
      "carries\n",
      "0     2.6281\n",
      "1     5.7638\n",
      "2    10.4346\n",
      "3     8.7369\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     3.551001\n",
      "1     9.787533\n",
      "2    16.336614\n",
      "3    13.303469\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "21  [0, 1, 1, 0, 0, 1, 1, 0]  [0, 0, 0, 0]        0         2.009\n",
      "17  [1, 0, 1, 0, 1, 0, 1, 0]  [0, 0, 0, 0]        0         2.134\n",
      "37  [1, 0, 1, 1, 0, 0, 1, 1]  [1, 0, 0, 0]        0         2.306\n",
      "5   [1, 1, 1, 0, 1, 1, 1, 0]  [0, 0, 0, 0]        0         2.448\n",
      "39  [1, 0, 1, 0, 0, 0, 1, 0]  [1, 0, 0, 0]        0         2.634\n",
      "10  [1, 1, 1, 1, 0, 1, 1, 1]  [1, 0, 0, 0]        0         2.635\n",
      "16  [1, 1, 0, 0, 0, 1, 0, 0]  [1, 0, 0, 0]        0         2.666\n",
      "7   [0, 1, 0, 1, 0, 1, 0, 0]  [0, 0, 0, 1]        0         2.866\n",
      "4   [0, 1, 1, 1, 0, 1, 0, 0]  [0, 0, 1, 1]        0         2.964\n",
      "26  [0, 1, 0, 1, 0, 0, 0, 1]  [0, 1, 0, 0]        0         3.619\n",
      "                  data_index        answer  carries  solving_time\n",
      "24  [0, 1, 0, 0, 0, 0, 1, 0]  [0, 0, 1, 0]        1         3.525\n",
      "22  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         3.619\n",
      "32  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         3.837\n",
      "9   [0, 1, 0, 1, 0, 0, 1, 0]  [0, 0, 1, 1]        1         4.931\n",
      "11  [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1         5.603\n",
      "19  [1, 0, 1, 0, 1, 0, 0, 1]  [0, 0, 0, 1]        1         5.619\n",
      "36  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         5.790\n",
      "3   [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1         7.150\n",
      "8   [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         7.728\n",
      "2   [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         9.836\n",
      "                  data_index        answer  carries  solving_time\n",
      "38  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         6.181\n",
      "23  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         6.587\n",
      "20  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         8.348\n",
      "34  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2         9.555\n",
      "15  [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2         9.961\n",
      "14  [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2        10.212\n",
      "1   [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2        12.149\n",
      "0   [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2        12.947\n",
      "29  [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 1]        2        13.102\n",
      "13  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2        15.304\n",
      "                  data_index        answer  carries  solving_time\n",
      "33  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.665\n",
      "18  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         6.606\n",
      "30  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         6.634\n",
      "28  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         7.368\n",
      "27  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         8.039\n",
      "35  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         8.383\n",
      "12  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        10.415\n",
      "25  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3        10.883\n",
      "6   [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3        10.915\n",
      "31  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        12.461\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-03-27_17_18_46.01867_1992_1_3_COMPUTER SCIENCE.result\n",
      "carries\n",
      "0    5.112400\n",
      "1    6.188100\n",
      "2    8.558857\n",
      "3    8.725500\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     9.257223\n",
      "1     8.584126\n",
      "2    13.917424\n",
      "3    16.077354\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "17  [0, 0, 0, 1, 0, 0, 0, 0]  [0, 0, 0, 1]        0         2.412\n",
      "1   [0, 1, 1, 1, 0, 0, 0, 0]  [0, 1, 1, 1]        0         3.195\n",
      "14  [1, 1, 1, 1, 1, 0, 0, 1]  [0, 1, 1, 0]        0         3.563\n",
      "13  [1, 1, 1, 1, 0, 0, 0, 1]  [1, 1, 1, 0]        0         3.824\n",
      "39  [1, 0, 1, 1, 1, 0, 0, 1]  [0, 0, 1, 0]        0         4.389\n",
      "6   [1, 1, 0, 1, 1, 0, 0, 1]  [0, 1, 0, 0]        0         4.530\n",
      "25  [0, 1, 1, 1, 0, 0, 1, 0]  [0, 1, 0, 1]        0         5.714\n",
      "35  [1, 1, 1, 0, 0, 1, 1, 0]  [1, 0, 0, 0]        0         7.500\n",
      "29  [0, 1, 1, 0, 0, 1, 0, 0]  [0, 0, 1, 0]        0         7.856\n",
      "11  [1, 1, 1, 1, 1, 0, 1, 1]  [0, 1, 0, 0]        0         8.141\n",
      "                  data_index        answer  carries  solving_time\n",
      "30  [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 0, 0]        1         4.598\n",
      "3   [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         4.821\n",
      "4   [0, 1, 0, 1, 0, 0, 1, 0]  [0, 0, 1, 1]        1         5.027\n",
      "23  [1, 1, 0, 0, 1, 0, 1, 0]  [0, 0, 1, 0]        1         5.306\n",
      "18  [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         6.171\n",
      "12  [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1         6.338\n",
      "33  [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1]        1         6.908\n",
      "38  [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         7.423\n",
      "27  [1, 1, 1, 0, 1, 1, 0, 1]  [0, 0, 0, 1]        1         7.438\n",
      "32  [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1         7.851\n",
      "                  data_index        answer  carries  solving_time\n",
      "21  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         6.401\n",
      "22  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         6.686\n",
      "36  [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2         7.090\n",
      "0   [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 1]        2         7.538\n",
      "10  [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         8.323\n",
      "19  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         9.836\n",
      "20  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2        14.038\n",
      "                  data_index        answer  carries  solving_time\n",
      "26  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         3.980\n",
      "34  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.509\n",
      "31  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         6.249\n",
      "16  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         6.657\n",
      "28  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         9.028\n",
      "9   [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3        11.798\n",
      "37  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3        13.090\n",
      "8   [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3        13.493\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-01_14_13_24.37854_1999_1_3_POLITICAL SCIENCE & INTERNATIONAL RELATIONS.result\n",
      "carries\n",
      "0    2.920700\n",
      "1    4.583500\n",
      "2    6.451714\n",
      "3    7.202200\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     4.475480\n",
      "1     6.595869\n",
      "2     9.401119\n",
      "3    11.236982\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "34  [0, 1, 0, 0, 0, 0, 0, 0]  [0, 1, 0, 0]        0         2.119\n",
      "23  [0, 0, 1, 1, 0, 0, 1, 1]  [0, 0, 0, 0]        0         2.259\n",
      "25  [1, 1, 1, 1, 0, 1, 1, 1]  [1, 0, 0, 0]        0         2.354\n",
      "17  [1, 0, 0, 1, 1, 0, 0, 0]  [0, 0, 0, 1]        0         2.447\n",
      "27  [1, 1, 0, 0, 1, 0, 0, 0]  [0, 1, 0, 0]        0         2.791\n",
      "4   [0, 0, 1, 0, 0, 0, 1, 0]  [0, 0, 0, 0]        0         2.932\n",
      "29  [1, 1, 1, 0, 1, 0, 0, 0]  [0, 1, 1, 0]        0         3.103\n",
      "9   [0, 1, 1, 1, 0, 1, 0, 1]  [0, 0, 1, 0]        0         3.153\n",
      "8   [1, 1, 1, 0, 0, 1, 0, 0]  [1, 0, 1, 0]        0         3.227\n",
      "31  [1, 1, 1, 1, 1, 0, 1, 0]  [0, 1, 0, 1]        0         4.822\n",
      "                  data_index        answer  carries  solving_time\n",
      "18  [0, 1, 0, 1, 0, 0, 1, 0]  [0, 0, 1, 1]        1         2.869\n",
      "39  [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         3.138\n",
      "24  [1, 0, 1, 0, 1, 0, 0, 1]  [0, 0, 0, 1]        1         3.931\n",
      "13  [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         4.463\n",
      "30  [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 1, 0]        1         4.524\n",
      "15  [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1         5.056\n",
      "28  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         5.056\n",
      "26  [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1]        1         5.466\n",
      "1   [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         5.479\n",
      "22  [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1         5.853\n",
      "                  data_index        answer  carries  solving_time\n",
      "36  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         3.965\n",
      "32  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         5.559\n",
      "2   [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         6.369\n",
      "12  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2         6.494\n",
      "16  [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 1]        2         6.634\n",
      "7   [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         7.444\n",
      "3   [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2         8.697\n",
      "                  data_index        answer  carries  solving_time\n",
      "37  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         4.790\n",
      "19  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         5.490\n",
      "21  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         7.509\n",
      "6   [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         8.839\n",
      "11  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         9.383\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_15_07_38.02637_2000_1_3_MATHEMATICS.result\n",
      "carries\n",
      "0    2.8324\n",
      "1    4.5402\n",
      "2    4.7696\n",
      "3    5.6346\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     3.627081\n",
      "1     6.717088\n",
      "2     6.969485\n",
      "3    10.445369\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "15  [0, 1, 1, 1, 0, 0, 1, 1]  [0, 1, 0, 0]        0         2.307\n",
      "23  [1, 1, 1, 0, 1, 1, 0, 0]  [0, 0, 1, 0]        0         2.477\n",
      "39  [1, 0, 1, 0, 0, 0, 1, 0]  [1, 0, 0, 0]        0         2.541\n",
      "2   [1, 0, 1, 1, 1, 0, 0, 1]  [0, 0, 1, 0]        0         2.604\n",
      "37  [1, 1, 0, 0, 0, 1, 0, 0]  [1, 0, 0, 0]        0         2.633\n",
      "35  [1, 1, 1, 1, 0, 0, 1, 0]  [1, 1, 0, 1]        0         2.647\n",
      "19  [0, 1, 1, 1, 0, 0, 1, 0]  [0, 1, 0, 1]        0         3.198\n",
      "7   [1, 1, 1, 1, 1, 0, 1, 1]  [0, 1, 0, 0]        0         3.276\n",
      "22  [1, 1, 1, 0, 1, 0, 1, 0]  [0, 1, 0, 0]        0         3.306\n",
      "1   [0, 0, 1, 1, 0, 0, 0, 1]  [0, 0, 1, 0]        0         3.335\n",
      "                  data_index        answer  carries  solving_time\n",
      "12  [1, 0, 1, 0, 1, 0, 0, 1]  [0, 0, 0, 1]        1         3.635\n",
      "11  [1, 0, 1, 1, 0, 1, 1, 0]  [0, 1, 0, 1]        1         3.790\n",
      "18  [0, 1, 1, 0, 0, 1, 0, 1]  [0, 0, 0, 1]        1         3.853\n",
      "14  [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 1, 0]        1         3.947\n",
      "27  [1, 1, 0, 1, 1, 0, 1, 1]  [0, 0, 1, 0]        1         4.040\n",
      "6   [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1]        1         4.072\n",
      "34  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         4.462\n",
      "36  [0, 1, 0, 1, 0, 0, 1, 0]  [0, 0, 1, 1]        1         4.775\n",
      "31  [1, 1, 1, 0, 1, 1, 0, 1]  [0, 0, 0, 1]        1         5.742\n",
      "20  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         7.086\n",
      "                  data_index        answer  carries  solving_time\n",
      "38  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         3.304\n",
      "5   [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2         3.432\n",
      "16  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         3.695\n",
      "30  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         4.150\n",
      "28  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         4.650\n",
      "17  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         4.957\n",
      "13  [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2         5.557\n",
      "21  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         5.557\n",
      "0   [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2         6.041\n",
      "8   [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         6.353\n",
      "                  data_index        answer  carries  solving_time\n",
      "33  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         3.197\n",
      "25  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         3.371\n",
      "3   [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         4.033\n",
      "24  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         4.150\n",
      "26  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         4.689\n",
      "4   [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         4.728\n",
      "29  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         5.992\n",
      "9   [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         7.384\n",
      "32  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         8.184\n",
      "10  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        10.618\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-03-29_16_11_33.18310_1992_1_3_CHEMISTRY.result\n",
      "carries\n",
      "0    3.325500\n",
      "1    7.225222\n",
      "2    7.628900\n",
      "3    9.008778\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     4.745969\n",
      "1    14.034720\n",
      "2    13.635899\n",
      "3    20.446910\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "19  [0, 0, 0, 1, 0, 0, 0, 0]  [0, 0, 0, 1]        0         2.200\n",
      "29  [0, 1, 1, 1, 0, 1, 1, 0]  [0, 0, 0, 1]        0         2.450\n",
      "34  [1, 0, 0, 0, 1, 0, 0, 0]  [0, 0, 0, 0]        0         3.019\n",
      "0   [0, 0, 0, 1, 0, 0, 0, 1]  [0, 0, 0, 0]        0         3.023\n",
      "7   [1, 1, 1, 1, 1, 1, 0, 0]  [0, 0, 1, 1]        0         3.221\n",
      "11  [1, 0, 0, 1, 0, 0, 0, 0]  [1, 0, 0, 1]        0         3.492\n",
      "23  [1, 0, 0, 1, 0, 0, 0, 1]  [1, 0, 0, 0]        0         3.532\n",
      "22  [1, 1, 1, 0, 0, 0, 1, 0]  [1, 1, 0, 0]        0         3.828\n",
      "16  [1, 1, 1, 1, 0, 0, 1, 1]  [1, 1, 0, 0]        0         3.860\n",
      "15  [1, 1, 0, 1, 0, 1, 0, 1]  [1, 0, 0, 0]        0         4.630\n",
      "                  data_index        answer  carries  solving_time\n",
      "39  [1, 1, 1, 0, 1, 1, 0, 1]  [0, 0, 0, 1]        1         3.444\n",
      "12  [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 0]        1         3.624\n",
      "1   [1, 0, 1, 0, 0, 1, 1, 0]  [0, 1, 0, 0]        1         4.572\n",
      "14  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         4.988\n",
      "30  [1, 1, 0, 0, 1, 0, 1, 0]  [0, 0, 1, 0]        1         6.771\n",
