Log transformation-reduce impact of outlier (1).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "77b2982e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Import Libraries \n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import pandas as pd "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a0964bc0",
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>29.03</td>\n",
       "      <td>5.92</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>27.18</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>22.67</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>17.82</td>\n",
       "      <td>1.75</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>18.78</td>\n",
       "      <td>3.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Thur</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>244 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     total_bill   tip     sex smoker   day    time  size\n",
       "0         16.99  1.01  Female     No   Sun  Dinner     2\n",
       "1         10.34  1.66    Male     No   Sun  Dinner     3\n",
       "2         21.01  3.50    Male     No   Sun  Dinner     3\n",
       "3         23.68  3.31    Male     No   Sun  Dinner     2\n",
       "4         24.59  3.61  Female     No   Sun  Dinner     4\n",
       "..          ...   ...     ...    ...   ...     ...   ...\n",
       "239       29.03  5.92    Male     No   Sat  Dinner     3\n",
       "240       27.18  2.00  Female    Yes   Sat  Dinner     2\n",
       "241       22.67  2.00    Male    Yes   Sat  Dinner     2\n",
       "242       17.82  1.75    Male     No   Sat  Dinner     2\n",
       "243       18.78  3.00  Female     No  Thur  Dinner     2\n",
       "\n",
       "[244 rows x 7 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Load Data Set and make a copy \n",
    "tips =sns.load_dataset('tips')\n",
    "tips1= tips\n",
    "tips1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c7f9a60b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='day', ylabel='total_bill'>"
      ]
     },
     "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": [
    "#Create Box plot to check outliers\n",
    "sns.boxplot (data = tips1 , x = 'day', y = 'total_bill' )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "06338c45",
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>244.000000</td>\n",
       "      <td>244.000000</td>\n",
       "      <td>244.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>19.785943</td>\n",
       "      <td>2.998279</td>\n",
       "      <td>2.569672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>8.902412</td>\n",
       "      <td>1.383638</td>\n",
       "      <td>0.951100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>3.070000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>13.347500</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>17.795000</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>24.127500</td>\n",
       "      <td>3.562500</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>50.810000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       total_bill         tip        size\n",
       "count  244.000000  244.000000  244.000000\n",
       "mean    19.785943    2.998279    2.569672\n",
       "std      8.902412    1.383638    0.951100\n",
       "min      3.070000    1.000000    1.000000\n",
       "25%     13.347500    2.000000    2.000000\n",
       "50%     17.795000    2.900000    2.000000\n",
       "75%     24.127500    3.562500    3.000000\n",
       "max     50.810000   10.000000    6.000000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tips1.describe()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "87115b7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "#Apply log Transformation to address outliers \n",
    "tips1['total_bill'] = np.log10(tips1['total_bill'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "fe235442",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='day', ylabel='total_bill'>"
      ]
     },
     "execution_count": 10,
     "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": [
    "\n",
    "#Create box plot and check outlier again \n",
    "sns.boxplot (data = tips1 , x = 'day', y = 'total_bill' )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "15d1d158",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}