07 Array 真是太炫了.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 04-01 用電腦來學習\n",
    "\n",
    "今天我們會簡單介紹 Python 在算數學的時候, 可以用到的一些基本工具。做這個的目的, 除了介紹基本工具, 更重要的是希望大家知道, 「你一定要去寫有意思的程式, 你才有興趣寫下去。」\n",
    "\n",
    "也就是, 「你要覺得好玩才可以。」也許是我們同學太優秀, 所以似乎不太會找好玩的問題。\n",
    "\n",
    "另一方面, 如果我們要學的東西就是, 嗯, 什麼貝式統計啦, 假設檢定啦, information theory 啦, 或其他任何有點深奧生硬的主題, 要怎麼辦呢? 一個很好的方法, 就是用 Python 寫程式來幫你學習!\n",
    "\n",
    "很能代表這樣精神的, 就是 Allen Downey 教授, 他學什麼都寫成程式。他以前是寫 Java 的, 有本很出名的書叫 \"How To Think Like a Computer Scientist\", 第一版用的是 Java。之後有人覺得這本書太有意思, 和他合寫 Python 版, 然後他的主力程式語言就變成 Python 了!\n",
    "\n",
    "[【Allen Downey 免費的書下載】](https://greenteapress.com/wp/)\n",
    "\n",
    "另一個很好的例子是 Mosky, 她是台科大資料系出身, 近來非常認真的唸數學和統計學, 她的\n",
    "\n",
    "[【Hypothesis Testing with Python】](https://github.com/moskytw/hypothesis-testing-with-python)\n",
    "\n",
    "就是很好的「用電腦學習」的範例。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 04-02 進入 array 導向的程式設計\n",
    "\n",
    "數據分析最重要的概念, 大概是「不到最後關頭, 絕不輕言使用迴圈」。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "有一班同學成績是這樣的:\n",
    "    \n",
    "    grades = [35, 74, 43, 66, 87, 55, 71, 65]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "老師想要每位同學成績都是乘 1.1 倍!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "grades = [35, 74, 43, 66, 87, 55, 71, 65]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "curved = []\n",
    "\n",
    "for g in grades:\n",
    "    curved.append(g*1.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[38.5,\n",
       " 81.4,\n",
       " 47.300000000000004,\n",
       " 72.60000000000001,\n",
       " 95.7,\n",
       " 60.50000000000001,\n",
       " 78.10000000000001,\n",
       " 71.5]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "curved"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "或許再加個 3 分, 於是又..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "curved2 = []\n",
    "\n",
    "for g in curved:\n",
    "    curved2.append(g + 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[42.5,\n",
       " 85.4,\n",
       " 51.300000000000004,\n",
       " 76.60000000000001,\n",
       " 99.7,\n",
       " 64.5,\n",
       " 82.10000000000001,\n",
       " 75.5]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "curved2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "換成 array, 又快又自然!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "grad_arr = np.array(grades)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([35, 74, 43, 66, 87, 55, 71, 65])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grad_arr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([38.5, 81.4, 47.3, 72.6, 95.7, 60.5, 78.1, 71.5])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grad_arr * 1.1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "看來還是再加個 3 分..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([42.5, 85.4, 51.3, 76.6, 99.7, 64.5, 82.1, 75.5])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grad_arr * 1.1 + 4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 這個就叫 \"broadcasting!\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 04-03 Broadcasting 比我們想像更有趣"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "一位老師成績這樣算的:\n",
    "\n",
    "* 平時成績 20%\n",
    "* 期中考 35%\n",
    "* 期未考 45%\n",
    "\n",
    "有位同學\n",
    "\n",
    "* 平時成績 85 分\n",
    "* 期中 70 分\n",
    "* 期末 80 分\n",
    "\n",
    "這位同學的學期成績是多少?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "grades = np.array([85, 70, 80])\n",
    "weights = np.array([0.2, 0.35, 0.45])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "wgrades = grades * weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([17. , 24.5, 36. ])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wgrades"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "77.5"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wgrades.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我們其實可以用 dot product (矩陣乘法) 算出來!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "77.5"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grades @ weights"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "很多同學一起來..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "grades = np.array([[85, 70, 80],\n",