      "17  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         8.715\n",
      "21  [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 0, 0]        1         8.815\n",
      "37  [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1        11.065\n",
      "4   [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1        13.033\n",
      "                  data_index        answer  carries  solving_time\n",
      "35  [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 1]        2         3.183\n",
      "24  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         4.001\n",
      "6   [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         5.627\n",
      "36  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         6.283\n",
      "32  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         6.747\n",
      "28  [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2         8.133\n",
      "38  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         8.582\n",
      "27  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2        10.426\n",
      "3   [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2        11.277\n",
      "31  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2        12.030\n",
      "                  data_index        answer  carries  solving_time\n",
      "8   [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         4.070\n",
      "18  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         4.149\n",
      "10  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         4.166\n",
      "33  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.312\n",
      "5   [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         7.301\n",
      "9   [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         7.691\n",
      "2   [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3        12.510\n",
      "13  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        17.729\n",
      "26  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3        18.151\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-01_13_20_06.53436_2000_2_4_COMPUTER ENGINEERING.result\n",
      "carries\n",
      "0    3.400000\n",
      "1    4.826200\n",
      "2    7.048000\n",
      "3    6.666222\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     5.647468\n",
      "1     6.020397\n",
      "2    11.086824\n",
      "3     9.545287\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "26  [0, 0, 1, 1, 0, 0, 1, 1]  [0, 0, 0, 0]        0         2.402\n",
      "14  [0, 1, 0, 1, 0, 1, 0, 1]  [0, 0, 0, 0]        0         2.448\n",
      "0   [0, 1, 1, 1, 0, 1, 1, 1]  [0, 0, 0, 0]        0         2.463\n",
      "30  [1, 1, 1, 1, 0, 1, 0, 0]  [1, 0, 1, 1]        0         2.834\n",
      "37  [1, 1, 1, 1, 0, 1, 1, 0]  [1, 0, 0, 1]        0         3.088\n",
      "29  [0, 1, 1, 0, 0, 0, 0, 0]  [0, 1, 1, 0]        0         3.336\n",
      "18  [1, 0, 1, 1, 1, 0, 1, 0]  [0, 0, 0, 1]        0         3.354\n",
      "22  [1, 1, 1, 0, 0, 1, 0, 0]  [1, 0, 1, 0]        0         3.838\n",
      "39  [1, 0, 0, 1, 0, 0, 0, 1]  [1, 0, 0, 0]        0         4.103\n",
      "9   [1, 0, 1, 1, 1, 0, 1, 1]  [0, 0, 0, 0]        0         6.134\n",
      "                  data_index        answer  carries  solving_time\n",
      "33  [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 0]        1         4.013\n",
      "35  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         4.041\n",
      "13  [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 0, 0]        1         4.305\n",
      "21  [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         4.790\n",
      "31  [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         4.841\n",
      "25  [0, 1, 1, 0, 0, 1, 0, 1]  [0, 0, 0, 1]        1         4.916\n",
      "24  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         4.978\n",
      "32  [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1         5.189\n",
      "19  [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1         5.198\n",
      "27  [1, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0]        1         5.991\n",
      "                  data_index        answer  carries  solving_time\n",
      "4   [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         4.494\n",
      "11  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         4.525\n",
      "34  [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         5.619\n",
      "3   [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2         6.619\n",
      "23  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         7.899\n",
      "5   [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         8.634\n",
      "6   [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         9.102\n",
      "20  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         9.492\n",
      "                  data_index        answer  carries  solving_time\n",
      "28  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         4.414\n",
      "36  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.110\n",
      "15  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         6.274\n",
      "10  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         6.322\n",
      "2   [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         6.622\n",
      "38  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         6.712\n",
      "1   [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         7.119\n",
      "12  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         8.368\n",
      "17  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         9.055\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-01_16_18_37.19890_1999_2_4_MEDICINE.result\n",
      "carries\n",
      "0     2.815700\n",
      "1     8.908667\n",
      "2    11.277750\n",
      "3     7.631500\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     3.814609\n",
      "1    16.907175\n",
      "2    25.377852\n",
      "3    14.229060\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "17  [1, 1, 1, 1, 0, 0, 0, 0]  [1, 1, 1, 1]        0         1.917\n",
      "37  [0, 0, 1, 1, 0, 0, 0, 0]  [0, 0, 1, 1]        0         2.291\n",
      "28  [1, 0, 1, 1, 1, 0, 0, 0]  [0, 0, 1, 1]        0         2.557\n",
      "1   [1, 1, 1, 1, 1, 0, 1, 0]  [0, 1, 0, 1]        0         2.666\n",
      "20  [1, 1, 0, 1, 0, 0, 0, 1]  [1, 1, 0, 0]        0         2.731\n",
      "12  [1, 0, 1, 1, 0, 0, 1, 0]  [1, 0, 0, 1]        0         2.864\n",
      "34  [1, 0, 0, 1, 1, 0, 0, 0]  [0, 0, 0, 1]        0         2.915\n",
      "30  [0, 1, 1, 0, 0, 1, 0, 0]  [0, 0, 1, 0]        0         3.322\n",
      "22  [1, 1, 1, 1, 1, 1, 1, 0]  [0, 0, 0, 1]        0         3.447\n",
      "25  [1, 1, 1, 1, 1, 0, 0, 1]  [0, 1, 1, 0]        0         3.447\n",
      "                  data_index        answer  carries  solving_time\n",
      "6   [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         5.428\n",
      "35  [0, 1, 0, 0, 0, 0, 1, 0]  [0, 0, 1, 0]        1         6.961\n",
      "27  [0, 1, 1, 0, 0, 1, 0, 1]  [0, 0, 0, 1]        1         7.105\n",
      "36  [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1         7.633\n",
      "7   [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         9.772\n",
      "39  [1, 1, 0, 1, 1, 0, 1, 1]  [0, 0, 1, 0]        1        16.553\n",
      "                  data_index        answer  carries  solving_time\n",
      "8   [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 1]        2         3.979\n",
      "9   [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         5.821\n",
      "38  [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2         7.848\n",
      "23  [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         7.862\n",
      "29  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2        11.289\n",
      "3   [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2        13.287\n",
      "0   [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2        13.631\n",
      "14  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2        26.505\n",
      "                  data_index        answer  carries  solving_time\n",
      "32  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         3.462\n",
      "18  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         4.195\n",
      "15  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         4.868\n",
      "13  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         5.946\n",
      "31  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         6.853\n",
      "16  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         7.352\n",
      "24  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         8.665\n",
      "10  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         9.914\n",
      "5   [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        11.243\n",
      "11  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3        13.817\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-01_15_20_28.54539_2000_1_2_ECONOMICS.result\n",
      "carries\n",
      "0     5.029600\n",
      "1    16.120444\n",
      "2    25.725875\n",
      "3    10.900556\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     8.355458\n",
      "1    39.827786\n",
      "2    85.018162\n",
      "3    21.412745\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "28  [0, 1, 0, 1, 0, 1, 0, 1]  [0, 0, 0, 0]        0         2.932\n",
      "9   [0, 0, 0, 1, 0, 0, 0, 1]  [0, 0, 0, 0]        0         3.181\n",
      "31  [1, 1, 1, 0, 0, 1, 1, 0]  [1, 0, 0, 0]        0         3.962\n",
      "39  [1, 0, 0, 1, 0, 0, 0, 0]  [1, 0, 0, 1]        0         4.306\n",
      "24  [1, 0, 0, 1, 1, 0, 0, 0]  [0, 0, 0, 1]        0         4.322\n",
      "35  [1, 1, 0, 0, 0, 1, 0, 0]  [1, 0, 0, 0]        0         4.431\n",
      "8   [1, 1, 0, 1, 0, 1, 0, 1]  [1, 0, 0, 0]        0         5.681\n",
      "26  [0, 1, 1, 1, 0, 0, 1, 0]  [0, 1, 0, 1]        0         6.775\n",
      "5   [0, 1, 1, 1, 0, 1, 0, 1]  [0, 0, 1, 0]        0         6.978\n",
      "20  [1, 0, 1, 1, 1, 0, 1, 0]  [0, 0, 0, 1]        0         7.728\n",
      "                  data_index        answer  carries  solving_time\n",
      "11  [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 0]        1         5.243\n",
      "6   [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         5.666\n",
      "0   [1, 0, 1, 0, 1, 0, 0, 1]  [0, 0, 0, 1]        1         7.605\n",
      "10  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         7.634\n",
      "32  [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1        12.759\n",
      "13  [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1        15.914\n",
      "25  [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1        20.756\n",
      "2   [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1        31.238\n",
      "1   [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1]        1        38.269\n",
      "                  data_index        answer  carries  solving_time\n",
      "23  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         5.462\n",
      "34  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         8.696\n",
      "27  [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2         8.867\n",
      "37  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2        12.149\n",
      "14  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2        14.414\n",
      "12  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2        24.443\n",
      "30  [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2        37.362\n",
      "7   [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2        94.414\n",
      "                  data_index        answer  carries  solving_time\n",
      "15  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.525\n",
      "38  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         5.774\n",
      "4   [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         8.150\n",
      "36  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         8.227\n",
      "33  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         8.540\n",
      "18  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3        10.696\n",
      "22  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        12.571\n",
      "21  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3        18.522\n",
      "3   [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3        20.100\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-03-28_18_52_30.47851_1990_1_3_CHEMICAL BIOLOGICAL ENGINEERING.result\n",
      "carries\n",
      "0     3.126800\n",
      "1     5.741200\n",
      "2    10.427200\n",
      "3     7.176667\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     7.752273\n",
      "1     8.917928\n",
      "2    17.330612\n",
      "3    18.006520\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "30  [0, 0, 0, 1, 0, 0, 0, 0]  [0, 0, 0, 1]        0         1.825\n",
      "27  [0, 0, 1, 1, 0, 0, 1, 0]  [0, 0, 0, 1]        0         1.832\n",
      "34  [1, 1, 1, 1, 0, 1, 1, 1]  [1, 0, 0, 0]        0         1.834\n",
      "18  [1, 1, 1, 1, 0, 0, 1, 1]  [1, 1, 0, 0]        0         2.014\n",
      "38  [1, 1, 0, 1, 0, 1, 0, 1]  [1, 0, 0, 0]        0         2.095\n",
      "3   [0, 0, 1, 1, 0, 0, 1, 1]  [0, 0, 0, 0]        0         2.238\n",
      "25  [1, 0, 0, 1, 1, 0, 0, 0]  [0, 0, 0, 1]        0         2.310\n",
      "5   [1, 1, 0, 1, 0, 0, 0, 0]  [1, 1, 0, 1]        0         3.140\n",
      "17  [1, 1, 0, 1, 1, 0, 0, 1]  [0, 1, 0, 0]        0         4.812\n",
      "0   [1, 1, 1, 0, 0, 1, 0, 0]  [1, 0, 1, 0]        0         9.168\n",
      "                  data_index        answer  carries  solving_time\n",
      "21  [1, 0, 1, 0, 0, 1, 1, 0]  [0, 1, 0, 0]        1         3.114\n",
      "16  [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         4.266\n",
      "12  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         4.937\n",
      "9   [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 0]        1         5.172\n",
      "32  [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1         5.200\n",
      "20  [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 0, 0]        1         5.214\n",
      "13  [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1]        1         6.460\n",
      "8   [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1         7.314\n",
      "29  [1, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0]        1         7.704\n",
      "1   [1, 1, 0, 0, 1, 0, 1, 0]  [0, 0, 1, 0]        1         8.031\n",
      "                  data_index        answer  carries  solving_time\n",
      "31  [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         5.336\n",
      "33  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         5.794\n",
      "2   [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 1]        2         6.836\n",
      "11  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         8.862\n",
      "15  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2        11.581\n",
      "22  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2        11.838\n",
      "35  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2        12.445\n",
      "24  [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2        13.252\n",
      "4   [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2        13.391\n",
      "7   [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2        14.937\n",
      "                  data_index        answer  carries  solving_time\n",
      "26  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         3.516\n",
      "19  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         4.733\n",
