explore.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Visualization for Exploration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook details data visualization for exploring a dataset. The goal is to understand more about the data as a human, not to make beautiful graphs, communicate, or feature engineering input into models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scipy.stats as st\n",
    "\n",
    "#ggplot equivalent: plotnine\n",
    "from plotnine import *\n",
    "\n",
    "#scales package equivalent: mizani\n",
    "from mizani.breaks import *\n",
    "from mizani.formatters import *\n",
    "\n",
    "#widgets\n",
    "from ipywidgets import interact, interactive, fixed, interact_manual\n",
    "import ipywidgets as widgets\n",
    "\n",
    "#utility\n",
    "import utils\n",
    "def clean_comma(x): return float(str(x).replace(',',''))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Snippet for plotnine with thai font by @korakot\n",
    "https://gist.github.com/korakot/01d181229b21411b0a20784e0ca20d3d\n",
    "'''\n",
    "import matplotlib\n",
    "# !wget https://github.com/Phonbopit/sarabun-webfont/raw/master/fonts/thsarabunnew-webfont.ttf -q\n",
    "# !cp thsarabunnew-webfont.ttf /usr/share/fonts/truetype/\n",
    "matplotlib.font_manager._rebuild()\n",
    "matplotlib.rc('font', family='TH Sarabun New')\n",
    "theme_set(theme_minimal(11, 'TH Sarabun New'));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>brand</th>\n",
       "      <th>series</th>\n",
       "      <th>model</th>\n",
       "      <th>gen</th>\n",
       "      <th>year</th>\n",
       "      <th>color</th>\n",
       "      <th>gear</th>\n",
       "      <th>gas</th>\n",
       "      <th>sales_price</th>\n",
       "      <th>original_price</th>\n",
       "      <th>market_price</th>\n",
       "      <th>description</th>\n",
       "      <th>contact_location</th>\n",
       "      <th>subscribers</th>\n",
       "      <th>scraped_date</th>\n",
       "      <th>removed_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2210000</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>JAZZ</td>\n",
       "      <td>1.5 i-VTEC SV (AS)</td>\n",
       "      <td>ปี08-13</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>สีขาว</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>NaN</td>\n",
       "      <td>488000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>เครดิตดีออกรถ10,000จบครับ\\nรับประกันเครื่องเกี...</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "      <td>1047.0</td>\n",
       "      <td>2019-05-22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2210001</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>ESTIMA</td>\n",
       "      <td>2.4 G HYBRID</td>\n",
       "      <td>ปี10-ปัจจุบัน</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>สีขาว</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1677000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3050000.0</td>\n",
       "      <td>TOPสุด Estima Aeras Hybrid รถเข้าเซอร์วิส TOYO...</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "      <td>182.0</td>\n",
       "      <td>2019-05-22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2210009</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>JAZZ</td>\n",
       "      <td>1.5 i-VTEC V (AS)</td>\n",
       "      <td>ปี08-13</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>สีน้ำเงิน</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>NaN</td>\n",
       "      <td>338000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>เครดิดีออกรถ10,000จบครับ\\nรับประกันเครื่องเกีย...</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "      <td>1047.0</td>\n",
       "      <td>2019-05-22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2210012</td>\n",
       "      <td>FORD</td>\n",
       "      <td>RANGER</td>\n",
       "      <td>2.2 WILDTRAK DBL CAB HI-RIDER</td>\n",
       "      <td>DOUBLECAB</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>สีขาว</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>NaN</td>\n",
       "      <td>689000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>849000.0</td>\n",
       "      <td>รับรองสภาพ ไม่มีชน มือเดียว พาช่างมาตรวจสภาพรถ...</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "      <td>760.0</td>\n",
       "      <td>2019-05-22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2210016</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>SOLUNA</td>\n",
       "      <td>VIOS 1.5 E (ABS+AB)</td>\n",
       "      <td>VIOS ปี13-ปัจจุบัน</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>สีบรอนซ์เงิน</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>NaN</td>\n",
       "      <td>359000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>649000.0</td>\n",
       "      <td>ไมล์แท้ 99,xxx TOYOTA SOLUNA VIOS 1.5E\\nTOYOTA...</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "      <td>699.0</td>\n",
       "      <td>2019-05-22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        id   brand  series                          model                 gen  \\\n",
       "0  2210000   HONDA    JAZZ             1.5 i-VTEC SV (AS)             ปี08-13   \n",
       "1  2210001  TOYOTA  ESTIMA                   2.4 G HYBRID       ปี10-ปัจจุบัน   \n",
       "2  2210009   HONDA    JAZZ              1.5 i-VTEC V (AS)             ปี08-13   \n",
       "3  2210012    FORD  RANGER  2.2 WILDTRAK DBL CAB HI-RIDER           DOUBLECAB   \n",
       "4  2210016  TOYOTA  SOLUNA            VIOS 1.5 E (ABS+AB)  VIOS ปี13-ปัจจุบัน   \n",
       "\n",
       "     year         color         gear  gas  sales_price original_price  \\\n",
       "0  2014.0         สีขาว  เกียร์ออโต้  NaN     488000.0            NaN   \n",
       "1  2013.0         สีขาว  เกียร์ออโต้  NaN    1677000.0            NaN   \n",
       "2  2008.0     สีน้ำเงิน  เกียร์ออโต้  NaN     338000.0            NaN   \n",
       "3  2016.0         สีขาว  เกียร์ออโต้  NaN     689000.0            NaN   \n",
       "4  2015.0  สีบรอนซ์เงิน  เกียร์ออโต้  NaN     359000.0            NaN   \n",
       "\n",
       "   market_price                                        description  \\\n",
       "0           NaN  เครดิตดีออกรถ10,000จบครับ\\nรับประกันเครื่องเกี...   \n",