    "                 [12, 88, 77],\n",
    "                 [85, 91, 33]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[17.  , 24.5 , 36.  ],\n",
       "       [ 2.4 , 30.8 , 34.65],\n",
       "       [17.  , 31.85, 14.85]])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grades * weights"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "軸的概念!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "wgrades = grades * weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[17.  , 24.5 , 36.  ],\n",
       "       [ 2.4 , 30.8 , 34.65],\n",
       "       [17.  , 31.85, 14.85]])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wgrades"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([77.5 , 67.85, 63.7 ])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wgrades.sum(axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "當然我這麼算有點誤導大家..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([77.5 , 67.85, 63.7 ])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grades @ weights"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我把它弄成「正確的矩陣」呢?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3,)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weights.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.2 ],\n",
       "       [0.35],\n",
       "       [0.45]])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weights.reshape(3,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[77.5 ],\n",
       "       [67.85],\n",
       "       [63.7 ]])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grades @ weights.reshape(3,1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 04-04 重要的 array 大變身\n",
    "\n",
    "我們在數據分析, 常常要改 array 的型式。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### [練習] 一個 50 個數字的 array\n",
    "\n",
    "先想辦法、用亂數做出 50 個數字的 array, 叫做 A 好了。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "A = np.random.randint(0, 10, 50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([8, 9, 5, 2, 0, 7, 4, 1, 3, 7, 1, 9, 5, 4, 9, 3, 5, 9, 7, 9, 6, 5,\n",
       "       6, 7, 2, 9, 2, 9, 1, 6, 9, 6, 0, 7, 5, 1, 5, 7, 7, 8, 1, 4, 9, 9,\n",
       "       8, 3, 7, 2, 5, 3])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 檢查 A 的 shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(50,)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 更改 A 的 shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "A.shape = (5,10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[8, 9, 5, 2, 0, 7, 4, 1, 3, 7],\n",
       "       [1, 9, 5, 4, 9, 3, 5, 9, 7, 9],\n",
       "       [6, 5, 6, 7, 2, 9, 2, 9, 1, 6],\n",
       "       [9, 6, 0, 7, 5, 1, 5, 7, 7, 8],\n",
       "       [1, 4, 9, 9, 8, 3, 7, 2, 5, 3]])"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "但用 `reshape` 其實是比較好的方式..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[8, 9, 5, 2, 0],\n",
       "       [7, 4, 1, 3, 7],\n",
       "       [1, 9, 5, 4, 9],\n",
       "       [3, 5, 9, 7, 9],\n",
       "       [6, 5, 6, 7, 2],\n",
       "       [9, 2, 9, 1, 6],\n",
       "       [9, 6, 0, 7, 5],\n",
       "       [1, 5, 7, 7, 8],\n",
       "       [1, 4, 9, 9, 8],\n",
       "       [3, 7, 2, 5, 3]])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A.reshape(10,5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[8, 9, 5, 2, 0, 7, 4, 1, 3, 7],\n",
       "       [1, 9, 5, 4, 9, 3, 5, 9, 7, 9],\n",
       "       [6, 5, 6, 7, 2, 9, 2, 9, 1, 6],\n",
       "       [9, 6, 0, 7, 5, 1, 5, 7, 7, 8],\n",
       "       [1, 4, 9, 9, 8, 3, 7, 2, 5, 3]])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "A = A.reshape(10, 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[8, 9, 5, 2, 0],\n",
       "       [7, 4, 1, 3, 7],\n",
       "       [1, 9, 5, 4, 9],\n",
       "       [3, 5, 9, 7, 9],\n",
       "       [6, 5, 6, 7, 2],\n",
       "       [9, 2, 9, 1, 6],\n",
       "       [9, 6, 0, 7, 5],\n",
       "       [1, 5, 7, 7, 8],\n",
       "       [1, 4, 9, 9, 8],\n",
       "       [3, 7, 2, 5, 3]])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 拉回成一條向量..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([8, 9, 5, 2, 0, 7, 4, 1, 3, 7, 1, 9, 5, 4, 9, 3, 5, 9, 7, 9, 6, 5,\n",