      "37  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         5.452\n",
      "39  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         5.506\n",
      "36  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         5.748\n",
      "10  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3        18.105\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-01_16_12_10.06150_1999_1_3_PSYCHOLOGY.result\n",
      "carries\n",
      "0    2.8901\n",
      "1    4.0812\n",
      "2    5.2420\n",
      "3    7.5169\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     3.861874\n",
      "1     6.833930\n",
      "2     7.986858\n",
      "3    12.256476\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "13  [1, 1, 1, 1, 0, 1, 1, 1]  [1, 0, 0, 0]        0         2.322\n",
      "6   [1, 1, 1, 1, 1, 0, 1, 1]  [0, 1, 0, 0]        0         2.541\n",
      "0   [0, 0, 0, 1, 0, 0, 0, 0]  [0, 0, 0, 1]        0         2.623\n",
      "28  [1, 1, 1, 1, 1, 1, 1, 1]  [0, 0, 0, 0]        0         2.635\n",
      "38  [1, 1, 0, 1, 0, 0, 0, 0]  [1, 1, 0, 1]        0         2.694\n",
      "16  [1, 1, 0, 0, 1, 0, 0, 0]  [0, 1, 0, 0]        0         2.706\n",
      "1   [1, 0, 1, 0, 1, 0, 0, 0]  [0, 0, 1, 0]        0         2.823\n",
      "2   [0, 1, 1, 1, 0, 1, 1, 0]  [0, 0, 0, 1]        0         3.135\n",
      "9   [1, 1, 1, 0, 1, 1, 1, 0]  [0, 0, 0, 0]        0         3.539\n",
      "34  [1, 1, 1, 1, 0, 0, 1, 0]  [1, 1, 0, 1]        0         3.883\n",
      "                  data_index        answer  carries  solving_time\n",
      "22  [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         2.916\n",
      "15  [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 0]        1         2.959\n",
      "18  [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 1, 0]        1         2.977\n",
      "17  [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 0, 0]        1         3.161\n",
      "3   [1, 1, 0, 1, 1, 0, 1, 1]  [0, 0, 1, 0]        1         3.885\n",
      "26  [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         3.931\n",
      "5   [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1         4.120\n",
      "36  [1, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0]        1         4.584\n",
      "21  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         4.802\n",
      "19  [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1         7.477\n",
      "                  data_index        answer  carries  solving_time\n",
      "20  [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         3.821\n",
      "23  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2         3.947\n",
      "30  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         4.072\n",
      "7   [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2         4.492\n",
      "4   [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         4.633\n",
      "10  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         5.508\n",
      "37  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         6.208\n",
      "33  [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2         7.165\n",
      "12  [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2         7.332\n",
      "                  data_index        answer  carries  solving_time\n",
      "25  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         4.646\n",
      "14  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         5.056\n",
      "31  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.679\n",
      "32  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         5.746\n",
      "8   [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         6.803\n",
      "11  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         8.348\n",
      "39  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         8.539\n",
      "29  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         8.908\n",
      "24  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         9.140\n",
      "27  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3        12.304\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-01_16_30_25.49509_1999_2_2_PSYCHOLOGY.result\n",
      "carries\n",
      "0     4.934200\n",
      "1     8.221000\n",
      "2     9.677333\n",
      "3    11.754125\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     7.974847\n",
      "1    18.882877\n",
      "2    14.580885\n",
      "3    19.570144\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "11  [1, 1, 1, 1, 0, 0, 0, 0]  [1, 1, 1, 1]        0         3.493\n",
      "10  [1, 1, 1, 1, 1, 1, 1, 1]  [0, 0, 0, 0]        0         3.947\n",
      "39  [1, 0, 1, 1, 0, 0, 1, 1]  [1, 0, 0, 0]        0         4.103\n",
      "7   [1, 0, 1, 0, 1, 0, 1, 0]  [0, 0, 0, 0]        0         4.197\n",
      "14  [1, 1, 0, 1, 1, 1, 0, 1]  [0, 0, 0, 0]        0         4.353\n",
      "22  [1, 1, 0, 1, 1, 0, 0, 1]  [0, 1, 0, 0]        0         4.384\n",
      "2   [1, 1, 1, 1, 1, 0, 0, 1]  [0, 1, 1, 0]        0         4.463\n",
      "9   [1, 1, 0, 0, 1, 0, 0, 0]  [0, 1, 0, 0]        0         5.384\n",
      "36  [1, 1, 1, 1, 0, 1, 1, 0]  [1, 0, 0, 1]        0         6.462\n",
      "0   [0, 0, 1, 1, 0, 0, 1, 0]  [0, 0, 0, 1]        0         8.556\n",
      "                  data_index        answer  carries  solving_time\n",
      "20  [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         4.212\n",
      "31  [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         5.712\n",
      "33  [1, 1, 0, 1, 1, 0, 1, 1]  [0, 0, 1, 0]        1         5.759\n",
      "6   [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         5.900\n",
      "16  [1, 1, 1, 0, 1, 1, 0, 1]  [0, 0, 0, 1]        1         6.478\n",
      "4   [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 1, 0]        1         6.664\n",
      "30  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         6.868\n",
      "19  [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1         6.994\n",
      "25  [0, 1, 0, 1, 0, 0, 1, 0]  [0, 0, 1, 1]        1        11.086\n",
      "12  [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1        22.537\n",
      "                  data_index        answer  carries  solving_time\n",
      "37  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         6.669\n",
      "18  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         7.275\n",
      "32  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2         8.165\n",
      "8   [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         8.837\n",
      "29  [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         9.133\n",
      "38  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         9.493\n",
      "34  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2        11.227\n",
      "13  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2        11.836\n",
      "1   [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2        14.461\n",
      "                  data_index        answer  carries  solving_time\n",
      "28  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         6.493\n",
      "35  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         8.586\n",
      "27  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         9.493\n",
      "24  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3        10.977\n",
      "26  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3        11.493\n",
      "17  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3        13.148\n",
      "15  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3        14.914\n",
      "3   [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        18.929\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-03-28_17_16_33.10768_1982_1_4_COMPUTER SCIENCE.result\n",
      "carries\n",
      "0    2.929900\n",
      "1    6.124750\n",
      "2    6.208111\n",
      "3    6.380200\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     4.859632\n",
      "1    10.561683\n",
      "2    10.206037\n",
      "3    12.587651\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "27  [0, 0, 1, 0, 0, 0, 0, 0]  [0, 0, 1, 0]        0         2.005\n",
      "30  [0, 1, 1, 0, 0, 0, 0, 0]  [0, 1, 1, 0]        0         2.189\n",
      "31  [1, 1, 1, 0, 1, 1, 0, 0]  [0, 0, 1, 0]        0         2.199\n",
      "39  [1, 1, 1, 1, 0, 0, 1, 1]  [1, 1, 0, 0]        0         2.369\n",
      "34  [0, 1, 1, 0, 0, 1, 1, 0]  [0, 0, 0, 0]        0         2.641\n",
      "5   [1, 1, 1, 1, 0, 0, 0, 0]  [1, 1, 1, 1]        0         2.814\n",
      "24  [1, 0, 1, 1, 1, 0, 1, 0]  [0, 0, 0, 1]        0         3.033\n",
      "17  [1, 1, 1, 1, 1, 1, 0, 0]  [0, 0, 1, 1]        0         3.295\n",
      "19  [1, 0, 1, 1, 0, 0, 1, 1]  [1, 0, 0, 0]        0         3.456\n",
      "3   [1, 0, 1, 1, 1, 0, 0, 1]  [0, 0, 1, 0]        0         5.298\n",
      "                  data_index        answer  carries  solving_time\n",
      "8   [1, 0, 1, 0, 1, 0, 0, 1]  [0, 0, 0, 1]        1         3.563\n",
      "1   [0, 1, 0, 0, 0, 0, 1, 0]  [0, 0, 1, 0]        1         4.230\n",
      "38  [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1         5.123\n",
      "21  [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 0]        1         6.153\n",
      "11  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         6.252\n",
      "20  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         6.303\n",
      "22  [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 0, 0]        1         6.438\n",
      "13  [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1        10.936\n",
      "                  data_index        answer  carries  solving_time\n",
      "15  [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         4.571\n",
      "0   [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         5.014\n",
      "9   [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2         5.034\n",
      "16  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         5.084\n",
      "26  [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         5.390\n",
      "10  [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2         5.575\n",
      "23  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2         6.219\n",
      "12  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         8.360\n",
      "29  [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2        10.626\n",
      "                  data_index        answer  carries  solving_time\n",
      "4   [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         3.736\n",
      "28  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         3.756\n",
      "18  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         3.803\n",
      "35  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         4.000\n",
      "33  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         4.115\n",
      "2   [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         4.574\n",
      "25  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         9.277\n",
      "32  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         9.755\n",
      "6   [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3        10.135\n",
      "14  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3        10.651\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_15_17_38.07868_2000_1_3_MECHANICAL ENGINEERING.result\n",
      "carries\n",
      "0    3.273800\n",
      "1    5.301400\n",
      "2    7.005222\n",
      "3    8.455286\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     4.145429\n",
      "1     9.376523\n",
      "2    11.902208\n",
      "3    13.824581\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "20  [0, 1, 0, 0, 0, 1, 0, 0]  [0, 0, 0, 0]        0         2.604\n",
      "6   [1, 0, 0, 1, 0, 0, 0, 1]  [1, 0, 0, 0]        0         2.682\n",
      "25  [0, 1, 1, 0, 0, 1, 1, 0]  [0, 0, 0, 0]        0         2.774\n",
      "0   [0, 1, 0, 1, 0, 1, 0, 1]  [0, 0, 0, 0]        0         3.197\n",
      "30  [0, 1, 1, 1, 0, 0, 0, 1]  [0, 1, 1, 0]        0         3.370\n",
      "32  [1, 0, 1, 1, 1, 0, 0, 0]  [0, 0, 1, 1]        0         3.525\n",
      "24  [1, 0, 1, 1, 1, 0, 1, 0]  [0, 0, 0, 1]        0         3.556\n",
      "16  [1, 1, 0, 1, 1, 0, 0, 1]  [0, 1, 0, 0]        0         3.603\n",
      "12  [0, 1, 0, 1, 0, 0, 0, 0]  [0, 1, 0, 1]        0         3.651\n",
      "26  [1, 1, 0, 1, 0, 1, 0, 0]  [1, 0, 0, 1]        0         3.776\n",
      "                  data_index        answer  carries  solving_time\n",
      "1   [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         3.135\n",
      "34  [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         3.572\n",
      "38  [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         4.056\n",
      "5   [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         4.166\n",
      "13  [1, 0, 1, 0, 0, 1, 1, 0]  [0, 1, 0, 0]        1         4.228\n",
      "17  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         5.040\n",
      "28  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         5.228\n",
      "2   [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1         5.978\n",
      "19  [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1         8.258\n",
      "10  [0, 1, 0, 0, 0, 0, 1, 0]  [0, 0, 1, 0]        1         9.353\n",
      "                  data_index        answer  carries  solving_time\n",
      "33  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         4.040\n",
      "27  [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2         5.275\n",
      "15  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         5.713\n",
      "31  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2         5.836\n",
      "35  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         5.851\n",
      "39  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         6.665\n",
      "29  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2         7.790\n",
      "3   [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2        10.681\n",
      "4   [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2        11.196\n",
      "                  data_index        answer  carries  solving_time\n",
      "14  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         4.884\n",
      "22  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         6.478\n",
      "18  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         7.743\n",
      "21  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         8.290\n",
      "36  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         8.837\n",
      "23  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         9.524\n",
      "11  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3        13.431\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_16_15_28.77170_1995_1_4_ELECTRICAL AND COMPUTER ENGINEERING.result\n",
      "carries\n",
      "0    3.923000\n",
      "1    4.908889\n",
      "2    6.706125\n",
      "3    6.255667\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     6.022691\n",
      "1     7.243873\n",
      "2    10.731360\n",
      "3     9.031204\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "27  [1, 1, 1, 0, 0, 0, 0, 0]  [1, 1, 1, 0]        0         2.541\n",
      "19  [1, 1, 1, 1, 1, 0, 0, 1]  [0, 1, 1, 0]        0         3.165\n",
      "24  [1, 1, 0, 1, 0, 0, 0, 1]  [1, 1, 0, 0]        0         3.322\n",
      "17  [0, 0, 1, 0, 0, 0, 0, 0]  [0, 0, 1, 0]        0         3.430\n",
      "34  [0, 0, 1, 1, 0, 0, 1, 0]  [0, 0, 0, 1]        0         3.460\n",
      "36  [1, 1, 1, 1, 1, 0, 1, 0]  [0, 1, 0, 1]        0         3.650\n",
      "0   [1, 1, 1, 1, 0, 1, 0, 1]  [1, 0, 1, 0]        0         4.072\n",
      "10  [1, 0, 0, 1, 0, 0, 0, 1]  [1, 0, 0, 0]        0         4.150\n",