       "1     3050000.0  TOPสุด Estima Aeras Hybrid รถเข้าเซอร์วิส TOYO...   \n",
       "2           NaN  เครดิดีออกรถ10,000จบครับ\\nรับประกันเครื่องเกีย...   \n",
       "3      849000.0  รับรองสภาพ ไม่มีชน มือเดียว พาช่างมาตรวจสภาพรถ...   \n",
       "4      649000.0  ไมล์แท้ 99,xxx TOYOTA SOLUNA VIOS 1.5E\\nTOYOTA...   \n",
       "\n",
       "  contact_location  subscribers scraped_date removed_date  \n",
       "0         กรุงเทพฯ       1047.0   2019-05-22          NaN  \n",
       "1         กรุงเทพฯ        182.0   2019-05-22          NaN  \n",
       "2         กรุงเทพฯ       1047.0   2019-05-22          NaN  \n",
       "3         กรุงเทพฯ        760.0   2019-05-22          NaN  \n",
       "4         กรุงเทพฯ        699.0   2019-05-22          NaN  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('data/taladrod.csv')\n",
    "df['sales_price'] = df.sales_price.map(clean_comma)\n",
    "df['market_price'] = df.market_price.map(clean_comma)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Warming Up: Missing Values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We use grammar of graphics implementation `ggplot` (ported to Python as `plotnine`) to explore the `taladrod` dataset. Grammar of graphics is an especially useful tool since we do not know exactly what kind of plots we want to see and want to be able to add them up as we go.\n",
    "\n",
    "![Grammar of Graphics](images/ggpyramid.png)\n",
    "Source: [A Comprehensive Guide to the Grammar of Graphics for Effective Visualization of Multi-dimensional Data](https://towardsdatascience.com/a-comprehensive-guide-to-the-grammar-of-graphics-for-effective-visualization-of-multi-dimensional-1f92b4ed4149)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>col_name</th>\n",
       "      <th>per_missing</th>\n",
       "      <th>rnk</th>\n",
       "      <th>over90</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>original_price</td>\n",
       "      <td>0.991380</td>\n",
       "      <td>00_original_price</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gas</td>\n",
       "      <td>0.936525</td>\n",
       "      <td>01_gas</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>removed_date</td>\n",
       "      <td>0.886728</td>\n",
       "      <td>02_removed_date</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>market_price</td>\n",
       "      <td>0.561658</td>\n",
       "      <td>03_market_price</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>subscribers</td>\n",
       "      <td>0.000641</td>\n",
       "      <td>04_subscribers</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         col_name  per_missing                rnk  over90\n",
       "0  original_price     0.991380  00_original_price    True\n",
       "1             gas     0.936525             01_gas    True\n",
       "2    removed_date     0.886728    02_removed_date   False\n",
       "3    market_price     0.561658    03_market_price   False\n",
       "4     subscribers     0.000641     04_subscribers   False"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "missing = utils.check_missing(df)\n",
    "missing['over90'] = missing.per_missing.map(lambda x: True if x>0.9 else False)\n",
    "missing.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (-9223363263941433635)>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = (ggplot(missing,aes(x='rnk',y='per_missing',fill='over90')) + #base plot\n",
    "     geom_col() + #type of plot \n",
    "     geom_text(aes(x='rnk',y='per_missing+0.1',label='round(100*per_missing,2)')) +#annotate\n",
    "     scale_y_continuous(labels=percent_format()) + #y-axis tick\n",
    "     theme_minimal() + coord_flip()#theme and flipping plot\n",
    "    )\n",
    "g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>brand</th>\n",
       "      <th>series</th>\n",
       "      <th>model</th>\n",
       "      <th>gen</th>\n",
       "      <th>year</th>\n",
       "      <th>color</th>\n",
       "      <th>gear</th>\n",
       "      <th>sales_price</th>\n",
       "      <th>market_price</th>\n",
       "      <th>description</th>\n",
       "      <th>contact_location</th>\n",
       "      <th>subscribers</th>\n",
       "      <th>scraped_date</th>\n",
       "      <th>removed_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2210000</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>JAZZ</td>\n",
       "      <td>1.5 i-VTEC SV (AS)</td>\n",
       "      <td>ปี08-13</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>สีขาว</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>488000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>เครดิตดีออกรถ10,000จบครับ\\nรับประกันเครื่องเกี...</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "      <td>1047.0</td>\n",
       "      <td>2019-05-22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2210001</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>ESTIMA</td>\n",
       "      <td>2.4 G HYBRID</td>\n",
       "      <td>ปี10-ปัจจุบัน</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>สีขาว</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>1677000.0</td>\n",
       "      <td>3050000.0</td>\n",
       "      <td>TOPสุด Estima Aeras Hybrid รถเข้าเซอร์วิส TOYO...</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "      <td>182.0</td>\n",
       "      <td>2019-05-22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2210009</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>JAZZ</td>\n",
       "      <td>1.5 i-VTEC V (AS)</td>\n",
       "      <td>ปี08-13</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>สีน้ำเงิน</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>338000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>เครดิดีออกรถ10,000จบครับ\\nรับประกันเครื่องเกีย...</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "      <td>1047.0</td>\n",
       "      <td>2019-05-22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2210012</td>\n",
       "      <td>FORD</td>\n",
       "      <td>RANGER</td>\n",
       "      <td>2.2 WILDTRAK DBL CAB HI-RIDER</td>\n",
       "      <td>DOUBLECAB</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>สีขาว</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>689000.0</td>\n",