       "       6, 7, 2, 9, 2, 9, 1, 6, 9, 6, 0, 7, 5, 1, 5, 7, 7, 8, 1, 4, 9, 9,\n",
       "       8, 3, 7, 2, 5, 3])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A.ravel()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[8, 9, 5, 2, 0],\n",
       "       [7, 4, 1, 3, 7],\n",
       "       [1, 9, 5, 4, 9],\n",
       "       [3, 5, 9, 7, 9],\n",
       "       [6, 5, 6, 7, 2],\n",
       "       [9, 2, 9, 1, 6],\n",
       "       [9, 6, 0, 7, 5],\n",
       "       [1, 5, 7, 7, 8],\n",
       "       [1, 4, 9, 9, 8],\n",
       "       [3, 7, 2, 5, 3]])"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 快速 array 生成法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.zeros(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0.]])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.zeros((3,4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 0., 0., 0., 0.],\n",
       "       [0., 1., 0., 0., 0.],\n",
       "       [0., 0., 1., 0., 0.],\n",
       "       [0., 0., 0., 1., 0.],\n",
       "       [0., 0., 0., 0., 1.]])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.eye(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 1., 1., 1., 1., 1., 1.],\n",
       "       [1., 1., 1., 1., 1., 1., 1.],\n",
       "       [1., 1., 1., 1., 1., 1., 1.],\n",
       "       [1., 1., 1., 1., 1., 1., 1.],\n",
       "       [1., 1., 1., 1., 1., 1., 1.],\n",
       "       [1., 1., 1., 1., 1., 1., 1.],\n",
       "       [1., 1., 1., 1., 1., 1., 1.],\n",
       "       [1., 1., 1., 1., 1., 1., 1.]])"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.ones((8,7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 0, 0],\n",
       "       [0, 2, 0],\n",
       "       [0, 0, 3]])"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.diag((1, 2, 3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "很有趣的是..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "A = np.array([[1, 2, 3],\n",
    "             [4, 5, 6],\n",
    "             [7, 8, 9]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 2, 3],\n",
       "       [4, 5, 6],\n",
       "       [7, 8, 9]])"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 5, 9])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.diag(A)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 04-05 array 過濾器\n",
    "\n",
    "array 有個很有趣的用法..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "L = np.array([3, -2, -1, 5, 7, -3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我們用另一個 array, 把「要的」標 True, 不要的標 False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "want = np.array([True, False, False, True, True, False])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "也就是我們只要正的..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3, 5, 7])"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L[want]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "其實我們可以這樣做..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True, False, False,  True,  True, False])"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L>0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3, 5, 7])"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L[L>0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = np.array([1, 2, 3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3,)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "a.shape = (1,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "L = np.array([3, -2, -1, 5, 7, -3, 87])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 3, -2, -1,  5,  7, -3, 87])"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True, False, False,  True,  True, False,  True])"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L>0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True,  True,  True,  True,  True,  True, False])"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L<10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True, False, False,  True,  True, False, False])"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(L>0) & (L<10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3, 5, 7])"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L[(L>0) & (L<10)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### [練習] 畫個函數 (如 sinc), 標出正的部份!¶"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x11c652438>]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(-5, 5, 1000)\n",