      "39  [1, 0, 1, 1, 0, 0, 0, 1]  [1, 0, 1, 0]        0         5.650\n",
      "2   [1, 1, 0, 1, 1, 0, 0, 0]  [0, 1, 0, 1]        0         5.790\n",
      "                  data_index        answer  carries  solving_time\n",
      "31  [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         3.416\n",
      "23  [1, 0, 1, 1, 0, 1, 1, 0]  [0, 1, 0, 1]        1         3.994\n",
      "6   [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         4.011\n",
      "38  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         4.088\n",
      "8   [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         5.025\n",
      "35  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         5.025\n",
      "15  [0, 1, 0, 1, 0, 0, 1, 0]  [0, 0, 1, 1]        1         5.291\n",
      "26  [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1         6.571\n",
      "11  [1, 1, 0, 1, 1, 0, 1, 1]  [0, 0, 1, 0]        1         6.759\n",
      "                  data_index        answer  carries  solving_time\n",
      "28  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         4.478\n",
      "3   [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         4.681\n",
      "25  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         5.322\n",
      "4   [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         6.009\n",
      "20  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         6.040\n",
      "16  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2         8.774\n",
      "18  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         9.149\n",
      "14  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         9.196\n",
      "                  data_index        answer  carries  solving_time\n",
      "32  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         4.791\n",
      "21  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         5.166\n",
      "30  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         5.243\n",
      "29  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.259\n",
      "33  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         5.525\n",
      "22  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         6.259\n",
      "13  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         7.665\n",
      "5   [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         8.165\n",
      "7   [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         8.228\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_16_21_57.11743_1997_2_3_POLITICAL SCIENCE.result\n",
      "carries\n",
      "0     4.309500\n",
      "1     6.534200\n",
      "2     8.646667\n",
      "3    12.555000\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     5.977044\n",
      "1     9.387149\n",
      "2    13.814826\n",
      "3    25.478768\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "14  [1, 1, 0, 0, 1, 1, 0, 0]  [0, 0, 0, 0]        0         3.166\n",
      "19  [1, 1, 1, 0, 1, 0, 1, 0]  [0, 1, 0, 0]        0         3.478\n",
      "29  [0, 0, 0, 1, 0, 0, 0, 0]  [0, 0, 0, 1]        0         3.728\n",
      "21  [1, 0, 0, 1, 1, 0, 0, 1]  [0, 0, 0, 0]        0         3.838\n",
      "39  [1, 1, 1, 1, 1, 0, 0, 1]  [0, 1, 1, 0]        0         3.900\n",
      "36  [1, 1, 1, 0, 0, 1, 0, 0]  [1, 0, 1, 0]        0         4.243\n",
      "33  [1, 0, 1, 1, 0, 0, 1, 0]  [1, 0, 0, 1]        0         4.666\n",
      "4   [0, 1, 1, 0, 0, 1, 0, 0]  [0, 0, 1, 0]        0         5.151\n",
      "17  [1, 1, 1, 1, 1, 1, 0, 0]  [0, 0, 1, 1]        0         5.338\n",
      "34  [1, 1, 1, 1, 1, 1, 1, 0]  [0, 0, 0, 1]        0         5.587\n",
      "                  data_index        answer  carries  solving_time\n",
      "10  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         4.634\n",
      "24  [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         5.368\n",
      "9   [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         5.369\n",
      "31  [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 0, 0]        1         6.197\n",
      "5   [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1         6.200\n",
      "6   [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1]        1         6.306\n",
      "22  [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1         6.477\n",
      "18  [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         7.009\n",
      "26  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         8.461\n",
      "15  [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1         9.321\n",
      "                  data_index        answer  carries  solving_time\n",
      "30  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         5.744\n",
      "2   [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2         6.806\n",
      "27  [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2         6.869\n",
      "38  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         7.149\n",
      "3   [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2         7.466\n",
      "37  [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         8.605\n",
      "0   [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         9.759\n",
      "1   [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2        12.195\n",
      "23  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2        13.227\n",
      "                  data_index        answer  carries  solving_time\n",
      "32  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         6.119\n",
      "28  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         7.415\n",
      "25  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         7.618\n",
      "11  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3        10.181\n",
      "16  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        14.117\n",
      "7   [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        20.929\n",
      "13  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3        21.506\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-03-27_15_30_26.12097_1993_1_3_COMPUTER SCIENCE.result\n",
      "carries\n",
      "0    2.315200\n",
      "1    5.360556\n",
      "2    6.365333\n",
      "3    9.161700\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     3.459292\n",
      "1     9.933567\n",
      "2    13.376560\n",
      "3    20.031322\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "38  [0, 0, 1, 0, 0, 0, 1, 0]  [0, 0, 0, 0]        0         1.681\n",
      "27  [1, 1, 1, 0, 1, 0, 0, 0]  [0, 1, 1, 0]        0         1.757\n",
      "34  [0, 0, 1, 1, 0, 0, 1, 0]  [0, 0, 0, 1]        0         1.905\n",
      "37  [0, 1, 1, 1, 0, 1, 1, 1]  [0, 0, 0, 0]        0         1.927\n",
      "9   [1, 1, 0, 1, 0, 1, 0, 1]  [1, 0, 0, 0]        0         2.111\n",
      "20  [1, 0, 1, 0, 1, 0, 1, 0]  [0, 0, 0, 0]        0         2.159\n",
      "8   [0, 1, 1, 1, 0, 0, 0, 0]  [0, 1, 1, 1]        0         2.368\n",
      "14  [1, 1, 1, 1, 0, 0, 1, 0]  [1, 1, 0, 1]        0         2.863\n",
      "2   [1, 1, 1, 1, 0, 0, 0, 1]  [1, 1, 1, 0]        0         3.116\n",
      "6   [1, 1, 0, 1, 1, 0, 0, 0]  [0, 1, 0, 1]        0         3.265\n",
      "                  data_index        answer  carries  solving_time\n",
      "32  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         1.711\n",
      "17  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         3.519\n",
      "39  [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         3.894\n",
      "0   [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         4.730\n",
      "24  [1, 0, 1, 1, 0, 1, 1, 0]  [0, 1, 0, 1]        1         4.953\n",
      "25  [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         5.551\n",
      "33  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         7.007\n",
      "19  [1, 1, 0, 0, 1, 0, 1, 0]  [0, 0, 1, 0]        1         7.854\n",
      "21  [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 1, 0]        1         9.026\n",
      "                  data_index        answer  carries  solving_time\n",
      "30  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         2.725\n",
      "35  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         2.835\n",
      "18  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         3.372\n",
      "28  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         4.484\n",
      "12  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         6.171\n",
      "31  [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2         6.880\n",
      "1   [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2         7.320\n",
      "3   [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2        11.085\n",
      "36  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2        12.416\n",
      "                  data_index        answer  carries  solving_time\n",
      "11  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         2.355\n",
      "23  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         2.525\n",
      "26  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         5.735\n",
      "22  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         7.368\n",
      "16  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         7.426\n",
      "13  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         8.833\n",
      "4   [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         8.844\n",
      "7   [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        13.652\n",
      "5   [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3        17.253\n",
      "29  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3        17.626\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-03-27_16_05_34.90836_1991_1_4_COMPUTER SCIENCE.result\n",
      "carries\n",
      "0     4.952500\n",
      "1     9.803111\n",
      "2    15.538889\n",
      "3    19.247125\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     9.128916\n",
      "1    21.216555\n",
      "2    28.828627\n",
      "3    40.455895\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "10  [0, 0, 1, 1, 0, 0, 0, 0]  [0, 0, 1, 1]        0         2.551\n",
      "39  [0, 1, 1, 1, 0, 1, 0, 0]  [0, 0, 1, 1]        0         3.027\n",
      "25  [1, 1, 0, 0, 0, 0, 0, 0]  [1, 1, 0, 0]        0         3.289\n",
      "26  [1, 0, 0, 1, 1, 0, 0, 0]  [0, 0, 0, 1]        0         3.824\n",
      "32  [1, 1, 1, 1, 1, 1, 1, 0]  [0, 0, 0, 1]        0         4.038\n",
      "23  [0, 1, 1, 0, 0, 1, 0, 0]  [0, 0, 1, 0]        0         4.324\n",
      "37  [0, 0, 1, 1, 0, 0, 1, 1]  [0, 0, 0, 0]        0         5.355\n",
      "31  [1, 1, 1, 1, 0, 1, 0, 0]  [1, 0, 1, 1]        0         6.831\n",
      "4   [1, 1, 1, 0, 0, 1, 1, 0]  [1, 0, 0, 0]        0         7.669\n",
      "7   [1, 0, 1, 1, 0, 0, 1, 1]  [1, 0, 0, 0]        0         8.617\n",
      "                  data_index        answer  carries  solving_time\n",
      "30  [0, 1, 0, 1, 0, 0, 1, 0]  [0, 0, 1, 1]        1         3.800\n",
      "29  [0, 1, 0, 0, 0, 0, 1, 0]  [0, 0, 1, 0]        1         5.118\n",
      "15  [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1         5.941\n",
      "17  [1, 1, 1, 0, 1, 1, 0, 1]  [0, 0, 0, 1]        1         6.150\n",
      "27  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         6.160\n",
      "34  [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1        11.036\n",
      "9   [1, 1, 0, 1, 1, 0, 1, 1]  [0, 0, 1, 0]        1        13.246\n",
      "22  [1, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0]        1        18.056\n",
      "36  [1, 1, 0, 0, 1, 0, 1, 0]  [0, 0, 1, 0]        1        18.721\n",
      "                  data_index        answer  carries  solving_time\n",
      "14  [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         8.876\n",
      "16  [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 1]        2         9.837\n",
      "18  [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2         9.955\n",
      "19  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2        12.729\n",
      "1   [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2        12.818\n",
      "24  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2        14.947\n",
      "20  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2        18.720\n",
      "5   [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2        25.216\n",
      "12  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2        26.752\n",
      "                  data_index        answer  carries  solving_time\n",
      "13  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         7.971\n",
      "11  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         8.682\n",
      "8   [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3        12.151\n",
      "28  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3        15.029\n",
      "6   [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3        19.490\n",
      "2   [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        25.154\n",
      "35  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3        26.400\n",
      "38  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        39.100\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-03-28_19_10_15.02378_1993_1_4_COMPUTER SCIENCE.result\n",
      "carries\n",
      "0    2.650889\n",
      "1    4.167625\n",
      "2    6.125333\n",
      "3    9.752333\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     4.764848\n",
      "1     8.744511\n",
      "2    13.939534\n",
      "3    25.578277\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "33  [0, 0, 0, 1, 0, 0, 0, 0]  [0, 0, 0, 1]        0         1.875\n",
      "11  [1, 0, 1, 1, 1, 0, 0, 0]  [0, 0, 1, 1]        0         1.939\n",
      "23  [0, 0, 0, 0, 0, 0, 0, 0]  [0, 0, 0, 0]        0         1.952\n",
      "1   [0, 0, 1, 1, 0, 0, 1, 1]  [0, 0, 0, 0]        0         2.046\n",
      "6   [0, 1, 1, 1, 0, 0, 0, 0]  [0, 1, 1, 1]        0         2.205\n",
      "38  [1, 0, 0, 0, 0, 0, 0, 0]  [1, 0, 0, 0]        0         2.268\n",
      "24  [1, 1, 1, 1, 1, 0, 1, 0]  [0, 1, 0, 1]        0         3.080\n",
      "10  [1, 1, 0, 1, 0, 0, 0, 0]  [1, 1, 0, 1]        0         3.424\n",
      "36  [0, 1, 1, 0, 0, 0, 1, 0]  [0, 1, 0, 0]        0         5.069\n",
      "                  data_index        answer  carries  solving_time\n",
      "12  [0, 1, 1, 0, 0, 1, 0, 1]  [0, 0, 0, 1]        1         1.678\n",
      "14  [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         2.412\n",
      "3   [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         2.925\n",
      "4   [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         3.600\n",
      "5   [1, 1, 0, 1, 1, 0, 1, 1]  [0, 0, 1, 0]        1         4.237\n",
      "30  [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1         4.271\n",
      "20  [1, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0]        1         5.085\n",
      "32  [1, 0, 1, 1, 0, 1, 1, 0]  [0, 1, 0, 1]        1         9.133\n",
      "                  data_index        answer  carries  solving_time\n",
      "18  [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 1]        2         2.454\n",
      "26  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         3.665\n",
      "28  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2         3.731\n",
      "9   [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         3.794\n",
      "19  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         4.698\n",
      "37  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         6.501\n",
      "0   [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         7.337\n",
      "15  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2         7.565\n",
      "34  [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2        15.383\n",
