T1-3-Data Cleaning-Plots.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=pd.read_csv('../GitHub/python-ml-course/datasets/customer-churn-model/Customer Churn Model.txt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>State</th>\n",
       "      <th>Account Length</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Phone</th>\n",
       "      <th>Int'l Plan</th>\n",
       "      <th>VMail Plan</th>\n",
       "      <th>VMail Message</th>\n",
       "      <th>Day Mins</th>\n",
       "      <th>Day Calls</th>\n",
       "      <th>Day Charge</th>\n",
       "      <th>...</th>\n",
       "      <th>Eve Calls</th>\n",
       "      <th>Eve Charge</th>\n",
       "      <th>Night Mins</th>\n",
       "      <th>Night Calls</th>\n",
       "      <th>Night Charge</th>\n",
       "      <th>Intl Mins</th>\n",
       "      <th>Intl Calls</th>\n",
       "      <th>Intl Charge</th>\n",
       "      <th>CustServ Calls</th>\n",
       "      <th>Churn?</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3328</th>\n",
       "      <td>AZ</td>\n",
       "      <td>192</td>\n",
       "      <td>415</td>\n",
       "      <td>414-4276</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>36</td>\n",
       "      <td>156.2</td>\n",
       "      <td>77</td>\n",
       "      <td>26.55</td>\n",
       "      <td>...</td>\n",
       "      <td>126</td>\n",
       "      <td>18.32</td>\n",
       "      <td>279.1</td>\n",
       "      <td>83</td>\n",
       "      <td>12.56</td>\n",
       "      <td>9.9</td>\n",
       "      <td>6</td>\n",
       "      <td>2.67</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3329</th>\n",
       "      <td>WV</td>\n",
       "      <td>68</td>\n",
       "      <td>415</td>\n",
       "      <td>370-3271</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>231.1</td>\n",
       "      <td>57</td>\n",
       "      <td>39.29</td>\n",
       "      <td>...</td>\n",
       "      <td>55</td>\n",
       "      <td>13.04</td>\n",
       "      <td>191.3</td>\n",
       "      <td>123</td>\n",
       "      <td>8.61</td>\n",
       "      <td>9.6</td>\n",
       "      <td>4</td>\n",
       "      <td>2.59</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3330</th>\n",
       "      <td>RI</td>\n",
       "      <td>28</td>\n",
       "      <td>510</td>\n",
       "      <td>328-8230</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>180.8</td>\n",
       "      <td>109</td>\n",
       "      <td>30.74</td>\n",
       "      <td>...</td>\n",
       "      <td>58</td>\n",
       "      <td>24.55</td>\n",
       "      <td>191.9</td>\n",
       "      <td>91</td>\n",
       "      <td>8.64</td>\n",
       "      <td>14.1</td>\n",
       "      <td>6</td>\n",
       "      <td>3.81</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3331</th>\n",
       "      <td>CT</td>\n",
       "      <td>184</td>\n",
       "      <td>510</td>\n",
       "      <td>364-6381</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>213.8</td>\n",
       "      <td>105</td>\n",
       "      <td>36.35</td>\n",
       "      <td>...</td>\n",
       "      <td>84</td>\n",
       "      <td>13.57</td>\n",
       "      <td>139.2</td>\n",
       "      <td>137</td>\n",
       "      <td>6.26</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10</td>\n",
       "      <td>1.35</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3332</th>\n",
       "      <td>TN</td>\n",
       "      <td>74</td>\n",
       "      <td>415</td>\n",
       "      <td>400-4344</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>25</td>\n",
       "      <td>234.4</td>\n",
       "      <td>113</td>\n",
       "      <td>39.85</td>\n",
       "      <td>...</td>\n",
       "      <td>82</td>\n",
       "      <td>22.60</td>\n",
       "      <td>241.4</td>\n",
       "      <td>77</td>\n",
       "      <td>10.86</td>\n",
       "      <td>13.7</td>\n",
       "      <td>4</td>\n",
       "      <td>3.70</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     State  Account Length  Area Code     Phone Int'l Plan VMail Plan  \\\n",
       "3328    AZ             192        415  414-4276         no        yes   \n",
       "3329    WV              68        415  370-3271         no         no   \n",
       "3330    RI              28        510  328-8230         no         no   \n",
       "3331    CT             184        510  364-6381        yes         no   \n",
       "3332    TN              74        415  400-4344         no        yes   \n",
       "\n",
       "      VMail Message  Day Mins  Day Calls  Day Charge  ...  Eve Calls  \\\n",
       "3328             36     156.2         77       26.55  ...        126   \n",
       "3329              0     231.1         57       39.29  ...         55   \n",
       "3330              0     180.8        109       30.74  ...         58   \n",