       "      <td>849000.0</td>\n",
       "      <td>รับรองสภาพ ไม่มีชน มือเดียว พาช่างมาตรวจสภาพรถ...</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "      <td>760.0</td>\n",
       "      <td>2019-05-22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2210016</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>SOLUNA</td>\n",
       "      <td>VIOS 1.5 E (ABS+AB)</td>\n",
       "      <td>VIOS ปี13-ปัจจุบัน</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>สีบรอนซ์เงิน</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>359000.0</td>\n",
       "      <td>649000.0</td>\n",
       "      <td>ไมล์แท้ 99,xxx TOYOTA SOLUNA VIOS 1.5E\\nTOYOTA...</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "      <td>699.0</td>\n",
       "      <td>2019-05-22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        id   brand  series                          model                 gen  \\\n",
       "0  2210000   HONDA    JAZZ             1.5 i-VTEC SV (AS)             ปี08-13   \n",
       "1  2210001  TOYOTA  ESTIMA                   2.4 G HYBRID       ปี10-ปัจจุบัน   \n",
       "2  2210009   HONDA    JAZZ              1.5 i-VTEC V (AS)             ปี08-13   \n",
       "3  2210012    FORD  RANGER  2.2 WILDTRAK DBL CAB HI-RIDER           DOUBLECAB   \n",
       "4  2210016  TOYOTA  SOLUNA            VIOS 1.5 E (ABS+AB)  VIOS ปี13-ปัจจุบัน   \n",
       "\n",
       "     year         color         gear  sales_price  market_price  \\\n",
       "0  2014.0         สีขาว  เกียร์ออโต้     488000.0           NaN   \n",
       "1  2013.0         สีขาว  เกียร์ออโต้    1677000.0     3050000.0   \n",
       "2  2008.0     สีน้ำเงิน  เกียร์ออโต้     338000.0           NaN   \n",
       "3  2016.0         สีขาว  เกียร์ออโต้     689000.0      849000.0   \n",
       "4  2015.0  สีบรอนซ์เงิน  เกียร์ออโต้     359000.0      649000.0   \n",
       "\n",
       "                                         description contact_location  \\\n",
       "0  เครดิตดีออกรถ10,000จบครับ\\nรับประกันเครื่องเกี...         กรุงเทพฯ   \n",
       "1  TOPสุด Estima Aeras Hybrid รถเข้าเซอร์วิส TOYO...         กรุงเทพฯ   \n",
       "2  เครดิดีออกรถ10,000จบครับ\\nรับประกันเครื่องเกีย...         กรุงเทพฯ   \n",
       "3  รับรองสภาพ ไม่มีชน มือเดียว พาช่างมาตรวจสภาพรถ...         กรุงเทพฯ   \n",
       "4  ไมล์แท้ 99,xxx TOYOTA SOLUNA VIOS 1.5E\\nTOYOTA...         กรุงเทพฯ   \n",
       "\n",
       "   subscribers scraped_date removed_date  \n",
       "0       1047.0   2019-05-22          NaN  \n",
       "1        182.0   2019-05-22          NaN  \n",
       "2       1047.0   2019-05-22          NaN  \n",
       "3        760.0   2019-05-22          NaN  \n",
       "4        699.0   2019-05-22          NaN  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#drop columns with too many missing values\n",
    "df.drop(missing[missing.over90==True].col_name,1,inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Categorical Variables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We want to know primarily two things about our categorical variables:\n",
    "1. How each variable is distributed\n",
    "2. How each variable relate to the dependent variable\n",
    "    * 2.1 when dependent variable is numerical\n",
    "    * 2.2 when dependent variable is categorical"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>brand</th>\n",
       "      <th>series</th>\n",
       "      <th>gen</th>\n",
       "      <th>color</th>\n",
       "      <th>gear</th>\n",
       "      <th>contact_location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HONDA</td>\n",
       "      <td>JAZZ</td>\n",
       "      <td>ปี08-13</td>\n",
       "      <td>สีขาว</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>ESTIMA</td>\n",
       "      <td>ปี10-ปัจจุบัน</td>\n",
       "      <td>สีขาว</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HONDA</td>\n",
       "      <td>JAZZ</td>\n",
       "      <td>ปี08-13</td>\n",
       "      <td>สีน้ำเงิน</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>FORD</td>\n",
       "      <td>RANGER</td>\n",
       "      <td>DOUBLECAB</td>\n",
       "      <td>สีขาว</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>SOLUNA</td>\n",
       "      <td>VIOS ปี13-ปัจจุบัน</td>\n",
       "      <td>สีบรอนซ์เงิน</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    brand  series                 gen         color         gear  \\\n",
       "0   HONDA    JAZZ             ปี08-13         สีขาว  เกียร์ออโต้   \n",
       "1  TOYOTA  ESTIMA       ปี10-ปัจจุบัน         สีขาว  เกียร์ออโต้   \n",
       "2   HONDA    JAZZ             ปี08-13     สีน้ำเงิน  เกียร์ออโต้   \n",
       "3    FORD  RANGER           DOUBLECAB         สีขาว  เกียร์ออโต้   \n",
       "4  TOYOTA  SOLUNA  VIOS ปี13-ปัจจุบัน  สีบรอนซ์เงิน  เกียร์ออโต้   \n",
       "\n",
       "  contact_location  \n",
       "0         กรุงเทพฯ  \n",
       "1         กรุงเทพฯ  \n",
       "2         กรุงเทพฯ  \n",
       "3         กรุงเทพฯ  \n",
       "4         กรุงเทพฯ  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat_vars = ['brand','series','gen','color','gear','contact_location']\n",
    "cat_df = df[cat_vars].copy()\n",
    "cat_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To simplify the data cleaning step, we \"otherify\" values that appear less than 3% of the time in all categorical columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#otherify popular values; you can (should?) also have a mapping dict\n",
    "for col in cat_vars: cat_df = utils.otherify(cat_df,col,th=0.03)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Value Distribution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Even without plotting them out, we can see the value distribution in each variable using `ipywidgets`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e0b185ce927541798a6ce9015a3dc2d9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='col', options=('brand', 'series', 'gen', 'color', 'gear', 'contact…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function utils.value_dist(df, col)>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "interact(utils.value_dist, df =fixed(cat_df),\n",