      "                  data_index        answer  carries  solving_time\n",
      "7   [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         2.152\n",
      "16  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         2.584\n",
      "8   [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         3.338\n",
      "29  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         4.383\n",
      "27  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         8.465\n",
      "25  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         8.694\n",
      "22  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3        16.134\n",
      "13  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3        17.489\n",
      "31  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3        24.532\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-01_14_22_32.37891_1996_1_3_GEOGRAPHY.result\n",
      "carries\n",
      "0     3.927400\n",
      "1     6.698600\n",
      "2    10.722100\n",
      "3    10.661875\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     5.254306\n",
      "1    10.222870\n",
      "2    19.818735\n",
      "3    19.168586\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "21  [1, 1, 1, 1, 0, 0, 0, 0]  [1, 1, 1, 1]        0         2.933\n",
      "13  [1, 0, 1, 1, 1, 0, 1, 1]  [0, 0, 0, 0]        0         3.239\n",
      "7   [0, 0, 0, 1, 0, 0, 0, 0]  [0, 0, 0, 1]        0         3.388\n",
      "36  [1, 1, 1, 1, 0, 1, 1, 1]  [1, 0, 0, 0]        0         3.634\n",
      "25  [1, 1, 0, 1, 0, 0, 0, 1]  [1, 1, 0, 0]        0         3.853\n",
      "19  [1, 1, 0, 1, 1, 1, 0, 0]  [0, 0, 0, 1]        0         4.045\n",
      "34  [1, 1, 1, 0, 1, 1, 0, 0]  [0, 0, 1, 0]        0         4.118\n",
      "2   [1, 1, 1, 1, 1, 1, 1, 0]  [0, 0, 0, 1]        0         4.385\n",
      "39  [1, 1, 0, 0, 1, 0, 0, 0]  [0, 1, 0, 0]        0         4.529\n",
      "1   [1, 0, 1, 1, 1, 0, 0, 1]  [0, 0, 1, 0]        0         5.150\n",
      "                  data_index        answer  carries  solving_time\n",
      "38  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         3.889\n",
      "30  [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1         5.040\n",
      "3   [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         5.073\n",
      "24  [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1         6.071\n",
      "33  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         6.150\n",
      "32  [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         7.227\n",
      "8   [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         7.821\n",
      "22  [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 1, 0]        1         7.853\n",
      "12  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         8.181\n",
      "6   [1, 0, 1, 0, 1, 0, 0, 1]  [0, 0, 0, 1]        1         9.681\n",
      "                  data_index        answer  carries  solving_time\n",
      "17  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         5.634\n",
      "23  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         7.103\n",
      "29  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         7.743\n",
      "31  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         8.759\n",
      "16  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         9.571\n",
      "27  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2        10.774\n",
      "4   [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2        11.320\n",
      "18  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2        11.664\n",
      "11  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2        12.601\n",
      "20  [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2        22.052\n",
      "                  data_index        answer  carries  solving_time\n",
      "28  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         6.290\n",
      "35  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         7.633\n",
      "37  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         7.990\n",
      "9   [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         9.553\n",
      "26  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         9.571\n",
      "14  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3        10.149\n",
      "15  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3        15.211\n",
      "0   [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3        18.898\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-01_16_18_56.68604_1999_2_3_ANTHROPOLOGY.result\n",
      "carries\n",
      "0    4.065300\n",
      "1    6.774778\n",
      "2    9.663444\n",
      "3    9.464667\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     6.028345\n",
      "1    10.283262\n",
      "2    17.003967\n",
      "3    14.307877\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "32  [0, 0, 0, 0, 0, 0, 0, 0]  [0, 0, 0, 0]        0         2.554\n",
      "15  [0, 0, 1, 1, 0, 0, 0, 0]  [0, 0, 1, 1]        0         3.165\n",
      "30  [0, 1, 0, 1, 0, 1, 0, 1]  [0, 0, 0, 0]        0         3.244\n",
      "37  [1, 1, 1, 1, 1, 0, 1, 1]  [0, 1, 0, 0]        0         3.447\n",
      "9   [0, 1, 1, 1, 0, 0, 0, 1]  [0, 1, 1, 0]        0         4.075\n",
      "6   [1, 0, 1, 1, 1, 0, 1, 1]  [0, 0, 0, 0]        0         4.195\n",
      "29  [1, 1, 0, 1, 1, 0, 0, 1]  [0, 1, 0, 0]        0         4.586\n",
      "27  [1, 0, 0, 0, 0, 0, 0, 0]  [1, 0, 0, 0]        0         4.666\n",
      "7   [1, 0, 1, 1, 0, 0, 1, 0]  [1, 0, 0, 1]        0         4.853\n",
      "12  [1, 1, 0, 1, 0, 0, 0, 1]  [1, 1, 0, 0]        0         5.868\n",
      "                  data_index        answer  carries  solving_time\n",
      "36  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         4.353\n",
      "25  [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 0]        1         4.774\n",
      "33  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         5.681\n",
      "13  [1, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0]        1         6.508\n",
      "5   [1, 1, 1, 0, 1, 1, 0, 1]  [0, 0, 0, 1]        1         6.965\n",
      "23  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         7.133\n",
      "21  [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1         7.556\n",
      "35  [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1]        1         7.820\n",
      "28  [1, 0, 1, 0, 1, 0, 0, 1]  [0, 0, 0, 1]        1        10.183\n",
      "                  data_index        answer  carries  solving_time\n",
      "3   [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         5.177\n",
      "1   [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2         6.884\n",
      "26  [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2         6.960\n",
      "31  [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         7.881\n",
      "0   [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 1]        2         8.868\n",
      "18  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         9.664\n",
      "22  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2        10.633\n",
      "39  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2        14.804\n",
      "16  [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2        16.100\n",
      "                  data_index        answer  carries  solving_time\n",
      "17  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.306\n",
      "14  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         7.431\n",
      "8   [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         7.742\n",
      "10  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         9.053\n",
      "2   [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         9.118\n",
      "34  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3        10.555\n",
      "20  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3        10.894\n",
      "4   [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        12.368\n",
      "24  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3        12.715\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_37_28.75707_2001_2_2_ENGLISH LANGUAGE EDUCATION.result\n",
      "carries\n",
      "0     3.4001\n",
      "1     6.1996\n",
      "2     8.5694\n",
      "3    13.4712\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     5.315459\n",
      "1     9.705478\n",
      "2    17.212014\n",
      "3    33.837057\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "12  [1, 1, 0, 1, 0, 0, 0, 1]  [1, 1, 0, 0]        0         2.619\n",
      "34  [1, 1, 1, 1, 0, 1, 1, 1]  [1, 0, 0, 0]        0         2.619\n",
      "38  [0, 1, 1, 1, 0, 0, 1, 1]  [0, 1, 0, 0]        0         2.728\n",
      "10  [1, 1, 1, 0, 0, 1, 1, 0]  [1, 0, 0, 0]        0         2.932\n",
      "16  [0, 1, 0, 1, 0, 1, 0, 1]  [0, 0, 0, 0]        0         2.963\n",
      "7   [0, 1, 0, 1, 0, 0, 0, 1]  [0, 1, 0, 0]        0         3.011\n",
      "19  [0, 1, 0, 0, 0, 0, 0, 0]  [0, 1, 0, 0]        0         3.244\n",
      "3   [1, 0, 1, 1, 1, 0, 0, 0]  [0, 0, 1, 1]        0         4.105\n",
      "37  [1, 0, 1, 1, 0, 0, 1, 0]  [1, 0, 0, 1]        0         4.162\n",
      "4   [1, 1, 1, 1, 0, 1, 0, 1]  [1, 0, 1, 0]        0         5.618\n",
      "                  data_index        answer  carries  solving_time\n",
      "11  [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         3.791\n",
      "8   [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         4.276\n",
      "39  [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         4.650\n",
      "36  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         5.272\n",
      "21  [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1]        1         5.775\n",
      "23  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         6.462\n",
      "6   [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 1, 0]        1         6.774\n",
      "2   [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1         7.822\n",
      "9   [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1         8.212\n",
      "35  [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1         8.962\n",
      "                  data_index        answer  carries  solving_time\n",
      "30  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         4.978\n",
      "17  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         5.603\n",
      "26  [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2         5.681\n",
      "22  [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2         6.166\n",
      "25  [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2         6.915\n",
      "29  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         7.538\n",
      "14  [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2         8.649\n",
      "5   [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         8.790\n",
      "15  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2        12.008\n",
      "33  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2        19.366\n",
      "                  data_index        answer  carries  solving_time\n",
      "32  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         6.509\n",
      "24  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         6.742\n",
      "28  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         8.229\n",
      "20  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         9.461\n",
      "18  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        10.723\n",
      "1   [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3        11.930\n",
      "31  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        12.554\n",
      "0   [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3        13.149\n",
      "13  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        13.929\n",
      "27  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3        41.486\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-01_16_23_59.06571_1999_2_4_KOREAN LANGUAGE AND LITERATURE.result\n",
      "carries\n",
      "0     3.644900\n",
      "1     7.204889\n",
      "2    10.839400\n",
      "3    12.084222\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     5.416517\n",
      "1    12.787359\n",
      "2    19.254983\n",
      "3    20.929461\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "38  [1, 1, 1, 1, 1, 0, 0, 0]  [0, 1, 1, 1]        0         2.690\n",
      "13  [1, 0, 1, 1, 0, 0, 0, 0]  [1, 0, 1, 1]        0         2.869\n",
      "17  [1, 0, 1, 1, 0, 0, 0, 1]  [1, 0, 1, 0]        0         2.948\n",
      "32  [0, 1, 1, 0, 0, 1, 1, 0]  [0, 0, 0, 0]        0         3.072\n",
      "11  [0, 1, 1, 0, 0, 0, 1, 0]  [0, 1, 0, 0]        0         3.181\n",
      "23  [1, 1, 0, 1, 1, 1, 0, 1]  [0, 0, 0, 0]        0         3.713\n",
      "34  [1, 1, 1, 1, 1, 1, 1, 0]  [0, 0, 0, 1]        0         3.838\n",
      "25  [1, 1, 0, 0, 0, 1, 0, 0]  [1, 0, 0, 0]        0         4.087\n",
      "2   [1, 0, 1, 1, 1, 0, 1, 0]  [0, 0, 0, 1]        0         4.541\n",
      "16  [0, 1, 1, 1, 0, 1, 1, 0]  [0, 0, 0, 1]        0         5.510\n",
      "                  data_index        answer  carries  solving_time\n",
      "37  [1, 0, 1, 0, 0, 1, 1, 0]  [0, 1, 0, 0]        1         3.415\n",
      "35  [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 0]        1         3.962\n",
      "12  [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         5.337\n",
      "15  [1, 1, 0, 0, 1, 0, 1, 0]  [0, 0, 1, 0]        1         6.823\n",
      "5   [1, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0]        1         6.993\n",
      "24  [0, 1, 0, 0, 0, 0, 1, 0]  [0, 0, 1, 0]        1         7.805\n",
      "0   [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1         8.087\n",
      "31  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1        10.695\n",
      "4   [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1        11.727\n",
      "                  data_index        answer  carries  solving_time\n",
      "22  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         5.759\n",
      "9   [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2         6.806\n",
      "36  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         7.274\n",
      "30  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         8.102\n",
      "20  [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2        10.039\n",
      "7   [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2        10.758\n",
      "28  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2        11.305\n",
      "19  [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2        13.820\n",
      "14  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2        15.728\n",
      "3   [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2        18.803\n",
      "                  data_index        answer  carries  solving_time\n",
      "33  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.930\n",
      "18  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         7.868\n",
      "26  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         8.868\n",
      "21  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         9.212\n",
      "27  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3        11.634\n",
      "29  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        14.460\n",
      "8   [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3        14.945\n",
      "39  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3        17.725\n",
      "10  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        18.116\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_27_31.68209_2000_1_4_MEDICINE.result\n",
      "carries\n",