    "y = np.sinc(x)\n",
    "\n",
    "plt.plot(x,y,lw=6)\n",
    "plt.plot(x[y>0] , y[y>0], 'o')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 04-06 像上數學課一樣算數學!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sympy as sym"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8333333333333333"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1/2 + 1/3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5/6"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym.Rational(1, 2) + sym.Rational(1, 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "先來變美一點..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "sym.init_printing()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAAsAAAArBAMAAABcLm8jAAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAMhAi783diatmdpm7RFShYZRwAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAqklEQVQYGWNgEGBgMmBgYPAPTVMAUmnfioAkQwOIQKc6V20ECR5isL8Aohl4EsAU92cgM4CB+yMDA0sCA8cHBgZ2IOsAAwPzBoYlCkAl1js2gRWSR/wHAaChxIDycgGgMrMLHAlAKpqB5wADA98nIJOBgdUBTPEHVu0FMvQjGVgeAKkPDNxODAz8CQycfxkY2AIYOH+CfQXi8QLlQHqOM6gAVTKw725kYAAAAVwoPE5sN/8AAAAASUVORK5CYII=\n",
      "text/latex": [
       "$$\\frac{5}{6}$$"
      ],
      "text/plain": [
       "5/6"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym.Rational(1, 2)  + sym.Rational(1, 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "更方便的做法 -- sympify"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAAsAAAArBAMAAABcLm8jAAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAMhAi783diatmdpm7RFShYZRwAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAqklEQVQYGWNgEGBgMmBgYPAPTVMAUmnfioAkQwOIQKc6V20ECR5isL8Aohl4EsAU92cgM4CB+yMDA0sCA8cHBgZ2IOsAAwPzBoYlCkAl1js2gRWSR/wHAaChxIDycgGgMrMLHAlAKpqB5wADA98nIJOBgdUBTPEHVu0FMvQjGVgeAKkPDNxODAz8CQycfxkY2AIYOH+CfQXi8QLlQHqOM6gAVTKw725kYAAAAVwoPE5sN/8AAAAASUVORK5CYII=\n",
      "text/latex": [
       "$$\\frac{5}{6}$$"
      ],
      "text/plain": [
       "5/6"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym.S(1)/2 + sym.S(1)/3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "這太常用了, 所以我們讀進來..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sympy import S, N"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAAsAAAArBAMAAABcLm8jAAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAMhAi783diatmdpm7RFShYZRwAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAqklEQVQYGWNgEGBgMmBgYPAPTVMAUmnfioAkQwOIQKc6V20ECR5isL8Aohl4EsAU92cgM4CB+yMDA0sCA8cHBgZ2IOsAAwPzBoYlCkAl1js2gRWSR/wHAaChxIDycgGgMrMLHAlAKpqB5wADA98nIJOBgdUBTPEHVu0FMvQjGVgeAKkPDNxODAz8CQycfxkY2AIYOH+CfQXi8QLlQHqOM6gAVTKw725kYAAAAVwoPE5sN/8AAAAASUVORK5CYII=\n",
      "text/latex": [
       "$$\\frac{5}{6}$$"
      ],
      "text/plain": [
       "5/6"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "S(1)/2 + S(1)/3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAAwAAAAJBAMAAAD0ltBnAAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAdu+ZiURUMmYiu6sQ3c2sJJ3AAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAPklEQVQIHWNgEPr///9nBhbXlArxAoYyBknGAgYgWMB9AEiyb+AFcZgT+EHU+QP8AUBKjoHJAUgtY+B2YAAA88kMj3opkRQAAAAASUVORK5CYII=\n",
      "text/latex": [
       "$$\\pi$$"
      ],
      "text/plain": [
       "π"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym.pi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "π = sym.pi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAAwAAAAJBAMAAAD0ltBnAAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAdu+ZiURUMmYiu6sQ3c2sJJ3AAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAPklEQVQIHWNgEPr///9nBhbXlArxAoYyBknGAgYgWMB9AEiyb+AFcZgT+EHU+QP8AUBKjoHJAUgtY+B2YAAA88kMj3opkRQAAAAASUVORK5CYII=\n",
      "text/latex": [
       "$$\\pi$$"
      ],
      "text/plain": [
       "π"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "π"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$$3.1415926535897932385$$"
      ],
      "text/plain": [
       "3.1415926535897932385"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "N(π, 20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