    "         col = widgets.Dropdown(options=list(cat_df.columns),value='brand'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise** Implement `cat_plot` function that plots value distribution for each categorical variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "84bca6143a1a41e68e40620fc3a8c119",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='col', options=('brand', 'series', 'gen', 'color', 'gear', 'contact…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.cat_plot(df, col)>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def cat_plot(df,col):\n",
    "    return utils.cat_plot(df,col) \n",
    "#input dataframe and column\n",
    "#output histogram plot of value distribution\n",
    "\n",
    "interact(cat_plot, df=fixed(cat_df),\n",
    "         col = widgets.Dropdown(options=list(cat_df.columns),value='brand'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0285bb7c62c84b7baea6062eb1d6c07f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='col', index=2, options=('brand', 'series', 'gen', 'color', 'gear',…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.cat_plot_noothers(df, col)>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#excluding others\n",
    "def cat_plot_noothers(df,col):\n",
    "    x = df.copy()\n",
    "    x = x[x[col]!='others']\n",
    "    return utils.cat_plot(x,col) + utils.thai_text(8)\n",
    "\n",
    "interact(cat_plot_noothers, df=fixed(cat_df),\n",
    "         col = widgets.Dropdown(options=list(cat_df.columns),value='gen'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Numerical and Categorical Variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>brand</th>\n",
       "      <th>series</th>\n",
       "      <th>gen</th>\n",
       "      <th>color</th>\n",
       "      <th>gear</th>\n",
       "      <th>contact_location</th>\n",
       "      <th>sales_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HONDA</td>\n",
       "      <td>others</td>\n",
       "      <td>ปี08-13</td>\n",
       "      <td>สีขาว</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "      <td>13.056226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>others</td>\n",
       "      <td>others</td>\n",
       "      <td>สีขาว</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "      <td>14.320520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HONDA</td>\n",
       "      <td>others</td>\n",
       "      <td>ปี08-13</td>\n",
       "      <td>others</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "      <td>12.669810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>FORD</td>\n",
       "      <td>others</td>\n",
       "      <td>others</td>\n",
       "      <td>สีขาว</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "      <td>13.413541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>SOLUNA</td>\n",
       "      <td>others</td>\n",
       "      <td>สีบรอนซ์เงิน</td>\n",
       "      <td>เกียร์ออโต้</td>\n",
       "      <td>กรุงเทพฯ</td>\n",
       "      <td>12.733758</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    brand  series      gen         color         gear contact_location  \\\n",
       "0   HONDA  others  ปี08-13         สีขาว  เกียร์ออโต้         กรุงเทพฯ   \n",
       "1  TOYOTA  others   others         สีขาว  เกียร์ออโต้         กรุงเทพฯ   \n",
       "2   HONDA  others  ปี08-13        others  เกียร์ออโต้         กรุงเทพฯ   \n",
       "3    FORD  others   others         สีขาว  เกียร์ออโต้         กรุงเทพฯ   \n",
       "4  TOYOTA  SOLUNA   others  สีบรอนซ์เงิน  เกียร์ออโต้         กรุงเทพฯ   \n",
       "\n",
       "   sales_price  \n",
       "0    13.056226  \n",
       "1    14.320520  \n",
       "2    12.669810  \n",
       "3    13.413541  \n",
       "4    12.733758  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#relationship between dependent variable and categorical variable\n",
    "cat_df['sales_price'] = utils.boxcox(df['sales_price'])\n",
    "cat_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>color</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>others</th>\n",
       "      <td>1756.0</td>\n",
       "      <td>12.568359</td>\n",
       "      <td>1.019319</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>12.072547</td>\n",
       "      <td>12.542548</td>\n",
       "      <td>13.028055</td>\n",
       "      <td>16.905644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>สีขาว</th>\n",
       "      <td>4207.0</td>\n",
       "      <td>13.085453</td>\n",
       "      <td>0.940839</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>12.672950</td>\n",
       "      <td>13.005832</td>\n",
       "      <td>13.498058</td>\n",
       "      <td>16.438729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>สีดำ</th>\n",
       "      <td>2848.0</td>\n",
       "      <td>13.071142</td>\n",
       "      <td>0.913027</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>12.594734</td>\n",
       "      <td>13.014780</td>\n",
       "      <td>13.535466</td>\n",
       "      <td>16.111071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>สีน้ำตาล</th>\n",
       "      <td>607.0</td>\n",
       "      <td>12.660002</td>\n",
       "      <td>0.814474</td>\n",
       "      <td>8.853808</td>\n",
       "      <td>12.144203</td>\n",
       "      <td>12.782689</td>\n",
       "      <td>13.140205</td>\n",
       "      <td>15.635210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>สีบรอนซ์เงิน</th>\n",
       "      <td>1879.0</td>\n",
       "      <td>12.760100</td>\n",
       "      <td>0.923268</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>12.421188</td>\n",
       "      <td>12.779876</td>\n",
       "      <td>13.151924</td>\n",
       "      <td>15.854130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>สีเทา</th>\n",
       "      <td>2740.0</td>\n",
       "      <td>12.786451</td>\n",
       "      <td>0.957211</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>12.421188</td>\n",
       "      <td>12.818555</td>\n",
       "      <td>13.188621</td>\n",
       "      <td>17.822480</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               count       mean       std       min        25%        50%  \\\n",
       "color                                                                       \n",
       "others        1756.0  12.568359  1.019319  0.000000  12.072547  12.542548   \n",