      "0    2.8220\n",
      "1    5.1645\n",
      "2    6.3309\n",
      "3    7.7425\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     4.086850\n",
      "1     7.793951\n",
      "2     8.964025\n",
      "3    15.862574\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "28  [1, 1, 1, 1, 1, 1, 1, 1]  [0, 0, 0, 0]        0         2.072\n",
      "29  [1, 0, 0, 0, 0, 0, 0, 0]  [1, 0, 0, 0]        0         2.213\n",
      "27  [0, 1, 0, 0, 0, 1, 0, 0]  [0, 0, 0, 0]        0         2.541\n",
      "32  [1, 1, 0, 0, 0, 0, 0, 0]  [1, 1, 0, 0]        0         2.619\n",
      "21  [1, 1, 0, 1, 1, 0, 0, 0]  [0, 1, 0, 1]        0         2.697\n",
      "39  [1, 1, 1, 1, 0, 0, 1, 1]  [1, 1, 0, 0]        0         2.713\n",
      "18  [1, 1, 1, 0, 1, 0, 0, 0]  [0, 1, 1, 0]        0         2.774\n",
      "34  [0, 0, 0, 1, 0, 0, 0, 0]  [0, 0, 0, 1]        0         2.822\n",
      "6   [1, 1, 0, 1, 0, 1, 0, 1]  [1, 0, 0, 0]        0         3.525\n",
      "19  [0, 1, 1, 0, 0, 0, 1, 0]  [0, 1, 0, 0]        0         4.244\n",
      "                  data_index        answer  carries  solving_time\n",
      "8   [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         3.650\n",
      "24  [1, 1, 0, 1, 1, 0, 1, 1]  [0, 0, 1, 0]        1         3.915\n",
      "38  [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 0]        1         4.368\n",
      "12  [1, 0, 1, 0, 0, 1, 1, 0]  [0, 1, 0, 0]        1         4.447\n",
      "17  [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         4.509\n",
      "30  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         5.150\n",
      "9   [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1         5.165\n",
      "5   [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         5.783\n",
      "13  [1, 0, 1, 0, 1, 0, 0, 1]  [0, 0, 0, 1]        1         6.899\n",
      "3   [1, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0]        1         7.759\n",
      "                  data_index        answer  carries  solving_time\n",
      "15  [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         4.697\n",
      "16  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         4.854\n",
      "35  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         5.541\n",
      "22  [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2         5.587\n",
      "1   [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         5.806\n",
      "7   [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         6.088\n",
      "10  [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2         6.916\n",
      "0   [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         7.353\n",
      "33  [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2         7.681\n",
      "11  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         8.786\n",
      "                  data_index        answer  carries  solving_time\n",
      "26  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         3.431\n",
      "37  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         3.728\n",
      "36  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         4.509\n",
      "14  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         4.775\n",
      "2   [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         5.991\n",
      "25  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         8.524\n",
      "31  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         8.663\n",
      "20  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         9.352\n",
      "4   [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        12.961\n",
      "23  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3        15.491\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-03-28_18_18_17.93646_1994_1_4_COMPUTER SCIENCE.result\n",
      "carries\n",
      "0     2.158900\n",
      "1     3.259667\n",
      "2     5.403000\n",
      "3    12.021250\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     3.530101\n",
      "1     4.750941\n",
      "2    10.768498\n",
      "3    31.927572\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "4   [0, 0, 1, 1, 0, 0, 1, 0]  [0, 0, 0, 1]        0         1.457\n",
      "14  [1, 1, 0, 0, 1, 0, 0, 0]  [0, 1, 0, 0]        0         1.547\n",
      "38  [0, 0, 1, 1, 0, 0, 0, 0]  [0, 0, 1, 1]        0         1.547\n",
      "11  [1, 0, 0, 0, 0, 0, 0, 0]  [1, 0, 0, 0]        0         1.619\n",
      "30  [1, 0, 1, 1, 1, 0, 0, 0]  [0, 0, 1, 1]        0         1.953\n",
      "25  [0, 1, 1, 1, 0, 0, 0, 0]  [0, 1, 1, 1]        0         2.141\n",
      "21  [1, 1, 1, 1, 0, 0, 1, 1]  [1, 1, 0, 0]        0         2.255\n",
      "26  [1, 1, 0, 1, 0, 0, 0, 1]  [1, 1, 0, 0]        0         2.541\n",
      "0   [0, 1, 1, 0, 0, 1, 0, 0]  [0, 0, 1, 0]        0         3.099\n",
      "35  [1, 1, 0, 1, 0, 1, 0, 1]  [1, 0, 0, 0]        0         3.430\n",
      "                  data_index        answer  carries  solving_time\n",
      "37  [0, 1, 1, 0, 0, 1, 0, 1]  [0, 0, 0, 1]        1         2.141\n",
      "28  [1, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0]        1         2.406\n",
      "31  [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 0, 0]        1         2.630\n",
      "12  [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 0]        1         3.181\n",
      "13  [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1         3.381\n",
      "17  [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 1, 0]        1         3.472\n",
      "29  [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1         3.723\n",
      "8   [1, 1, 0, 0, 1, 0, 1, 0]  [0, 0, 1, 0]        1         4.111\n",
      "39  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         4.292\n",
      "                  data_index        answer  carries  solving_time\n",
      "22  [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2         3.421\n",
      "16  [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2         3.558\n",
      "15  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         3.846\n",
      "20  [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2         3.897\n",
      "18  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         4.078\n",
      "5   [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         5.454\n",
      "32  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         8.206\n",
      "7   [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2        10.764\n",
      "                  data_index        answer  carries  solving_time\n",
      "24  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         3.709\n",
      "33  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         4.318\n",
      "23  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         6.374\n",
      "1   [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         7.120\n",
      "36  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        11.501\n",
      "6   [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3        13.470\n",
      "10  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        15.401\n",
      "9   [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3        34.277\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-03-29_16_11_46.48906_1995_2_4_BIOLOGY.result\n",
      "carries\n",
      "0     6.4747\n",
      "1     7.3515\n",
      "2    12.6382\n",
      "3    12.3441\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0    11.238027\n",
      "1    14.076618\n",
      "2    21.956684\n",
      "3    23.748334\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "14  [0, 0, 1, 1, 0, 0, 0, 0]  [0, 0, 1, 1]        0         3.432\n",
      "32  [1, 1, 1, 0, 1, 1, 1, 0]  [0, 0, 0, 0]        0         3.468\n",
      "7   [1, 0, 0, 1, 1, 0, 0, 0]  [0, 0, 0, 1]        0         4.049\n",
      "0   [0, 1, 1, 1, 0, 0, 1, 0]  [0, 1, 0, 1]        0         6.068\n",
      "8   [1, 1, 1, 1, 1, 0, 1, 1]  [0, 1, 0, 0]        0         6.431\n",
      "1   [1, 0, 1, 1, 0, 0, 1, 0]  [1, 0, 0, 1]        0         6.636\n",
      "6   [1, 1, 1, 1, 1, 0, 0, 0]  [0, 1, 1, 1]        0         7.726\n",
      "39  [1, 1, 1, 1, 1, 0, 0, 1]  [0, 1, 1, 0]        0         7.780\n",
      "24  [1, 1, 0, 1, 0, 0, 0, 1]  [1, 1, 0, 0]        0         8.140\n",
      "5   [1, 1, 1, 1, 0, 1, 0, 0]  [1, 0, 1, 1]        0        11.017\n",
      "                  data_index        answer  carries  solving_time\n",
      "10  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         3.155\n",
      "30  [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 0, 0]        1         4.704\n",
      "11  [1, 1, 1, 0, 1, 1, 0, 1]  [0, 0, 0, 1]        1         4.732\n",
      "15  [1, 1, 0, 1, 1, 0, 1, 1]  [0, 0, 1, 0]        1         5.631\n",
      "12  [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1         8.450\n",
      "17  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         9.310\n",
      "38  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         9.593\n",
      "28  [1, 1, 0, 1, 0, 0, 1, 0]  [1, 0, 1, 1]        1        13.237\n",
      "                  data_index        answer  carries  solving_time\n",
      "20  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         7.670\n",
      "35  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         9.395\n",
      "13  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2        10.157\n",
      "37  [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2        10.286\n",
      "3   [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2        10.471\n",
      "23  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2        10.946\n",
      "31  [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2        12.117\n",
      "29  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2        13.630\n",
      "9   [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2        19.332\n",
      "2   [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2        22.378\n",
      "                  data_index        answer  carries  solving_time\n",
      "19  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.174\n",
      "36  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         5.763\n",
      "4   [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         7.195\n",
      "22  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         8.920\n",
      "25  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3        10.443\n",
      "34  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3        11.848\n",
      "21  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        17.429\n",
      "33  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3        17.919\n",
      "16  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3        19.324\n",
      "18  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        19.426\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-03-29_16_27_33.85448_1990_1_4_COMPUTER SCIENCE.result\n",
      "carries\n",
      "0    4.8701\n",
      "1    6.8918\n",
      "2    7.3003\n",
      "3    8.3960\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     8.952006\n",
      "1    14.938031\n",
      "2    13.302644\n",
      "3    19.692779\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "38  [1, 1, 1, 1, 1, 1, 1, 1]  [0, 0, 0, 0]        0         3.644\n",
      "18  [1, 0, 0, 1, 0, 0, 0, 0]  [1, 0, 0, 1]        0         3.891\n",
      "32  [1, 1, 1, 1, 0, 1, 1, 1]  [1, 0, 0, 0]        0         3.942\n",
      "31  [1, 0, 1, 1, 0, 0, 0, 0]  [1, 0, 1, 1]        0         3.953\n",
      "3   [1, 1, 1, 0, 1, 0, 0, 0]  [0, 1, 1, 0]        0         4.021\n",
      "35  [0, 1, 0, 0, 0, 1, 0, 0]  [0, 0, 0, 0]        0         4.215\n",
      "21  [0, 1, 1, 1, 0, 0, 0, 1]  [0, 1, 1, 0]        0         4.526\n",
      "1   [1, 0, 1, 1, 0, 0, 1, 0]  [1, 0, 0, 1]        0         4.755\n",
      "29  [1, 1, 1, 0, 0, 1, 0, 0]  [1, 0, 1, 0]        0         5.235\n",
      "7   [1, 1, 1, 1, 0, 0, 1, 1]  [1, 1, 0, 0]        0        10.519\n",
      "                  data_index        answer  carries  solving_time\n",
      "10  [0, 1, 0, 0, 0, 0, 1, 0]  [0, 0, 1, 0]        1         4.070\n",
      "14  [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         4.087\n",
      "28  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         4.681\n",
      "8   [1, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0]        1         4.913\n",
      "13  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         5.024\n",
      "19  [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 1, 0]        1         5.183\n",
      "30  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         5.793\n",
      "34  [0, 1, 1, 0, 0, 1, 0, 1]  [0, 0, 0, 1]        1         7.557\n",
      "5   [1, 0, 0, 1, 0, 1, 0, 1]  [0, 1, 0, 0]        1        10.856\n",
      "6   [1, 1, 0, 0, 1, 0, 1, 0]  [0, 0, 1, 0]        1        16.754\n",
      "                  data_index        answer  carries  solving_time\n",
      "12  [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         4.941\n",
      "33  [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         5.106\n",
      "9   [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2         5.145\n",
      "24  [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         5.454\n",
      "26  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         5.621\n",
      "15  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         6.729\n",
      "20  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         7.907\n",
      "23  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         8.561\n",
      "4   [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2         8.805\n",
      "0   [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2        14.734\n",
      "                  data_index        answer  carries  solving_time\n",
      "39  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         4.086\n",
      "27  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         5.656\n",
      "25  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         5.710\n",
      "37  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         5.967\n",
      "22  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         6.660\n",
      "17  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         7.578\n",
      "11  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         7.679\n",
      "36  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         7.902\n",
      "16  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         8.725\n",
      "2   [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3        23.997\n"
     ]
    },
    {
     "data": {