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       "513984425322341576233610642506390497500865627109535919465897514131034822769306\n",
       "247435363256916078154781811528436679570611086153315044521274739245449454236828\n",
       "860613408414863776700961207151249140430272538607648236341433462351897576645216\n",
       "413767969031495019108575984423919862916421939949072362346468441173940326591840\n",
       "443780513338945257423995082965912285085558215725031071257012668302402929525220\n",
       "118726767562204154205161841634847565169998116141010029960783869092916030288400\n",
       "269104140792886215078424516709087000699282120660418371806535567252532567532861\n",
       "291042487761825829765157959847035622262934860034158722980534989650226291748788\n",
       "202734209222245339856264766914905562842503912757710284027998066365825488926488\n",
       "025456610172967026640765590429099456815065265305371829412703369313785178609040\n",
       "708667114965583434347693385781711386455873678123014587687126603489139095620099\n",
       "393610310291616152881384379099042317473363948045759314931405297634757481193567\n",
       "091101377517210080315590248530906692037671922033229094334676851422144773793937\n",
       "517034436619910403375111735471918550464490263655128162288244625759163330391072\n",
       "253837421821408835086573917715096828874782656995995744906617583441375223970968\n",
       "340800535598491754173818839994469748676265516582765848358845314277568790029095\n",
       "170283529716344562129640435231176006651012412006597558512761785838292041974844\n",
       "236080071930457618932349229279650198751872127267507981255470958904556357921221\n",
       "033346697499235630254947802490114195212382815309114079073860251522742995818072\n",
       "471625916685451333123948049470791191532673430282441860414263639548000448002670\n",
       "496248201792896476697583183271314251702969234889627668440323260927524960357996\n",
       "469256504936818360900323809293459588970695365349406034021665443755890045632882\n",
       "250545255640564482465151875471196218443965825337543885690941130315095261793780\n",
       "029741207665147939425902989695946995565761218656196733786236256125216320862869\n",
       "222103274889218654364802296780705765615144632046927906821207388377814233562823\n",
       "608963208068222468012248261177185896381409183903673672220888321513755600372798\n",
       "394004152970028783076670944474560134556417254370906979396122571429894671543578\n",
       "468788614445812314593571984922528471605049221242470141214780573455105008019086\n",
       "996033027634787081081754501193071412233908663938339529425786905076431006383519\n",
       "834389341596131854347546495569781038293097164651438407007073604112373599843452\n",
       "251610507027056235266012764848308407611830130527932054274628654036036745328651\n",
       "057065874882256981579367897669742205750596834408697350201410206723585020072452\n",
       "256326513410559240190274216248439140359989535394590944070469120914093870012645\n",
       "600162374288021092764579310657922955249887275846101264836999892256959688159205\n",
       "60010165525637567"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "N(π, 10000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "什麼都在 π 中出現過..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "pistring = str(N(π, 100000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'1215' in pistring"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'9487' in pistring"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$$11942$$"
      ],
      "text/plain": [