       "สีขาว         4207.0  13.085453  0.940839  0.000000  12.672950  13.005832   \n",
       "สีดำ          2848.0  13.071142  0.913027  0.000000  12.594734  13.014780   \n",
       "สีน้ำตาล       607.0  12.660002  0.814474  8.853808  12.144203  12.782689   \n",
       "สีบรอนซ์เงิน  1879.0  12.760100  0.923268  0.000000  12.421188  12.779876   \n",
       "สีเทา         2740.0  12.786451  0.957211  0.000000  12.421188  12.818555   \n",
       "\n",
       "                    75%        max  \n",
       "color                               \n",
       "others        13.028055  16.905644  \n",
       "สีขาว         13.498058  16.438729  \n",
       "สีดำ          13.535466  16.111071  \n",
       "สีน้ำตาล      13.140205  15.635210  \n",
       "สีบรอนซ์เงิน  13.151924  15.854130  \n",
       "สีเทา         13.188621  17.822480  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#relationship between sales price and color\n",
    "cat_df.groupby('color').sales_price.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise** Implement `numcat_plot` function that plots the relationship between a dependent numerical variable and an independent categorical as displayed above. Useful geoms are `geom_boxplot`, `geom_violin` and `geom_jitter`. Optionally remove outliers before plotting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def numcat_plot(df,num,cat, no_outliers=True, geom=geom_boxplot()):\n",
    "    return utils.numcat_plot(df,num,cat, no_outliers, geom) \n",
    "#plot the summary above"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "742ae9cc038345498ac37612c0f5298e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='cat', index=2, options=('brand', 'series', 'gen', 'color', 'gear',…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.numcat_plot(df, num, cat, no_outliers=True, geom=<plotnine.geoms.geom_boxplot.geom_boxplot object at 0x7fa9a455f358>)>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "interact(numcat_plot, \n",
    "         df=fixed(cat_df),\n",
    "         num=fixed('sales_price'),\n",
    "         no_outliers = widgets.Checkbox(value=True),\n",
    "         geom=fixed(geom_boxplot()), #geom_violin, geom_jitter\n",
    "         cat= widgets.Dropdown(options=list(cat_df.columns)[:-1],value='gen'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c9fa7bb65689470c88bc638acc54f6fa",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='cat', index=1, options=('brand', 'series', 'gen', 'color', 'gear',…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.numcat_plot(df, num, cat, no_outliers=True, geom=<plotnine.geoms.geom_boxplot.geom_boxplot object at 0x7fa9a455f358>)>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "interact(numcat_plot, \n",
    "         df=fixed(cat_df),\n",
    "         num=fixed('sales_price'),\n",
    "         no_outliers = widgets.Checkbox(value=True),\n",
    "         geom=fixed(geom_violin()), #geom_violin, geom_jitter\n",
    "         cat= widgets.Dropdown(options=list(cat_df.columns)[:-1],value='series'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sometimes we want to see the numerical distribution filled with categories. This is especially useful plotting the results of a binary classification."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8772911341765)>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def numdist_plot(df, num,cat, geom=geom_density(alpha=0.5), no_outliers=True):\n",
    "    return utils.numdist_plot(df, num, cat, geom, no_outliers)\n",
    "\n",
    "#either\n",
    "#density: geom_density(alpha=0.5)\n",
    "#histogram: geom_histogram(binwidth=0.5, position='identity',alpha=0.5) \n",
    "#position: identity or dodge\n",
    "numdist_plot(cat_df,'sales_price','gear')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8772911345542)>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numdist_plot(cat_df,'sales_price','gear',\n",
    "             geom=geom_histogram(binwidth=0.5, position='dodge',alpha=0.5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Categorical and Categorical Variables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise** We can cross-tabulate categorical variables to see their relationship by using `facet_wrap`; for instance, if our dependent variable is `gear` and indpendent variable of interest is `color`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def catcat_plot(df, cat_dep, cat_ind):\n",
    "    return utils.catcat_plot(df,cat_dep,cat_ind)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "73f24f0a4ba34645a35b8004792bb644",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='cat_dep', index=4, options=('brand', 'series', 'gen', 'color', 'ge…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.catcat_plot(df, cat_dep, cat_ind)>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "interact(catcat_plot, \n",
    "         df=fixed(cat_df),\n",
    "         cat_dep=widgets.Dropdown(options=list(cat_df.columns)[:-1],value='gear'),\n",
    "         cat_ind= widgets.Dropdown(options=list(cat_df.columns)[:-1],value='color'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Multiple Ways of Relationships"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can use `facet_grid` to display multiple ways of relationships; but keep in mind that this is probably what your model is doing anyways so it might not be most human-readable plot to explore."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/charin/anaconda3/envs/drlnd/lib/python3.6/site-packages/plotnine/stats/stat.py:310: FutureWarning: Sorting because non-concatenation axis is not aligned. A future version\n",
      "of pandas will change to not sort by default.\n",
      "\n",
      "To accept the future behavior, pass 'sort=False'.\n",
      "\n",
      "To retain the current behavior and silence the warning, pass 'sort=True'.\n",
      "\n",
      "  stats = pd.concat(stats, axis=0, ignore_index=True)\n",
      "/home/charin/anaconda3/envs/drlnd/lib/python3.6/site-packages/plotnine/utils.py:633: FutureWarning: Sorting because non-concatenation axis is not aligned. A future version\n",
      "of pandas will change to not sort by default.\n",
      "\n",
      "To accept the future behavior, pass 'sort=False'.\n",
      "\n",