      "image/png": 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Jw8zMkjhxmJlZEicOMzNL4sRhZmZJnDjMzCyJE4eZmSVx4jAzsyROHGZmlsSJw8zMkjhxmJlZEicOMzNL4sRhZmZJnDjMzCyJE4eZmSVx4jAzsyROHGZmlsSJw8zMkpSaOCSdKmmtpKtr5v2npOsk/VbSdyVtXWYMZmZWrLJrHKcBi4fNuwhYEBHPB/4AfKTkGMzMrEClJo6IuARYN2zehRGxIZ/8FbBjmTGYmVmxpld8/H8CzhptoaSlwFKAtrY2+vv7JymsTTM4ONg0sTYTl2t5XLblaNVyrSxxSOoGNgDfGG2diFgOLAfo6OiIzs7OyQluE/X399MssTYTl2t5XLblaNVyrSRxSDoSeDVwUEREFTGYmdnE1N3Hocxhkj6RTz9T0gtTDyhpMXA08NqIeCh1ezMzq1ZK5/hXgAOAJfn0A8CXx9pA0krgl8AektZI6gJOAuYAF0m6UtL/pIdtZmZVSWmq2i8i9pZ0BUBE3CNp5lgbRMSSEWb3pgRoZmaNJaXG8aikaUAASNoO+FspUZmZWcNKSRwnAt8Fni6pB1gF/EcpUZmZWcOqu6kqIr4h6TLgIEDAIRExUFpkZmbWkFKH494B/CzfbnNJe0fE5cWHZWZmjaruxCHpU8CRwPXk/Rz5zwOLD8vMrLFJKnR/zXRJW0qN403ArhHxSFnBmJk1i3o+6Ocfcz43Hv+qSYhmcqV0jl8N+BboZmZTXEqN4zPAFfmzNR4emhkRry08KjMza1gpiWMFcALwO3z9hpnZlJWSOB6KiBNLi8TMzJpCSuL4maTPAOfyxKYqD8c1M5tCUhLHXvnP/WvmeTiumdkUk3Ll+KIyAzEzs+YwbuKQdFhEnCHpAyMtj4jPFx+WmZk1qnpqHLPyn3NGWNY8lzqamVkhxk0cEXFy/vbHEfHz2mWSXlxKVGZm1rBSrhz/Up3zzMyshdXTx3EA8CJgu2H9HFsC08oKzMzMGlM9fRwzgdn5urX9HPcDbywjKDMza1z19HFcDFws6bSIuGm09SR9KSKWFRqdmZk1nLr7OMZKGrkndZRLOlXS2vzGiEPztpV0kaQ/5j+3SYjXzMwqltI5PhGnAYuHzTsG+ElE7Ab8JJ82M7MmUWriiIhLgHXDZh9Mdqdd8p+HlBmDmZkVq8jEUe9zFNsi4vb8/V+AtgJjMDOzkqXc5HA8X0zdICJC0qhXn0taCiwFaGtro7+/f+LRTaLBwcGmibWZuFzL47ItTyuWa92JQ9IPePItRu4DVgMnR8Rpde7qDknzIuJ2SfOAtaOtGBHLgeUAHR0d0dnZWW+4lerv76dZYm0mLtfyuGxLcsH5LVmuKU1VNwCDwCn5637gAWD3fLpe5wJH5O+PAL6fsK2ZmVUspanqRRGxb830DyT9JiL2lXTNSBtIWgl0AnMlrQGOBY4HzpbUBdwEvGlioZvZeKR6ux7rF+F7m051KYljtqRnRsTNAJKeSXZFOcAjI20QEUtG2ddBCcc1swmq90N+/jHnc+Pxryo5GmsVKYnjg8AqSdeTjaDaBfhnSbN4fHitmZm1uJQnAP5Q0m7A/8tn/T4i/pq//0LhkZmZWUNKHY67DzA/3+4FkoiI0wuPyszMGlbKcNyvA7sCVwIb89kBOHGYmU0hKTWODuA54SEVZmZTWsp1HFcDzygrEDMzaw4pNY65wLWSfg08PDQzIl5beFRmZtawUhLHcWUFYWZmzSNlOO7FZQZiZmbNYdzEIWlVRCyU9ABPvMmhyG5wu2Vp0ZmZWcOp55njC/Ofc8oPx8zMGl3do6oknSjpgDKDMTOzxpfSOX4Z8HFJewDfBc6MiNXlhGVmVo0XfPJC7lv/aGH7m3/M+YXta6vNZ3DVsS8vbH8TldI5vgJYIWlb4A3ACfndcncrLTozs0l23/pHC7tTcNEPyCoyCW2KiTxz/NlkNzrcGbiu2HDMzKzRpfRxfFbSH4F/J7uKvCMiXlNaZGZm1pBS+jiuBw6IiLvKCsbMzBpfPddx7J2//Q3wzPzJf4+JiMvLCMzMzBpTPTWO/xpjWQAHFhSL2YhWrlxJT08PAwMDtLe3093dzZIloz2V2MzKVs8FgIsmIxCzkaxcuZLu7m56e3vZuHEj06ZNo6urC8DJw6wiKQ9ymgG8B3hpPqsfODkiihvwbDZMT08Pvb29LFq06LGhjb29vSxbtmxKJ46irzWA4oZ6Nsq1BlaelM7xrwIzgK/k04fn894xkQNL+td82wB+B7y95hnmZgAMDAywcOHCJ8xbuHAhAwMDFUXUGIq81gCKvd6gUa41sPKkXMexb0QcERE/zV9vB/adyEEl7QD8C9mQ3gXANOAtE9mXtbb29nZWrVr1hHmrVq2ivb29oojMLCVxbJS069CEpGfx+LPHJ2I6sLmk6cAWwG2bsC9rUd3d3XR1ddHX18eGDRvo6+ujq6uL7u7uqkMzm7JSmqr+DeiTdEM+PR94+0QOGhG3SvoccDOwHrgwIi6cyL6stQ31YyxbtuyxUVU9PT1Tun/DrGopieNpwAKyhHEIcABw30QOKmkb4GBgF+Be4FuSDouIM4attxRYCtDW1kZ/f/9EDjfpBgcHmybWZjBv3jxOOukkBgcHmT17NoDLl2LLoOi/2Wb//RQVfxmfBQ1RthFR1wv4bf5zIdAHvAq4tN7th+3rUKC3ZvptwFfG2mafffaJZtHX11d1CC3J5fq4nT98XqH7K7Jsi45tshUZf9F/s2WWLbA66vwMT+rjyH++CjglIs4HZk4wX90M7C9pC0kCDgKm9jAZM7MmkdJUdaukk4G/J7ul+mZM7O66RMSlks4BLgc2AFcAyyeyL7OpaE77MTxvxTHF7nRFMbuZ0w7Z90trVSmJ403AYuBzEXGvpHnAhyZ64Ig4Fjh2otubTWUPDBzv6zisMikPcnoI+E7N9O3A7WUEZWZmjWtCTU1mZjZ1pTRVmZm1vML7jwrqO4LG6T9y4jAzq1Fk/5GfOW5mZoYTh5mZJXLiMDOzJO7jMGtShbd3X1Dcg5ystTlxmDWhIi/+gywJFb1Pa11uqjIzsyROHGZmlsSJw8zMkjhxmJlZEicOMzNL4lFV1hCy53kVJ3ugmZmVwTUOawj1PK5y5w+fl/J4YjMriROHmZklceIwM7MkThxmZpbEicPMzJI4cZiZWZLKEoekrSWdI+k6SQOSDqgqFjMzq1+V13F8EbggIt4oaSawRYWxmJlZnSpJHJK2Al4KHAkQEY8Aj1QRi5mZpamqxrELcCfwNUkvAC4DjoqIB2tXkrQUWArQ1tZGf3//ZMc5IYODg00Ta7NxuaZZtGhR3evqhPrW6+vrm2A0zaPQh2QV9IAsgFkzGuN/QFVcZSupA/gV8OKIuFTSF4H7I+Ljo23T0dERq1evnrQYN0V/fz+dnZ1Vh9Fy/LCh8vhvthzN9Dcr6bKI6Khn3ao6x9cAayLi0nz6HGDvimIxM7MElTRVRcRfJN0iaY+I+D1wEHBtFbFYuV7wyQu5b/2jhe2vyCaErTafwVXHvryw/ZlNFVWOqloGfCMfUXUD8PYKY7GS3Lf+0cKq6kU3pxTajm02hVSWOCLiSqCu9rRGUfStv8G3/zaz5uMrxxPUe0tv3/7bzFqZE4eZmSVx4jAzsyROHGZmlsSJw8zMkjhxmJlZEicOMzNL4sRhZmZJnDjMzCyJE4eZmSWp8l5VDaVRb8bnG/GZWaNx4sg16s34mv1GfHPaj+F5K44pbocritvVnHaA5nhWglkjceKwUj0wcHxDJmRo/qRsVhX3cZiZWRInDjMzS+LEYWZmSdzHYaUrtC/hgmIfHWtm6Zw4rFRFdYxDloCK3J/Zpqj3iaA6ob79NdOD3dxUZWY2AfU84bOvr68lnwbqGoc1hKn87c2s2bjGYQ1hKn97M2s2lSYOSdMkXSHpvCrjMDOz+lVd4zgKGKg4BjMzS1BZH4ekHcluFNQDfKCqOIY06j2VfD8lM2s0VXaOfwE4Gpgz2gqSlgJLAdra2ujv7y8tmAcGjue0xbMK2dfg4CCzZ88uZF9HXvBgqefdTAYHB10WJXHZlqNVy7WSxCHp1cDaiLhMUudo60XEcmA5QEdHRxR5g7snueD8wm6gV+jN+AqMq9kVfZNDe5zLthytWq5V9XG8GHitpBuBM4EDJZ1RUSxmZpagksQRER+JiB0jYj7wFuCnEXFYFbGYmVmaqkdVmZlZk6n8yvGI6Af6Kw7DzMzq5BqHmZklqbzG0Uga8fbfvvW3mTUaJ46cb/9tZlYfN1WZmVkSJw4zM0vipqoE9T4zAvzcCDNrXa5xJKj3WRB+boSZtTInDjMzS+LEYWZmSZw4zMwsiROHmZklceIwM7MkThxmZpbEicPMzJI4cZiZWRI1y0Voku4Ebqo6jjrNBe6qOogW5HItj8u2HM1UrjtHxHb1rNg0iaOZSFodER1Vx9FqXK7lcdmWo1XL1U1VZmaWxInDzMySOHGUY3nVAbQol2t5XLblaMlydR+HmZklcY3DzMySOHEUTNJiSb+X9CdJx1QdTyuQdKqktZKurjqWViJpJ0l9kq6VdI2ko6qOqVVIeqqkX0u6Ki/bT1YdU5HcVFUgSdOAPwB/D6wBfgMsiYhrKw2syUl6KTAInB4RC6qOp1VImgfMi4jLJc0BLgMO8d/rplP2uNBZETEoaQawCjgqIn5VcWiFcI2jWC8E/hQRN0TEI8CZwMEVx9T0IuISYF3VcbSaiLg9Ii7P3z8ADAA7VBtVa4jMYD45I3+1zLd0J45i7QDcUjO9Bv8jWhOQNB/YC7i02khah6Rpkq4E1gIXRUTLlK0Th9kUJ2k28G3g/RFxf9XxtIqI2BgRewI7Ai+U1DLNrE4cxboV2Klmesd8nllDytvfvw18IyK+U3U8rSgi7gX6gMVVx1IUJ45i/QbYTdIukmYCbwHOrTgmsxHlHbi9wEBEfL7qeFqJpO0kbZ2/35xswMx11UZVHCeOAkXEBuB9wI/IOhrPjohrqo2q+UlaCfwS2EPSGkldVcfUIl4MHA4cKOnK/PXKqoNqEfOAPkm/JftCeVFEnFdxTIXxcFwzM0viGoeZmSVx4jAzsyROHGZmlsSJw8zMkjhxmJlZEicOs5JJ2l7SOVXHYVYUD8c1K5Ck6fn1PCNOm7UCJw6zUUh6G/BvZHc1/S1wNvAxYCZwN/DWiLhD0nHArsCzgJvJLgB9PTAbmAYcAZwXEQvyW+8fD3QCmwFfjoiT81ucnwVsCUwH3hMRP5ukUzVLMr3qAMwakaTnkiWJF0XEXZK2JUsg+0dESHoHcDTwwXyT5wALI2K9pCOBvYHnR8S6/M6zQ7qA+yJiX0mbAT+XdCFZovlRRPTkyWWLSThNswlx4jAb2YHAtyLiLoA8ATwPOCuvHcwE/lyz/rkRsb5m+qKIGOkZIi8Hni/pjfn0VsBuZLelODW/6eD3IuLKgs/HrDDuHDer35eAkyLiecC7gKfWLHtw2LrDp4cIWBYRe+avXSLiwvxhVS8lu5vyaXkzmVlDcuIwG9lPgUMlPQ0gb6raisdvk3/EBPf7I+A9ec0CSbtLmiVpZ+COiDgF+F+ypi6zhuSmKrMRRMQ1knqAiyVtBK4AjgO+JekessSyywR2/b/AfODy/LbmdwKHkHWWf0jSo2TPV3eNwxqWR1WZmVkSN1WZmVkSJw4zM0vixGFmZkmcOMzMLIkTh5mZJXHiMDOzJE4cZmaWxInDzMyS/H9suvx9shQ94AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-01_13_19_46.19309_1998_2_3_PSYCHOLOGY.result\n",
      "carries\n",
      "0    4.2655\n",
      "1    5.4012\n",
      "2    8.5170\n",
      "3    7.6995\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     6.053498\n",
      "1     7.920993\n",
      "2    14.503134\n",
      "3    12.101849\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "39  [1, 1, 0, 1, 1, 1, 0, 0]  [0, 0, 0, 1]        0         3.275\n",
      "14  [1, 0, 0, 1, 1, 0, 0, 1]  [0, 0, 0, 0]        0         3.338\n",
      "19  [1, 1, 1, 0, 1, 0, 0, 0]  [0, 1, 1, 0]        0         3.510\n",
      "32  [1, 1, 1, 1, 1, 1, 0, 0]  [0, 0, 1, 1]        0         3.618\n",
      "15  [1, 0, 0, 1, 0, 0, 0, 0]  [1, 0, 0, 1]        0         4.055\n",
      "26  [1, 0, 1, 1, 0, 0, 0, 0]  [1, 0, 1, 1]        0         4.150\n",
      "24  [0, 1, 0, 1, 0, 0, 0, 1]  [0, 1, 0, 0]        0         4.384\n",
      "30  [1, 1, 1, 0, 1, 1, 0, 0]  [0, 0, 1, 0]        0         5.150\n",
      "5   [1, 0, 0, 0, 0, 0, 0, 0]  [1, 0, 0, 0]        0         5.509\n",
      "7   [1, 1, 1, 1, 1, 0, 0, 0]  [0, 1, 1, 1]        0         5.666\n",
      "                  data_index        answer  carries  solving_time\n",
      "2   [1, 0, 1, 0, 1, 0, 0, 1]  [0, 0, 0, 1]        1         4.353\n",
      "34  [1, 1, 0, 1, 0, 0, 1, 1]  [1, 0, 1, 0]        1         4.381\n",
      "36  [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         4.525\n",
      "27  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         4.744\n",
      "9   [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         4.826\n",
      "11  [1, 0, 1, 1, 0, 1, 1, 1]  [0, 1, 0, 0]        1         5.009\n",
      "18  [0, 1, 0, 1, 0, 0, 1, 0]  [0, 0, 1, 1]        1         5.149\n",
      "8   [1, 1, 1, 0, 0, 0, 0, 1]  [1, 1, 0, 1]        1         6.024\n",
      "29  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         6.727\n",
      "16  [1, 0, 1, 0, 0, 1, 0, 0]  [0, 1, 1, 0]        1         8.274\n",
      "                  data_index        answer  carries  solving_time\n",
      "20  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         6.023\n",
      "4   [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         6.462\n",
      "17  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         7.149\n",
      "10  [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2         7.213\n",
      "12  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         7.535\n",
      "0   [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2         7.978\n",
      "6   [1, 0, 0, 1, 0, 1, 1, 1]  [0, 0, 1, 0]        2         8.181\n",
      "1   [1, 0, 0, 0, 0, 1, 1, 0]  [0, 0, 1, 0]        2         8.322\n",
      "21  [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2         9.821\n",
      "25  [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2        16.486\n",
      "                  data_index        answer  carries  solving_time\n",
      "22  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         4.494\n",
      "35  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.759\n",
      "33  [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         5.993\n",
      "23  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         6.134\n",
      "38  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         7.199\n",
      "31  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         7.871\n",
      "28  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         8.789\n",
      "37  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         8.881\n",
      "13  [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3        10.507\n",
      "3   [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3        11.368\n"
     ]
    },
    {
     "data": {
      "image/png": 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ckqROhk4cabwgyV+2yw9M8lOjC02SNIm6nHG8A9gHOKBdvgX4p94jkiRNtM077Lt3Ve2Z5ByAqrohyRYjikuSNKG6nHHcmWQzoACS3B/4wUiikiRNrC6J463AJ4CfSHIocDrwtyOJSpI0sYZuqqqqDyQ5C9gPCPCsqrpwZJFJkiZSlz4OgKuB/2pft1WSPavq7P7DkiRNqqETR5K/Bg4CLqbt52h/7tt/WJKkSdXljOO5wEOq6o5RBSNJmnxdOsfPB7bv68BJ/iTJBUnOT/KhJPfuq2xJ0uh0OeN4I3BOkvOB782trKpndD1okp2BPwIeUVW3JzkWeB5wVNeyJEmbVpfEcTRwOPA/9HP9xlwH+53A1sCVPZQpSRqxLonjtqp6ax8HrapvJ3kT8C3gduCkqjpp/n5JDgYOBli9ejUzMzN9HH7kZmdnpybWaWK9jo51e0991cUo6nUSfk9dEsd/JXkjcBz3bKrqPBw3yX2AZwIPAm4EPpLkBVX1/sH9qupI4EiAtWvX1rp167oeaixmZmaYllinifU6OtbtgBNP6K0ueq/XHmPbGF0Sx+Pan08YWLfU4bhPAb5ZVdcCJPk48NPA+xd9lSRp7LpcOf7kHo/7LeAJSbamaaraDzizx/IlSSOywcQx14SU5OULba+qf+x60Ko6I8lHgbOB7wPn0DZJSZIm2zBnHNu0P1ctsK0WWDeUqnod8Lqlvl6SNB4bTBxVdUT79NNV9bnBbUl+ZiRRSZImVpcrx9825DpJ0jI2TB/HPjQjnu4/r59jW2CzUQUmSZpMw/RxbAGsbPcd7Oe4GXj2KIKSJE2uYfo4TgVOTXJUVV22vv2SvK2qXtprdJKkiTN0H8diSaNlR7kk/Rjo0jkuSZKJQ5LUTZ+JIz2WJUmaUH0mjrf0WJYkaUINPclhkn/nR6cYuYlmcsIjquqoHuOSJE2oLmcclwCzwDvbx83ALcDD2mVJ0o+BLvfj+Omq2mtg+d+TfKmq9kpyQd+BSZImU5czjpVJHji30D5f2S7e0WtUkqSJ1eWM4xXA6UkuphlB9SDg95NsAxw9iuAkSZOnyx0A/yPJQ4H/1676alV9t33+5t4jkyRNpC5nHACPB9a0r3tMEqrqvb1HJUmaWF2G474PeAhwLnBXu7oAE4c0oZL+r8utWvKNP7VMdDnjWAs8ovyrkabGsP+uaw45gUsPe9qIo9Fy0WVU1fnAA0YViCRpOnQ549gB+EqS/wa+N7eyqp7Re1SSpInVJXG8flRBSJKmR5fhuKeOMhBJ0nTYYOJIcnpVPTHJLdxzksMAVVXbjiw6SdLEGeae409sf64afTiSpEk39KiqJG9Nss8og5EkTb4uw3HPAl6b5OIkb0qydlRBSZIm19CJo6qOrqqnAnsBXwUOT/L1kUUmSZpIS7l17E/STHS4G3BRv+FIkiZdlz6Ov2vPMP6K5irytVX1yyOLTJI0kbpcAHgxsE9VXTeqYCRJk2+Y6zj2bJ9+CXjg4F0AAarq7FEEJkmaTMOccfzDItsK2HcpB06yPfAuYI+2nN+uqi8spSxJ0qYzzAWATx7Rsd8CnFhVz06yBbD1iI4jSepRlxs5rQBeAjypXTUDHFFVd3Y9aJLt2nIOAqiqO4A7upYjSdr0ugzH/WeaW8e+o308vl23FA8CrgX+Nck5Sd6VZJslliVJ2oS6jKraq6oeM7D82STnbcRx9wReWlVnJHkLcAjw2sGdkhwMHAywevVqZmZmlni4TWt2dnZqYp0m1utoWbc/1FddjOJvdhJ+T10Sx11JHlJVFwMkeTA/vPd4V1cAV1TVGe3yR2kSxz1U1ZHAkQBr166tdevWLfFwm9bMzAzTEus0sV5H6MQTrNs5PdZF73+zE/J76pI4/hQ4Jckl7fIa4LeWctCq+t8klyfZvaq+CuwHfGUpZUmSNq0uieN+NENn1wDPAvYBbtqIY78U+EA7ouoSlpiEJEmbVpfE8dqq+kiSbYEnA2+i6RzfeykHrqpzAWfYlaQp02VU1Vx/xtOAd1bVCcAW/YckSZpkXc44vp3kCODnaaZU35Klza4rSRNr1cMP4VFH/8hYnaU7ur+iVj0cmu/u49UlcTwX2B94U1XdmGRH4M9GE5YkjcctFx7GpYf18+Hc96iqNYec0FtZG2PoxFFVtwEfH1i+CrhqFEFJkiaXTU2SpE66NFVJ0o+FXpuETuyvrO22WtFbWRvDxCFJA/rq34AmAfVZ3qSwqUqS1IlnHJoISXotr6p6LW/SPOYNJ3HT7Z3vaLCovppntttqBee97hd6KUuTycShiTDMB/1yPe1fiptuv7PXuuhz2OikDBnV6NhUJUnqxMQhSerExCFJ6sQ+DklagmEHdOTw4cqbpgEdnnFI0hJU1QYfp5xyylD7TVPSABOHJKkjE4ckqRMThySpExOHJKkTE4ckqROH40pTqPfbm0JvtzidlNubanRMHNIU6vP2puBcVerGpipJUicmDklSJyYOSVInJg5JUicmDklSJ46q0kj1fYvTPkfseItTaWlMHBqpPm9x2ueQUXDYqLRUNlVJkjoxcUiSOjFxSJI6GWviSLJZknOSHD/OOCRJwxt35/jLgAuBbccchzR1eu/cP7Gf8rbbakUv5WhyjS1xJNmFZgrNQ4GXjysOaRr1OcEhNEmo7zK1fI2zqerNwCuBH4wxBklSR2M540jydOCaqjorybpF9jsYOBhg9erVzMzMbJoAN9Ls7OzUxLop9FUXo6hXf08/ZF30b7l+FoyrqepngGckeSpwb2DbJO+vqhcM7lRVRwJHAqxdu7b6vPhrKZL0XmZV9V7mRDnxhN4u2uv7AsA+Y5t61sVI9P43OyHG0lRVVa+uql2qag3wPOCz85PGJKqqoR67ver4ofeVpGkz7lFVWuZ6v8VpT7c3BW9xKi3V2BNHVc0AM2MOQyPS5y1OnatKmgxeOS5J6sTEIUnqxMQhSepk7H0ck2JSbzjkzYa0MboMIc/hw+3naECZOFqTesMhO3C1MYb9kF+u1xtoNGyqkiR14hmHRq7Xs6aeZnAFZ3GVlsrEoZHqc8ZVZ3CVJoOJozWpVzh7dbOkSWPiaE3qFc4/Lp3jw47+ceSPNH52jmsiDDMh5CmnnOLkkdIEMHFIkjoxcUiSOjFxSJI6MXFIkjoxcUiSOjFxSJI6MXFIkjoxcUiSOjFxSJI6MXFIkjpxrqoBkzj9t1N/S5o0Jo6W039L0nBsqpIkdWLikCR1YuKQJHVi4pAkdWLneAfD3qUOvFOdpOXLM44Ohr37nHeqk7ScmTgkSZ2YOCRJnZg4JEmdmDgkSZ2MJXEk2TXJKUm+kuSCJC8bRxySpO7GNRz3+8ArqursJKuAs5KcXFVfGVM8kqQhjeWMo6quqqqz2+e3ABcCO48jFklSNxn3tQRJ1gCnAXtU1c3zth0MHAywevXqxx9zzDGbPL6lmJ2dZeXKleMOY9mxXkfHuh2NaarXJz/5yWdV1dph9h1r4kiyEjgVOLSqPr6Bfa8FLtskgW28HYDrxh3EMmS9jo51OxrTVK+7VdX9h9lxbIkjyQrgeOBTVfWPYwliRJKcOWzm1vCs19GxbkdjudbruEZVBXg3cOFySxqStNyN6zqOnwFeCOyb5Nz28dQxxSJJ6mAsw3Gr6nRg+Klmp8+R4w5gmbJeR8e6HY1lWa9jH1UlSZouTjkiSerExNGzJPsn+WqSbyQ5ZNzxLAdJ3pPkmiTnjzuW5cSpf0Ynyb2T/HeS89q6fcO4Y+qTTVU9SrIZ8DXg54ErgC8BBziVysZJ8iRgFnhvVe0x7niWiyQ7AjsOTv0DPMu/143Xjhzdpqpm20sPTgdeVlVfHHNovfCMo18/BXyjqi6pqjuAY4BnjjmmqVdVpwHXjzuO5capf0anGrPt4or2sWy+pZs4+rUzcPnA8hX4j6gp0E798zjgjPFGsnwk2SzJucA1wMlVtWzq1sQh/Zhrp/75GPDH8+eL09JV1V1V9VhgF+CnkiybZlYTR7++Dew6sLxLu06aSG37+8eAD2xovjgtTVXdCJwC7D/uWPpi4ujXl4CHJnlQki2A5wHHjTkmaUFO/TM6Se6fZPv2+VY0A2YuGm9U/TFx9Kiqvg/8IfApmo7GY6vqgvFGNf2SfAj4ArB7kiuSvGjcMS0TTv0zOjsCpyT5Ms0XypOr6vgxx9Qbh+NKkjrxjEOS1ImJQ5LUiYlDktSJiUOS1ImJQ5LUiYlDGrEkOyX56LjjkPricFypR0k2b6/nWXBZWg5MHNJ6JPlN4E9pZjX9MnAs8BpgC+A7wPOr6uokrwceAjwY+BbNBaC/CqwENgMOBI6vqj3aqfcPA9YBWwL/VFVHtFOcfxjYluaWzi+pqv/aRG9V6mQs9xyXJl2SR9IkiZ+uquuS3JcmgTyhqirJ7wCvBF7RvuQRwBOr6vYkBwF7Ao+uquvbmWfnvAi4qar2SrIl8LkkJ9Ekmk9V1aFtctl6E7xNaUlMHNLC9gU+UlXXAbQJ4FHAh9uzgy2Abw7sf1xV3T6wfHJVLXQPkV8AHp3k2e3ydsBDaaaleE876eAnq+rcnt+P1Bs7x6XhvQ14e1U9Cvhd4N4D226dt+/85TkBXlpVj20fD6qqk9qbVT2JZjblo9pmMmkimTikhX0WeE6S+wG0TVXb8cNp8g9cYrmfAl7SnlmQ5GFJtkmyG3B1Vb0TeBdNU5c0kWyqkhZQVRckORQ4NcldwDnA64GPJLmBJrE8aAlFvwtYA5zdTmt+LfAsms7yP0tyJ8391T3j0MRyVJUkqRObqiRJnZg4JEmdmDgkSZ2YOCRJnZg4JEmdmDgkSZ2YOCRJnZg4JEmd/B8SCVmxCCF4NwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_07_03.71068_1998_2_3_HUMANITIES.result\n",
      "carries\n",
      "0    3.228100\n",
      "1    4.013667\n",
      "2    4.959500\n",
      "3    7.594143\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     4.320566\n",
      "1     5.423678\n",
      "2     7.259454\n",
      "3    13.210697\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "22  [1, 1, 1, 1, 0, 0, 0, 0]  [1, 1, 1, 1]        0         2.447\n",
      "2   [1, 1, 1, 1, 1, 0, 0, 0]  [0, 1, 1, 1]        0         2.479\n",
      "17  [1, 0, 0, 0, 0, 0, 0, 0]  [1, 0, 0, 0]        0         2.666\n",
      "6   [1, 1, 1, 1, 1, 1, 1, 1]  [0, 0, 0, 0]        0         2.995\n",
      "18  [1, 1, 1, 1, 1, 1, 1, 0]  [0, 0, 0, 1]        0         3.336\n",
      "10  [0, 0, 1, 0, 0, 0, 1, 0]  [0, 0, 0, 0]        0         3.416\n",
      "16  [1, 0, 1, 0, 1, 0, 0, 0]  [0, 0, 1, 0]        0         3.602\n",
      "3   [0, 1, 1, 0, 0, 1, 0, 0]  [0, 0, 1, 0]        0         3.635\n",
      "11  [0, 1, 1, 1, 0, 1, 1, 0]  [0, 0, 0, 1]        0         3.776\n",
      "37  [1, 1, 1, 1, 1, 0, 1, 0]  [0, 1, 0, 1]        0         3.929\n",
      "                  data_index        answer  carries  solving_time\n",
      "15  [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         3.305\n",
      "31  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         3.306\n",
      "34  [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         3.447\n",
      "25  [0, 1, 1, 0, 0, 1, 0, 1]  [0, 0, 0, 1]        1         3.619\n",
      "24  [1, 0, 1, 1, 0, 1, 1, 0]  [0, 1, 0, 1]        1         3.873\n",
      "1   [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         4.041\n",
      "7   [1, 1, 1, 0, 1, 0, 0, 1]  [0, 1, 0, 1]        1         4.451\n",
      "26  [1, 1, 1, 0, 0, 1, 0, 1]  [1, 0, 0, 1]        1         4.744\n",
      "27  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         5.337\n",
      "                  data_index        answer  carries  solving_time\n",
      "23  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2         3.603\n",
      "38  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         3.697\n",
      "12  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         3.978\n",
      "19  [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2         4.587\n",
      "39  [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         4.715\n",
      "30  [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         4.806\n",
      "0   [1, 1, 0, 0, 0, 0, 0, 1]  [1, 0, 1, 1]        2         5.134\n",
      "13  [1, 1, 1, 0, 0, 0, 1, 1]  [1, 0, 1, 1]        2         5.400\n",