       "11942"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pistring.find('1215')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1215'"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pistring[11942:11946]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 04-07 質數"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = 9487"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym.isprime(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAJsAAAAVBAMAAACj9YEXAAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAEER2zVSJ3ZkiZjKru+/kt61jAAAACXBIWXMAAA7EAAAOxAGVKw4bAAACHklEQVQ4Ea1UMUhbURQ9z/hjnknsHy0UDC7dioOIUw0uXYRGOnWqQ7GFijQWxUHRIcNfihndYunmFOjQoaG0lIJDiykIhVJaLRRBWqyiVVSM997/f/qa5EkEL+S998859+S++97/AFQ3LiP0Xd+ldxhx4GqzlvqZRVn6xISzA3Ts3cpCjz5NGcp41ngIly9dOJVK5RQx722I8Uw48JVX0cdA29yUi0607zPgx7Uc/U1NqJXbLqJDnjepnuB1vsoKDjxggO0SvBjIqD2eg4jU25HGRQzQ84l1JOdDJc2E19rdSKEZO4f//Uoa0T/n21EbjwyFrTqSPEJXGZFjQ1xT3fP+IpHXl0QxLaPdTpelul2W+Vpjs7E0kHQ1kS8+sCeCDtrtEilw73grYbelupucXVjiEZ/p5/gny20F7HYFsvmBkoh9rV9dIQOUJiQZC3matwP2fLv7RHf23anrnV7LQOXIYg1YKL4CvpN/GPbqZkUSMy+SbDY6SETyDbAJrKqK25ydOhG71rJM/iB29/L0wNd4BPiNX/WbVUaGLDmt5ZC6vIFC0SDFbpwBtltEZAPLwb0zTrYrbaTwktOcv3ROWXzh5/9OtvqSaW/FRYsXfALkLiW+HbxDW81n4OP2TA/0T/IZfZhiu+DeCf7vnRWm0TDcCLRh1epsAm5q8yF2kXV7guqxc/VMjiHFrbBEuwVvCKstgRffN2QvCsbHMsAZUr+HNuJnLHkAAAAASUVORK5CYII=\n",
      "text/latex": [
       "$$\\left \\{ 53 : 1, \\quad 179 : 1\\right \\}$$"
      ],
      "text/plain": [
       "{53: 1, 179: 1}"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym.factorint(9487)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$$9487$$"
      ],
      "text/plain": [
       "9487"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "53*179"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym.isprime(179)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAB4AAAAOBAMAAADKyLEKAAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAMpndq3ZmzYkiRO+7EFRAb64nAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAnklEQVQIHWNgYGAQAmIQwaTkC2IxmEAIXlMG6QlAJiuIDyRYNjDwKACZYiUQgr+AgeMDkNkA4gOJ+wcYWD8CVU4A8kEESP4XA8M0BiAfRID0fwOqBPFBBO8uBpF/DGwTgEwwwXAp4ulHhqkMQD6YAJrK9JdhiYvLbw8wAeSzHwASDFsgBN9ehvkCIOYfCMFqy3AMxFL/fxRCdDQtYAAAi1IujzSe3HEAAAAASUVORK5CYII=\n",
      "text/latex": [
       "$$449$$"
      ],
      "text/plain": [
       "449"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym.prime(87)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAB8AAAAPBAMAAADuVgmRAAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAMpndq3ZmzYkiRO+7EFRAb64nAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvElEQVQIHS3OTQsBcRDH8W+blbVscnBmU05KcZQcNnkDTl6DclCunJzUprhy8BKccXFUXoqnA1FrZv+mpvnNp6YG4sqRDZ2ByZCHw7h+8aIo+sTWgPpjTmrk+y0FW6At0wKnKJPCyIAHCd2Z/EHiVHc7FOj0ShKdo8IKgTPrjVxIy4UCZGqw1pAMDVhvmCksEcgMsW7QVNgGwafr1khcyT4VpHakwD2Svpudr37Yv+C9DFSiE4tyVd7YC/wAGmQo81LvDdcAAAAASUVORK5CYII=\n",
      "text/latex": [
       "$$457$$"
      ],
      "text/plain": [
       "457"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym.nextprime(449)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3 和 5 是孿生質數!\n",
      "5 和 7 是孿生質數!\n",
      "11 和 13 是孿生質數!\n",
      "17 和 19 是孿生質數!\n",
      "29 和 31 是孿生質數!\n",
      "41 和 43 是孿生質數!\n",
      "59 和 61 是孿生質數!\n",
      "71 和 73 是孿生質數!\n",
      "101 和 103 是孿生質數!\n",
      "107 和 109 是孿生質數!\n",
      "137 和 139 是孿生質數!\n",
      "149 和 151 是孿生質數!\n",
      "179 和 181 是孿生質數!\n",
      "191 和 193 是孿生質數!\n",
      "197 和 199 是孿生質數!\n",
      "227 和 229 是孿生質數!\n"
     ]
    }
   ],
   "source": [
    "for i in range(2, 50):\n",
    "    a = sym.prime(i)\n",
    "    b = sym.prime(i+1)\n",
    "    if b-a == 2:\n",
    "        print(f'{a} 和 {b} 是孿生質數!')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 04-08 Sympy 的矩陣"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "A = sym.Matrix([[2, -1, 3],\n",
    "               [0, 1, 2],\n",
    "               [-1, 1, 2]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAAkAAAAPBAMAAADE5vg+AAAALVBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADAOrOgAAAADnRSTlMAMhAi783diatmdpm7RL9tftMAAAAJcEhZcwAADsQAAA7EAZUrDhsAAABPSURBVAgdY2BkYFBmYGB5GpbEwMCWl67AwMDBAAIo5KzVAgwMPArMb8FSx8DkPgOGowwM+wQY3BgY+hgYChgYfBgYrBm4nBgYmHd3KzAAAOU9DBlFth6pAAAAAElFTkSuQmCC\n",
      "text/latex": [
       "$$5$$"
      ],
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A.det()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$$\\left[\\begin{matrix}0 & 1 & -1\\\\- \\frac{2}{5} & \\frac{7}{5} & - \\frac{4}{5}\\\\\\frac{1}{5} & - \\frac{1}{5} & \\frac{2}{5}\\end{matrix}\\right]$$"
      ],
      "text/plain": [
       "⎡ 0     1     -1 ⎤\n",
       "⎢                ⎥\n",
       "⎢-2/5  7/5   -4/5⎥\n",
       "⎢                ⎥\n",