      "To retain the current behavior and silence the warning, pass 'sort=True'.\n",
      "\n",
      "  return pd.concat(lst, axis=axis, ignore_index=True)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 18 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8780130226836)>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#getting fancy; not necessarily the best idea\n",
    "new_df = utils.remove_outliers(cat_df,'sales_price')\n",
    "g = (ggplot(new_df, aes(x='gen',y='sales_price')) +\n",
    "     geom_boxplot() + theme_minimal() +\n",
    "     facet_grid('contact_location~color') +\n",
    "     theme(axis_text_x = element_text(angle = 90, hjust = 1))\n",
    "    ) + utils.thai_text(8)\n",
    "g"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Numerical Variables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We want to know two things about numerical variables:\n",
    "1. Their distributions\n",
    "2. Their relationships with one another; possibly this involves transforming variables to make them less skewed aka more difficult to see variations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nb_year</th>\n",
       "      <th>sales_price</th>\n",
       "      <th>market_price</th>\n",
       "      <th>subscribers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6150.000000</td>\n",
       "      <td>6.150000e+03</td>\n",
       "      <td>6.150000e+03</td>\n",
       "      <td>6150.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.512195</td>\n",
       "      <td>7.120724e+05</td>\n",
       "      <td>1.333557e+06</td>\n",
       "      <td>525.634959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.026358</td>\n",
       "      <td>7.745356e+05</td>\n",
       "      <td>1.288468e+06</td>\n",
       "      <td>386.841217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>3.690000e+05</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.390010e+05</td>\n",
       "      <td>6.490000e+05</td>\n",
       "      <td>191.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.790010e+05</td>\n",
       "      <td>8.770000e+05</td>\n",
       "      <td>423.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>7.590010e+05</td>\n",
       "      <td>1.445000e+06</td>\n",
       "      <td>772.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>8.000000</td>\n",
       "      <td>1.297000e+07</td>\n",
       "      <td>1.645000e+07</td>\n",
       "      <td>1469.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           nb_year   sales_price  market_price  subscribers\n",
       "count  6150.000000  6.150000e+03  6.150000e+03  6150.000000\n",
       "mean      4.512195  7.120724e+05  1.333557e+06   525.634959\n",
       "std       2.026358  7.745356e+05  1.288468e+06   386.841217\n",
       "min       0.000000  1.000000e+00  3.690000e+05     1.000000\n",
       "25%       3.000000  3.390010e+05  6.490000e+05   191.250000\n",
       "50%       5.000000  4.790010e+05  8.770000e+05   423.000000\n",
       "75%       6.000000  7.590010e+05  1.445000e+06   772.000000\n",
       "max       8.000000  1.297000e+07  1.645000e+07  1469.000000"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import datetime\n",
    "now = datetime.datetime.now()\n",
    "df['nb_year'] = now.year - df['year']\n",
    "num_vars = ['nb_year','sales_price','market_price','subscribers']\n",
    "num_df = df[num_vars].dropna() #this is why you need to deal with missing values BEFORE exploration\n",
    "num_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`seaborn` has an excellent `pairplot` implementation which not only shows the distribution of values but also their relathionships. It seems like we can get what we want easily; however, as we can see `sales_price` and `market_price` are a little skewed, making it more difficult to see their relationships with other more spread out variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x7fc4c92746a0>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "sns.pairplot(num_df) #non-normal data is a problem!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In a lot of cases, a variable with normally distributed values have more variations and easier for us to see their relationships with other variables. We will try to transform our skewed variables to more \"normal\" ones to see if that helps.\n",
    "\n",
    "**Q-Q plot** compares two probability distributions by plotting their quantiles against each other. We can use this to determine the normality of a variable by plotting the sample quantiles (from the data we have) against its theoretical quantiles (where the quantiles would be if the variable is normally distributed)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ab3435b661644685b9ec84a5371e3d40",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='col', options=('nb_year', 'sales_price', 'market_price', 'subscrib…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function utils.qq_plot(df, col)>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "interact(utils.qq_plot, df=fixed(num_df),\n",
    "         col=widgets.Dropdown(options=list(num_df.columns)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Box-Cox transformation** is a statistical technique used to make data look like more normally distributed.\n",
    "\n",
    "\\begin{align}\n",
    "g_\\lambda(y) = \\left\\{\n",
    "\\begin{array}{lr}\\displaystyle\\frac{y^\\lambda - 1}{\\lambda} &  \\lambda \\neq 0\\\\\n",
    "        & \\\\\n",
    "       \\log(y) &  \\lambda = 0\n",
    "     \\end{array}\n",
    "   \\right.\n",
    "\\end{align}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise** Implement `boxcox` transformation according to the equation above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "def boxcox(ser,lamb=0):\n",
    "    pass\n",
    "#input a column from pandas dataframe\n",
    "#output transformed column"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One way of choosing the hyperparameter $\\lambda$ is to look at the Q-Q plot and choose transformation which makes the slope closest to 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2101cab964514632851ff177c84578df",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='col', index=1, options=('nb_year', 'sales_price', 'market_price', …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.what_lamb(df, col, lamb)>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#see transformation results\n",