       "3331              0     213.8        105       36.35  ...         84   \n",
       "3332             25     234.4        113       39.85  ...         82   \n",
       "\n",
       "      Eve Charge  Night Mins  Night Calls  Night Charge  Intl Mins  \\\n",
       "3328       18.32       279.1           83         12.56        9.9   \n",
       "3329       13.04       191.3          123          8.61        9.6   \n",
       "3330       24.55       191.9           91          8.64       14.1   \n",
       "3331       13.57       139.2          137          6.26        5.0   \n",
       "3332       22.60       241.4           77         10.86       13.7   \n",
       "\n",
       "      Intl Calls  Intl Charge  CustServ Calls  Churn?  \n",
       "3328           6         2.67               2  False.  \n",
       "3329           4         2.59               3  False.  \n",
       "3330           6         3.81               2  False.  \n",
       "3331          10         1.35               2  False.  \n",
       "3332           4         3.70               0  False.  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3333, 21)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scatter plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa024868358>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plot(kind='scatter',x=\"Day Mins\",y=\"Day Charge\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa0227a3208>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plot(kind='scatter',x=\"Night Mins\",y=\"Night Charge\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Creando la figura y los ejes (fig, axes). Se pueden nombrar los ejes directamente y no necesariamente con las posiciones de los paneles.\n",
    "\n",
    "**- fig,[ax1,ax2]=plt.subplots(1,2). Por cada fila se genera una lista con los axes**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa022269ef0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure,[[ax1,ax2],[ax3,ax4]]=plt.subplots(2,2,sharex=True,sharey=True)\n",
    "data.plot(kind='scatter',x='Day Mins',y='Day Charge',ax=ax1)\n",
    "data.plot(kind='scatter',x='Night Mins',y='Night Charge',ax=ax2)\n",
    "data.plot(kind='scatter',x='Day Calls',y='Day Charge',ax=ax3)\n",
    "data.plot(kind='scatter',x='Night Calls',y='Night Charge',ax=ax4)\n",
    "\n",
    "# ax2.set_xlabel(\"Day mins\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Histogramas de frecuencias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para conocer el número de bins que se debe usar se aplica la regla de Sturges\n",
    "\n",
    "\\begin{equation}\n",
    "bins=1+log_{2}(M)\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Histograma del número de llamadas al día')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "b=int(np.ceil(1+np.log2(data.shape[0]))) #np.ceil para redondear por encima \n",
    "plt.hist(data['Day Calls'],bins=b)\n",
    "plt.xlabel(\"Day Calls\")\n",
    "plt.ylabel(\"Frecuencias\")\n",
    "plt.title(\"Histograma del número de llamadas al día\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Diagrama de caja y bigotes (boxplot)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- El borde inferior de la caja define el percentil 25\n",
    "- El borde superior de la caja define el percentil 75\n",
    "- La línea amarilla es el percentil 50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Boxplot de las llamadas diarias')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.boxplot(data[\"Day Calls\"])\n",
    "plt.ylabel(\"Número de llamadas diarias\")\n",
    "plt.title(\"Boxplot de las llamadas diarias\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La altura de la caja es la resta entre el percentil 75 y el percentil 25. Se llama rango interquantilico (Inter quantil range, IQR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "data[\"Day Calls\"].describe()\n",
    "IQR=data[\"Day Calls\"].quantile(0.75)-data[\"Day Calls\"].quantile(0.25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para el ejemplo, el IQR es igual a {{IQR}}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Los bigotes se colocan a 1.5 veces el IQR tanto desde el cuantil 25 como del 75. Todos los valores que queden por fuera de estos bigotes se consideran outliers y se marcan con 'o'. Estos datos tienen esta condición fruto de un error en la medición o de condiciones específicas que lo generaron *(Es importante revisar su origen)*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(46.5, 154.5)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigote_inf=data[\"Day Calls\"].quantile(0.25)-1.5*IQR\n",
    "bigote_sup=data[\"Day Calls\"].quantile(0.75)+1.5*IQR\n",
    "\n",
    "bigote_inf,bigote_sup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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