       "⎣1/5   -1/5  2/5 ⎦"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A.inv()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 04-09 設定 Sympy 的變數"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 第一式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = sym.Symbol('x')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "f = x**2 - 3*x + 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$$x^{2} - 3 x + 2$$"
      ],
      "text/plain": [
       " 2          \n",
       "x  - 3⋅x + 2"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$$2 x - 3$$"
      ],
      "text/plain": [
       "2⋅x - 3"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym.diff(f, x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$$\\frac{x^{3}}{3} - \\frac{3 x^{2}}{2} + 2 x$$"
      ],
      "text/plain": [
       " 3      2      \n",
       "x    3⋅x       \n",
       "── - ──── + 2⋅x\n",
       "3     2        "
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym.integrate(f, x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "g = 5*x**2 - 3*x + 9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$$6 x^{2} - 6 x + 11$$"
      ],
      "text/plain": [
       "   2           \n",
       "6⋅x  - 6⋅x + 11"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f + g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$$\\left(x^{2} - 3 x + 2\\right) \\left(5 x^{2} - 3 x + 9\\right)$$"
      ],
      "text/plain": [
       "⎛ 2          ⎞ ⎛   2          ⎞\n",
       "⎝x  - 3⋅x + 2⎠⋅⎝5⋅x  - 3⋅x + 9⎠"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f * g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'k' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m--------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                          Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-96-0b3b22298560>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mh\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;36m2\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mk\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'k' is not defined"
     ]
    }
   ],
   "source": [
    "h = 3*k**2 - 3*k + 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 第二式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sympy.abc import x, y, z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "f = sym.atan(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$$\\frac{1}{x^{2} + 1}$$"
      ],
      "text/plain": [
       "  1   \n",
       "──────\n",
       " 2    \n",
       "x  + 1"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym.diff(f, x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$$x \\operatorname{atan}{\\left (x \\right )} - \\frac{1}{2} \\log{\\left (x^{2} + 1 \\right )}$$"
      ],
      "text/plain": [
       "               ⎛ 2    ⎞\n",
       "            log⎝x  + 1⎠\n",
       "x⋅atan(x) - ───────────\n",
       "                 2     "
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym.integrate(f, x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$$- \\frac{1}{2} \\log{\\left (2 \\right )} + \\frac{\\pi}{4}$$"
      ],
      "text/plain": [
       "  log(2)   π\n",
       "- ────── + ─\n",
       "    2      4"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym.integrate(f, (x, 0, 1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 【下期預告】熊貓終於是來了"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('http://stats.moe.gov.tw/files/detail/107/107_student.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>學校代碼</th>\n",
       "      <th>學校名稱</th>\n",
       "      <th>日間∕進修別</th>\n",
       "      <th>等級別</th>\n",
       "      <th>一年級男生</th>\n",
       "      <th>一年級女生</th>\n",
       "      <th>二年級男生</th>\n",
       "      <th>二年級女生</th>\n",
       "      <th>三年級男生</th>\n",
       "      <th>三年級女生</th>\n",
       "      <th>...</th>\n",
       "      <th>五年級男生</th>\n",
       "      <th>五年級女生</th>\n",
       "      <th>六年級男生</th>\n",
       "      <th>六年級女生</th>\n",
       "      <th>七年級男生</th>\n",
       "      <th>七年級女生</th>\n",
       "      <th>延修生男生</th>\n",
       "      <th>延修生女生</th>\n",
       "      <th>縣市名稱</th>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>國立政治大學</td>\n",
       "      <td>D 日</td>\n",