    "def what_lamb(df,col,lamb):\n",
    "    sample_df = df.copy()\n",
    "    former_g = utils.qq_plot(sample_df,col)\n",
    "    sample_df[col] = utils.boxcox(sample_df[col],lamb)\n",
    "    print(utils.qq_plot(sample_df,col),former_g)\n",
    "    \n",
    "interact(what_lamb, df=fixed(num_df),\n",
    "         col=widgets.Dropdown(options=list(num_df.columns),value='sales_price'),\n",
    "         lamb=widgets.FloatSlider(min=-3,max=3,step=0.5,value=0)\n",
    "         )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This can also be automated by plotting a slope for each arbitary $\\lambda$; for instance from -3 to 3."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "af91486191484fd8809ab0740fe31fc3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='col', index=1, options=('nb_year', 'sales_price', 'market_price', …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function utils.boxcox_plot(df, col, ls=[-3.0, -2.5, -2.0, -1.5, -1.0, -0.5, 0.0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0])>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lamb_df = utils.boxcox_lamb_df(num_df.subscribers)\n",
    "interact(utils.boxcox_plot, df=fixed(num_df),\n",
    "         col=widgets.Dropdown(options=list(num_df.columns),value='sales_price'),\n",
    "         ls=fixed([i/10 for i in range(-30,31,5)])\n",
    "         )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "#transform sales and market prices\n",
    "for col in ['sales_price','market_price']:\n",
    "    num_df['new_'+col] = utils.boxcox(num_df[col], utils.boxcox_lamb(num_df[col]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can see that post transformation, we can see the (lack of) relationships between variables clearer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x7fc488b269e8>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(num_df[['nb_year','new_sales_price','new_market_price','subscribers']]) #a little better!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For our example, we have only four numerical variables; but imagine when you have ten or more. You may want to plot their distributions separately from relationships."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>variable</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>nb_year</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>nb_year</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>nb_year</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>nb_year</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>nb_year</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  variable  value\n",
       "0  nb_year    6.0\n",
       "1  nb_year    3.0\n",
       "2  nb_year    4.0\n",
       "3  nb_year    4.0\n",
       "4  nb_year    7.0"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_m = num_df.melt()\n",
    "num_m.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise** Implement `value_dist_plot` to plot value distribution of all variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8780130263132)>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def value_dist_plot(df,bins=30):\n",
    "    return utils.value_dist_plot(df,bins)\n",
    "#input dataframe with only numerical variables\n",
    "#output distribution plot for each variable\n",
    "value_dist_plot(num_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Likewise in case there are too many pairs of relationships, you might plot the relationships pair-by-pair with `ipywidget` and `seaborn`'s `jointplot` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f90c1b5b4b2e4af9838656fcafe52dda",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='col_x', index=1, options=('nb_year', 'sales_price', 'market_price'…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function utils.jointplot(df, col_x, col_y, no_outliers=True, kind='reg')>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "interact(utils.jointplot, df=fixed(num_df),\n",
    "         col_x= widgets.Dropdown(options=list(num_df.columns),value='sales_price'),\n",
    "         col_y=widgets.Dropdown(options=list(num_df.columns),value='market_price'),\n",
    "         kind=widgets.Dropdown(options=['scatter','resid','reg','hex','kde','point'],value='scatter'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you might have noticed, we have not used any statistical concept to describe the relationship, and that is by design. We can also see correlation table with a simple `pandas` function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "            color:  #f1f1f1;\n",
       "        }    #T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow4_col0 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow4_col1 {\n",
       "            background-color:  #c12b30;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow4_col2 {\n",
       "            background-color:  #df634e;\n",
       "            color:  #000000;\n",
       "        }    #T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow4_col3 {\n",
       "            background-color:  #4b64d5;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow4_col4 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow4_col5 {\n",
       "            background-color:  #da5a49;\n",
       "            color:  #000000;\n",
       "        }    #T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow5_col0 {\n",
       "            background-color:  #7da0f9;\n",
       "            color:  #000000;\n",
       "        }    #T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow5_col1 {\n",
       "            background-color:  #e36b54;\n",
       "            color:  #000000;\n",
       "        }    #T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow5_col2 {\n",
       "            background-color:  #c53334;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow5_col3 {\n",
       "            background-color:  #5b7ae5;\n",
       "            color:  #000000;\n",
       "        }    #T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow5_col4 {\n",
       "            background-color:  #d44e41;\n",