      "5   [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2         6.791\n",
      "29  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         6.884\n",
      "                  data_index        answer  carries  solving_time\n",
      "32  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         5.103\n",
      "35  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         5.325\n",
      "14  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         5.650\n",
      "8   [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         5.666\n",
      "36  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         9.305\n",
      "33  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        10.165\n",
      "21  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        11.945\n"
     ]
    },
    {
     "data": {
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Wr2Dd6ceVHE1rWL9hY2FtUfQU8iKT0FRU0lUlaS5Z0ngucDDwMklPryIWMzPLp6oxjk7gioh4JCIeAy4DXlVRLGZmlkNVXVVrgT5JuwEbgJcCa0YXkrQQWAjQ0dHB4ODgloyxYcPDwy0Taytxu5bLbfu4otqijL/ZZvicKkkcETEk6QxgFfAwcDWwaYxyS4GlAF1dXdEql5vwpTHK4XYt0coVbtsRBbZF4X+zTfI5VTYdNyKWRcThEfEC4H7gt1XFYmZm9atyVtWTI+IuSU8hG984qqpYzMysflWex/H1NMaxEXh7RDxQYSxmZlanyhJHRDy/qn2bmVnjfMkRMzPLxYnDzMxyceIwM7NcnDjMzCwXJw4zM8vFicPMzHJx4jAzs1ycOMzMLBcnDjMzy8WJw8zMcnHiMDOzXJw4zMwsFycOMzPLpcrLqpuZNZ3ZnYs5aPni4ipcXlxVszsBjiuuwgbVnTgkCXg98NSI+M90A6Y9I+IXpUVnZraFPTR0OutOL+bLuehbx85ZvKKwuqYiT1fV54CjgZ60/BDw2cIjMjOzppYncRwZEW8H/gQQEfcD2za6Y0n/JulaSWsl9Ut6UqN1mZnZlpMncWyUNA0IAEl7AH9pZKeS9gH+FeiKiLnANOB1jdRlZmZbVp7EcSZwMfBkSX3AauC/prDv6cD2kqYDOwC3T6EuMzPbQuoeHI+Ir0q6ElgACDg+IoYa2WlE3Cbp48DNwAZgVUSsaqQuMzPbsvJOx70T+DGPHy0cFhFX5d2ppF2AVwAHAA8AX5P0hoj4yqhyC4GFAB0dHQwODubdVSWGh4dbJtZW4nYtl9v2cUW1RRl/s83wOeWZjvth4CTgBtI4R/r3mAb2+0LgDxFxd6r7G8DzgCckjohYCiwF6OrqiiKntZWp6Cl4lnG7lmjlCrftiALbovC/2Sb5nPIccbwGeFpEPFrAfm8GjpK0A1lX1QJgTQH1mplZyfIMjq8Fdi5ipxFxBXARcBXwPymOpUXUbWZm5cpzxPFR4FeS1gJ/HlkZES9vZMcRcSpwaiOvNTOz6uRJHMuBM8iOEBo6f8PMzFpfnsTxSEScWVokZmbWEvIkjh9L+ihwCU/sqso9HdfMzFpXnsRxaPr3qJp1jU7HNTOzFpXnzPHuMgMxM7PWMGniGDmjW9K7xtoeEZ8oPiwzM2tW9RxxzEz/zh5jW4yxzszM2tikiSMizkpPfxARP6ndJulvSonKzMyaVp4zxz9d5zozM2tj9YxxHE12AcI9Ro1z7Eh2AyYzM9uK1DPGsS0wK5WtHed4EHh1GUGZmVnzqmeM4zLgMknnRMRN45WT9OmIWFRodGZm1nTynMcxbtJIPFButoUc/KFVrN+wsdA65yxeUUg9O20/g2tOfXEhdVlzynsHQDNrAus3bGTd6ccVVl+RNxwqKgFZ88ozq8rMzKzQxKEC6zIzsyZVZOL4VL0FJR0o6eqax4OS3llgLGZmVpK6xzgkfZu/vsTIerJ7hZ8VEefUW1dE/AY4JNU7DbgNuLje15uZWXXyHHHcCAwDZ6fHg8BDwDPTcqMWADfUMWvLzMyaQJ5ZVc+LiCNqlr8t6ZcRcYSka6cQw+uA/im83sysUIXODFtZXF07bT+jsLqmIk/imCXpKRFxM4Ckp5CdUQ7waCM7l7Qt8HLgfeNsXwgsBOjo6GBwcLCR3Wxxw8PDLRNrK3G7PlGRbVF027by53TOsTMnL1Snk1Y+XGh90BxtmydxvBtYLekGshlUBwD/ImkmsLzB/b8EuCoi7hxrY0QsBZYCdHV1RVHzzMtW5Jx4e5zbtcbKFYW2RaFtW3BsLa1N2yLPmePfkfQM4H+lVb+JiD+l559scP89uJvKzKyl5D1z/HBgTnrdwZKIiHMb2XE6UnkR8JZGXm9mZtWoe1aVpC8DHwfmAUekR1ejO46IhyNit4hY32gdzaa/v5+5c+eyYMEC5s6dS3+/D6bMrP3kOeLoAp4VEb5d7Bj6+/tZsmQJy5YtY9OmTUybNo3e3l4Aenp6Ko7OzKw4ec7jWAvsWVYgra6vr49ly5bR3d3N9OnT6e7uZtmyZfT19VUdmplZofIccewOXCfpF8CfR1ZGxMsLj6oFDQ0NMW/evCesmzdvHkNDQxVFZGZWjjyJ47SygmgHnZ2drF69mu7u7s3rVq9eTWdnZ4VRmZkVL8903MvKDKTVLVmyhN7e3s1jHAMDA/T29rqryszazqSJQ9LqiJgn6SGeeJFDARERO5YWXQsZGQBftGgRQ0NDdHZ20tfX54FxM2s79dxzfF76d3b54bS2np4eenp6fIazmbW1POdxnCnp6DKDMTOz5pdnOu6VwAcl3SDp45IaPvnPzMxaV92JIyKWR8RLyc4Y/w1whqTflRaZmZk1pbzXqgJ4OtmFDvcHfJKCFUIq9pb1vsCBWXny3Dr2Y8ArgRuAC4APR8QDZQVmW5d6vujnLF7ButOP2wLRNL/ZnYs5aPniYitt9OYIo8zuBPDn1M7yHHHcABwdEfeUFYyZ1eehodMLTaJFzgQs9O551pTqOY/jsPT0l8BT0p3/NouIq8oIzMzMmlM9Rxz/PcG2AI4pKBYzM2sB9ZwA2D1ZGTMz23rkGRyfAbwNeEFaNQicFREbS4jLzMyaVJ4TAD9PduvYz6XH4WldQyTtLOkiSddLGvJZ6WZmrSHPrKojIuLgmuUfSbpmCvv+FLAyIl4taVtghynUZWZmW0iexLFJ0tMi4gYASU8FNjWyU0k7kXV5nQQQEY8CjzZSl5lZFeo9aVVn1FdfK520midx/DswIOnGtDwH+OcG93sAcDfwJUkHk10H6+SIeLi2kKSFwEKAjo4OBgcHG9zdljU8PNwysbYat+vjimyLov9mt4bPaWBgYNIyw8PDzJo1q676WqnN8iSO3YC5ZAnjeOBoYP0U9nsYsCgirpD0KWAx8MHaQhGxFFgK0NXVFa1yqXJfVr0kK1e4XUcU3BaF/s36c9qsXb8L8gyOfzAiHgR2BLqBz9D44PitwK0RcUVavogskZiZWZPLkzhGxjOOA86OiBXAto3sNCL+CNwi6cC0agFwXSN1mZnZlpWnq+o2SWcBLyK7pPp25Es8oy0CvppmVN1I4+MlZma2BeVJHK8BjgU+HhEPSNoLeE+jO46IqwHfDMrMrMXUnTgi4hHgGzXLdwB3lBGUmU2u8KvQriymvp22n1FIPda8GrmR01ar6JsNQWvN3bbmUfR9SXyvE8tjKmMUW52IqOux/ymX1l3WzKzVOHGYmVkuThxmZpaLE4eZmeXixGFmZrk4cZiZWS5OHGZmlovP47BSHfyhVazfUNzdhYs86W2n7WdwzakvLqw+s62FE4eVav2GjYWdWFb0JaoLP/PabCvhriozM8vFicPMzHJx4jAzs1ycOMzMLBcnDjMzy6WyWVWS1gEPkd2S9rGI8E2dzMxaQNXTcbsj4p6KYzAzsxzcVWVmZrlUmTgCWCXpSkkLK4zDzMxyqLKral5E3CbpycD3JV0fEZfXFkgJZSFAR0cHg4ODFYTZmFaKtWxFtcXw8HDh7erP6XFui+KV8TfbDCpLHBFxW/r3LkkXA88FLh9VZimwFKCrqyuKvNxEqVauKPTSGC2twLYo+pIjW8PnJKnust1n1FfOtzyuX+F/s02ikq4qSTMlzR55DrwYWFtFLGbtrJ773kcEAwMDdZc1q+qIowO4OP0amg6cFxErK4rFzMxyqCRxRMSNwMFV7NvMzKam6vM4mkaz3jfC94wws2bjxJE0630jfM8IM2s2PgHQzMxyceIwM7NcnDjMzCwXJw4zM8vFicPMzHJx4jAzs1w8HddKNbtzMQctX1xchcuLq2p2J0AxU7DNtiZOHFaqh4ZOb8rzY8DnyJg1yl1VZmaWixOHmZnl4sRhZma5OHGYmVkuThxmZpaLZ1UlzTpt1FNGzazZVJo4JE0D1gC3RcTLqoylWaeNesqomTWbqruqTgaGKo7BzMxyqCxxSNqXrA/mC1XFYGZm+VV5xPFJ4L3AXyqMwczMcqpkjEPSy4C7IuJKSfMnKLcQWAjQ0dHB4OBgqXEVVf/w8HChsZb9vsvWrO0Krd+2RSmjba2N2zUitvgD+ChwK7AO+CPwCPCViV5z+OGHR5n2P+XSwuoaGBgorK4i46pCs7ZrROu3bZGKblvLtFK7Amuizu/wSrqqIuJ9EbFvRMwBXgf8KCLeUEUsZmaWT9WzqszMrMVUfgJgRAwCgxWHYSUq9FyUlcXVtdP2Mwqry2xrUnnisPZW1EmVkCWgIuszs8a4q8rMzHJx4jAzs1ycOMzMLBePcdRoxkFcD+CaWbNx4kg8iGtmVh93VZmZWS5OHGZmlosTh5mZ5eLEYWZmuXhw3JqCpPrKnVFffdnFPs2sDD7isKZQz6WcBwYG8ly638xK4sRhZma5OHGYmVkuThxmZpaLB8dzqHcAFzyIa2bty0ccOdQ7MOtBXDNrZ5UkDklPkvQLSddIulbSh6qIw8zM8quqq+rPwDERMSxpBrBa0ncj4ucVxWNmZnWqJHFE1kcznBZnpIf7bczMWoCq6meXNA24Eng68NmIOGWMMguBhQAdHR2Hn3/++Vs2yAYNDw8za9asqsNoO27X8rhty9FK7drd3X1lRHTVU7ayxLE5AGln4GJgUUSsHa9cV1dXrFmzZssFNgWDg4PMnz+/6jDajtu1PG7bcrRSu0qqO3FUPqsqIh4ABoBjq47FzMwmV9Wsqj3SkQaStgdeBFxfRSxmZpZPVbOq9gKWp3GObYALI+LSimIxM7McKh/jqJeku4Gbqo6jTrsD91QdRBtyu5bHbVuOVmrX/SNij3oKtkziaCWS1tQ7yGT1c7uWx21bjnZt18oHx83MrLU4cZiZWS5OHOVYWnUAbcrtWh63bTnasl09xmFmZrn4iMPMzHJx4iiYpGMl/UbS7yUtrjqediDpi5LukjTuJWksP0n7SRqQdF26vcHJVcfULtr91hHuqipQOqHxt2Rnwt8K/BLoiYjrKg2sxUl6AdnVlM+NiLlVx9MuJO0F7BURV0maTXbR0eP99zp1ym4XOrP21hHAye1y6wgfcRTrucDvI+LGiHgUOB94RcUxtbyIuBy4r+o42k1E3BERV6XnDwFDwD7VRtUeItO2t45w4ijWPsAtNcu34v+I1gIkzQEOBa6oNpL2IWmapKuBu4DvR0TbtK0Th9lWTtIs4OvAOyPiwarjaRcRsSkiDgH2BZ4rqW26WZ04inUbsF/N8r5pnVlTSv3vXwe+GhHfqDqedtSOt45w4ijWL4FnSDpA0rbA64BLKo7JbExpAHcZMBQRn6g6nnbS7reOcOIoUEQ8BrwD+B7ZQOOFEXFttVG1Pkn9wM+AAyXdKqm36pjaxN8AbwSOkXR1ery06qDaxF7AgKRfk/2g/H473TrC03HNzCwXH3GYmVkuThxmZpaLE4eZmeXixGFmZrk4cZiZWS5OHGYlk7S3pIuqjsOsKJ6Oa1YgSdPT+TxjLpu1AycOs3FI+ifg38muavpr4ELgA8C2wL3A6yPiTkmnAU8DngrcTHYC6KuAWcA04ETg0oiYmy69fzowH9gO+GxEnJUucX4BsCMwHXhbRPx4C71Vs1ymVx2AWTOS9GyyJPG8iLhH0q5kCeSoiAhJbwLeC7w7veRZwLyI2CDpJOAw4DkRcV+68uyIXmB9RBwhaTvgJ5JWkSWa70VEX0ouO2yBt2nWECcOs7EdA3wtIu4BSAngIOCCdHSwLfCHmvKXRMSGmuXvR8RY9xB5MfAcSa9OyzsBzyC7LMUX00UHvxkRVxf8fswK48Fxs/p9GvhMRBwEvAV4Us22h0eVHb08QsCiiDgkPQ6IiFXpZlUvILua8jmpm8ysKTlxmI3tR8AJknYDSF1VO/H4ZfJPbLDe7wFvS0cWSHqmpJmS9gfujIizgS+QdXWZNSV3VZmNISKuldQHXCZpE/Ar4DTga5LuJ0ssBzRQ9ReAOcBV6bLmdwPHkw2Wv0fSRrL7q/uIw5qWZ1WZmVku7qoyM7NcnDjMzCwXJw4zM8vFicPMzHJx4jAzs1ycOMzMLBcnDjMzy8WJw8zMcvn/uoKlUCw8XR8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-04-04_14_12_47.38854_2000_1_3_ECONOMICS.result\n",
      "carries\n",
      "0    4.439300\n",
      "1    5.000200\n",
      "2    6.570800\n",
      "3    8.244714\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     6.650909\n",
      "1     8.726309\n",
      "2     9.164288\n",
      "3    11.605780\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "9   [1, 0, 0, 1, 0, 0, 0, 1]  [1, 0, 0, 0]        0         3.213\n",
      "29  [1, 1, 0, 1, 1, 1, 0, 1]  [0, 0, 0, 0]        0         3.292\n",
      "22  [1, 1, 1, 1, 0, 0, 1, 0]  [1, 1, 0, 1]        0         3.540\n",
      "16  [1, 0, 1, 1, 0, 0, 1, 1]  [1, 0, 0, 0]        0         4.041\n",
      "1   [1, 1, 0, 1, 1, 1, 0, 0]  [0, 0, 0, 1]        0         4.166\n",
      "32  [0, 1, 1, 1, 0, 0, 1, 0]  [0, 1, 0, 1]        0         4.197\n",
      "14  [1, 0, 1, 1, 1, 0, 1, 0]  [0, 0, 0, 1]        0         4.619\n",
      "23  [1, 1, 1, 0, 1, 0, 1, 0]  [0, 1, 0, 0]        0         4.869\n",
      "20  [0, 1, 0, 0, 0, 1, 0, 0]  [0, 0, 0, 0]        0         5.744\n",
      "13  [1, 0, 1, 0, 0, 0, 0, 0]  [1, 0, 1, 0]        0         6.712\n",
      "                  data_index        answer  carries  solving_time\n",
      "8   [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         3.401\n",
      "28  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         3.462\n",
      "18  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         3.837\n",
      "34  [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         3.853\n",
      "12  [1, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0]        1         4.326\n",
      "33  [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         4.635\n",
      "21  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         4.962\n",
      "17  [1, 0, 1, 0, 0, 0, 0, 1]  [1, 0, 0, 1]        1         5.556\n",
      "39  [0, 1, 1, 0, 0, 0, 0, 1]  [0, 1, 0, 1]        1         6.415\n",
      "11  [1, 1, 0, 1, 1, 0, 1, 0]  [0, 0, 1, 1]        1         9.555\n",
      "                  data_index        answer  carries  solving_time\n",
      "4   [1, 1, 0, 1, 0, 1, 1, 1]  [0, 1, 1, 0]        2         4.946\n",
      "26  [1, 0, 0, 1, 0, 0, 1, 0]  [0, 1, 1, 1]        2         5.040\n",
      "3   [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 1]        2         5.724\n",
      "36  [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         5.930\n",
      "0   [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         6.118\n",
      "38  [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         6.649\n",
      "10  [1, 0, 0, 0, 0, 0, 1, 0]  [0, 1, 1, 0]        2         7.212\n",
      "15  [1, 0, 0, 1, 0, 0, 1, 1]  [0, 1, 1, 0]        2         7.337\n",
      "35  [1, 1, 1, 0, 1, 0, 1, 1]  [0, 0, 1, 1]        2         7.571\n",
      "7   [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         9.181\n",
      "                  data_index        answer  carries  solving_time\n",
      "5   [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         6.072\n",
      "27  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3         6.759\n",
      "31  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         7.305\n",
      "2   [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         8.272\n",
      "24  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3         9.039\n",
      "37  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         9.305\n",
      "25  [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3        10.961\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_data/results/2019-03-27_16_42_57.58021_1997_1_4_COMPUTER SCIENCE.result\n",
      "carries\n",
      "0     2.7657\n",
      "1     3.5084\n",
      "2     4.6251\n",
      "3    10.0107\n",
      "Name: solving_time, dtype: float64\n",
      "carries\n",
      "0     6.583871\n",
      "1     6.218590\n",
      "2     8.909825\n",
      "3    29.408602\n",
      "Name: solving_time, dtype: float64\n",
      "                  data_index        answer  carries  solving_time\n",
      "38  [1, 0, 1, 0, 1, 0, 1, 0]  [0, 0, 0, 0]        0         1.211\n",
      "21  [0, 1, 1, 1, 0, 1, 1, 1]  [0, 0, 0, 0]        0         1.729\n",
      "19  [1, 0, 0, 0, 0, 0, 0, 0]  [1, 0, 0, 0]        0         1.807\n",
      "36  [1, 1, 0, 1, 1, 1, 0, 0]  [0, 0, 0, 1]        0         1.808\n",
      "27  [0, 1, 1, 0, 0, 0, 0, 0]  [0, 1, 1, 0]        0         1.843\n",
      "28  [1, 1, 0, 0, 0, 1, 0, 0]  [1, 0, 0, 0]        0         1.901\n",
      "6   [1, 1, 0, 0, 1, 1, 0, 0]  [0, 0, 0, 0]        0         2.368\n",
      "3   [1, 1, 1, 0, 0, 0, 0, 0]  [1, 1, 1, 0]        0         3.145\n",
      "18  [1, 0, 1, 1, 0, 0, 1, 0]  [1, 0, 0, 1]        0         4.243\n",
      "35  [1, 1, 1, 1, 0, 1, 0, 1]  [1, 0, 1, 0]        0         7.602\n",
      "                  data_index        answer  carries  solving_time\n",
      "25  [1, 0, 0, 0, 0, 1, 0, 0]  [0, 1, 0, 0]        1         1.577\n",
      "20  [0, 0, 1, 0, 0, 0, 0, 1]  [0, 0, 0, 1]        1         1.802\n",
      "22  [1, 0, 0, 1, 0, 1, 0, 0]  [0, 1, 0, 1]        1         3.140\n",
      "23  [1, 0, 1, 1, 0, 1, 1, 0]  [0, 1, 0, 1]        1         3.152\n",
      "32  [0, 1, 1, 0, 0, 1, 0, 1]  [0, 0, 0, 1]        1         3.327\n",
      "29  [1, 0, 1, 1, 0, 1, 0, 0]  [0, 1, 1, 1]        1         3.565\n",
      "12  [0, 1, 0, 1, 0, 0, 1, 1]  [0, 0, 1, 0]        1         3.574\n",
      "14  [1, 1, 0, 0, 0, 0, 1, 0]  [1, 0, 1, 0]        1         4.008\n",
      "33  [1, 0, 1, 1, 0, 1, 0, 1]  [0, 1, 1, 0]        1         4.564\n",
      "0   [1, 1, 1, 0, 1, 1, 0, 1]  [0, 0, 0, 1]        1         6.375\n",
      "                  data_index        answer  carries  solving_time\n",
      "30  [0, 1, 0, 0, 0, 0, 1, 1]  [0, 0, 0, 1]        2         2.095\n",
      "4   [0, 1, 0, 0, 0, 0, 0, 1]  [0, 0, 1, 1]        2         2.210\n",
      "34  [1, 1, 0, 0, 1, 0, 1, 1]  [0, 0, 0, 1]        2         2.498\n",
      "39  [1, 0, 0, 1, 0, 1, 1, 0]  [0, 0, 1, 1]        2         2.832\n",
      "7   [1, 0, 1, 0, 0, 1, 0, 1]  [0, 1, 0, 1]        2         4.481\n",
      "31  [0, 1, 1, 0, 0, 0, 1, 1]  [0, 0, 1, 1]        2         4.556\n",
      "13  [1, 1, 0, 1, 0, 1, 1, 0]  [0, 1, 1, 1]        2         6.404\n",
      "9   [1, 1, 0, 0, 1, 0, 0, 1]  [0, 0, 1, 1]        2         6.603\n",
      "8   [1, 1, 0, 0, 0, 0, 1, 1]  [1, 0, 0, 1]        2         7.098\n",
      "15  [1, 1, 0, 0, 0, 1, 1, 0]  [0, 1, 1, 0]        2         7.474\n",
      "                  data_index        answer  carries  solving_time\n",
      "16  [1, 0, 0, 0, 0, 1, 0, 1]  [0, 0, 1, 1]        3         3.417\n",
      "37  [1, 0, 0, 0, 0, 0, 0, 1]  [0, 1, 1, 1]        3         4.781\n",
      "17  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         5.120\n",
      "26  [1, 0, 1, 0, 0, 0, 1, 1]  [0, 1, 1, 1]        3         5.486\n",
      "5   [1, 0, 0, 0, 0, 1, 1, 1]  [0, 0, 0, 1]        3         6.463\n",
      "1   [1, 1, 1, 0, 0, 1, 1, 1]  [0, 1, 1, 1]        3         6.544\n",
      "11  [1, 1, 0, 0, 0, 1, 0, 1]  [0, 1, 1, 1]        3         6.628\n",
      "2   [1, 0, 0, 0, 0, 0, 1, 1]  [0, 1, 0, 1]        3         8.510\n",
      "24  [1, 1, 0, 0, 0, 1, 1, 1]  [0, 1, 0, 1]        3        18.091\n",
      "10  [1, 0, 1, 0, 0, 1, 1, 1]  [0, 0, 1, 1]        3        35.067\n"
     ]
    }
   ],
   "source": [
    "operator = 'subtract'\n",
    "df_results = list()\n",
    "result_files = get_all_result_files()\n",
    "cols = ['data_index', 'answer', 'carries', 'solving_time']\n",
    "for f in result_files:\n",
    "    if get_operator(f) == operator:\n",
    "\n",
    "        df_result = read_result_file(f)\n",
    "        df_result = df_result[df_result['correct'] == True]\n",
    "        #df_result = df_result[df_result['solving_time'] < 30]\n",
    "        df_result = df_result[cols]\n",
    "        df_results.append(df_result)\n",
    "        \n",
    "        st_means = df_result.groupby(['carries'])['solving_time'].mean()\n",
    "        st_stds = df_result.groupby(['carries'])['solving_time'].std()\n",
    "        print_all = True\n",
    "        if print_all:\n",
    "            \n",
    "            df_result.boxplot(column=['solving_time'], by='carries')\n",
    "            plt.ylabel('solving_time')\n",
    "            plt.show()\n",
    "            print(f)\n",
    "            print(st_means)\n",
    "            print(st_means + 2 * st_stds)\n",
    "            print(df_result[df_result['carries'] == 0].sort_values(by=['solving_time']))\n",
    "            print(df_result[df_result['carries'] == 1].sort_values(by=['solving_time']))\n",
    "            print(df_result[df_result['carries'] == 2].sort_values(by=['solving_time']))\n",
    "            print(df_result[df_result['carries'] == 3].sort_values(by=['solving_time']))"
   ]
  }
 ],
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
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