       "      <td>D 博士</td>\n",
       "      <td>96</td>\n",
       "      <td>85</td>\n",
       "      <td>82</td>\n",
       "      <td>78</td>\n",
       "      <td>93</td>\n",
       "      <td>59</td>\n",
       "      <td>...</td>\n",
       "      <td>71</td>\n",
       "      <td>52</td>\n",
       "      <td>58</td>\n",
       "      <td>46</td>\n",
       "      <td>74</td>\n",
       "      <td>40</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>30 臺北市</td>\n",
       "      <td>1 一般</td>\n",
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       "    <tr>\n",
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       "      <td>1</td>\n",
       "      <td>國立政治大學</td>\n",
       "      <td>D 日</td>\n",
       "      <td>M 碩士</td>\n",
       "      <td>624</td>\n",
       "      <td>742</td>\n",
       "      <td>632</td>\n",
       "      <td>695</td>\n",
       "      <td>348</td>\n",
       "      <td>431</td>\n",
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       "      <td>國立政治大學</td>\n",
       "      <td>D 日</td>\n",
       "      <td>B 學士</td>\n",
       "      <td>899</td>\n",
       "      <td>1,287</td>\n",
       "      <td>890</td>\n",
       "      <td>1,332</td>\n",
       "      <td>878</td>\n",
       "      <td>1,325</td>\n",
       "      <td>...</td>\n",
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       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>326</td>\n",
       "      <td>463</td>\n",
       "      <td>30 臺北市</td>\n",
       "      <td>1 一般</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>國立政治大學</td>\n",
       "      <td>N 職</td>\n",
       "      <td>M 碩士</td>\n",
       "      <td>303</td>\n",
       "      <td>248</td>\n",
       "      <td>253</td>\n",
       "      <td>259</td>\n",
       "      <td>201</td>\n",
       "      <td>210</td>\n",
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       "      <td>1 一般</td>\n",
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       "      <th>4</th>\n",
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       "      <td>國立清華大學</td>\n",
       "      <td>D 日</td>\n",
       "      <td>D 博士</td>\n",
       "      <td>225</td>\n",
       "      <td>99</td>\n",
       "      <td>201</td>\n",
       "      <td>71</td>\n",
       "      <td>189</td>\n",
       "      <td>73</td>\n",
       "      <td>...</td>\n",
       "      <td>158</td>\n",
       "      <td>50</td>\n",
       "      <td>112</td>\n",
       "      <td>43</td>\n",
       "      <td>168</td>\n",
       "      <td>58</td>\n",
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       "      <td>18 新竹市</td>\n",
       "      <td>1 一般</td>\n",
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       "<p>5 rows × 22 columns</p>\n",
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      "text/plain": [
       "   學校代碼    學校名稱 日間∕進修別   等級別 一年級男生  一年級女生 二年級男生  二年級女生 三年級男生  三年級女生  ...   \\\n",
       "0     1  國立政治大學    D 日  D 博士    96     85    82     78    93     59  ...    \n",
       "1     1  國立政治大學    D 日  M 碩士   624    742   632    695   348    431  ...    \n",
       "2     1  國立政治大學    D 日  B 學士   899  1,287   890  1,332   878  1,325  ...    \n",
       "3     1  國立政治大學    N 職  M 碩士   303    248   253    259   201    210  ...    \n",
       "4     2  國立清華大學    D 日  D 博士   225     99   201     71   189     73  ...    \n",
       "\n",
       "  五年級男生 五年級女生 六年級男生 六年級女生 七年級男生 七年級女生 延修生男生 延修生女生    縣市名稱   體系別  \n",
       "0    71    52    58    46    74    40     -     -  30 臺北市  1 一般  \n",
       "1     -     -     -     -     -     -     -     -  30 臺北市  1 一般  \n",
       "2     -     -     -     -     -     -   326   463  30 臺北市  1 一般  \n",
       "3    53    47     -     -     -     -     -     -  30 臺北市  1 一般  \n",
       "4   158    50   112    43   168    58     -     -  18 新竹市  1 一般  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 104,
     "metadata": {},
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    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果我們要算日間部, 用大學部一年級同學計算, 什麼學校女生比男生比例是最高的 (或男生比女生比例最高), 前 20 名要怎麼做呢?"
   ]
  }
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