       "            color:  #000000;\n",
       "        }    #T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow5_col5 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }</style><table id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0b\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >nb_year</th>        <th class=\"col_heading level0 col1\" >sales_price</th>        <th class=\"col_heading level0 col2\" >market_price</th>        <th class=\"col_heading level0 col3\" >subscribers</th>        <th class=\"col_heading level0 col4\" >new_sales_price</th>        <th class=\"col_heading level0 col5\" >new_market_price</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0blevel0_row0\" class=\"row_heading level0 row0\" >nb_year</th>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow0_col0\" class=\"data row0 col0\" >1</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow0_col1\" class=\"data row0 col1\" >-0.220633</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow0_col2\" class=\"data row0 col2\" >-0.00786656</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow0_col3\" class=\"data row0 col3\" >0.163404</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow0_col4\" class=\"data row0 col4\" >-0.275434</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow0_col5\" class=\"data row0 col5\" >-0.0152819</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0blevel0_row1\" class=\"row_heading level0 row1\" >sales_price</th>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow1_col0\" class=\"data row1 col0\" >-0.220633</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow1_col1\" class=\"data row1 col1\" >1</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow1_col2\" class=\"data row1 col2\" >0.862739</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow1_col3\" class=\"data row1 col3\" >-0.07795</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow1_col4\" class=\"data row1 col4\" >0.955499</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow1_col5\" class=\"data row1 col5\" >0.819534</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0blevel0_row2\" class=\"row_heading level0 row2\" >market_price</th>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow2_col0\" class=\"data row2 col0\" >-0.00786656</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow2_col1\" class=\"data row2 col1\" >0.862739</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow2_col2\" class=\"data row2 col2\" >1</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow2_col3\" class=\"data row2 col3\" >-0.063786</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow2_col4\" class=\"data row2 col4\" >0.858924</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow2_col5\" class=\"data row2 col5\" >0.948289</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0blevel0_row3\" class=\"row_heading level0 row3\" >subscribers</th>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow3_col0\" class=\"data row3 col0\" >0.163404</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow3_col1\" class=\"data row3 col1\" >-0.07795</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow3_col2\" class=\"data row3 col2\" >-0.063786</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow3_col3\" class=\"data row3 col3\" >1</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow3_col4\" class=\"data row3 col4\" >-0.0165204</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow3_col5\" class=\"data row3 col5\" >0.039791</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0blevel0_row4\" class=\"row_heading level0 row4\" >new_sales_price</th>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow4_col0\" class=\"data row4 col0\" >-0.275434</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow4_col1\" class=\"data row4 col1\" >0.955499</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow4_col2\" class=\"data row4 col2\" >0.858924</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow4_col3\" class=\"data row4 col3\" >-0.0165204</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow4_col4\" class=\"data row4 col4\" >1</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow4_col5\" class=\"data row4 col5\" >0.882803</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0blevel0_row5\" class=\"row_heading level0 row5\" >new_market_price</th>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow5_col0\" class=\"data row5 col0\" >-0.0152819</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow5_col1\" class=\"data row5 col1\" >0.819534</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow5_col2\" class=\"data row5 col2\" >0.948289</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow5_col3\" class=\"data row5 col3\" >0.039791</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow5_col4\" class=\"data row5 col4\" >0.882803</td>\n",
       "                        <td id=\"T_1d00e18a_85e2_11e9_b01d_1d76819b2e0brow5_col5\" class=\"data row5 col5\" >1</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fc488766d68>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#correlation plot if you must; but it's just ONE number for the relationship\n",
    "num_df.corr(method='pearson').style.background_gradient(cmap='coolwarm') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.23316757399518453"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def pearson_corr(x,y):\n",
    "    sub_x = x - x.mean()\n",
    "    sub_y = y - y.mean()\n",
    "    return (sub_x * sub_y).sum() / np.sqrt((sub_x**2).sum() * (sub_y**2).sum())\n",
    "\n",
    "#spearman and kendall: pearson with rank variables\n",
    "pearson_corr(df.nb_year,df.sales_price)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, the famous Anscombe plots show us that it is always better to look at distribution rather than a summary number.\n",
    "\n",
    "![Anscombe's Quartet](images/anscombe.png)\n",
    "\n",
    "Source: [A Comprehensive Guide to the Grammar of Graphics for Effective Visualization of Multi-dimensional Data](https://towardsdatascience.com/a-comprehensive-guide-to-the-grammar-of-graphics-for-effective-visualization-of-multi-dimensional-1f92b4ed4149)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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