{ "cells": [ { "cell_type": "markdown", "id": "92f5ec54", "metadata": {}, "source": [ "## Reseting Index of Dataframe" ] }, { "cell_type": "code", "execution_count": 1, "id": "06e8f3f1", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 2, "id": "c8470dfc", "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>Name</th>\n", " <th>Age</th>\n", " <th>Gender</th>\n", " <th>City</th>\n", " <th>Place of Work</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>Sahil Choudhary</td>\n", " <td>10</td>\n", " <td>M</td>\n", " <td>J</td>\n", " <td>True</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>Sonia Choudhary</td>\n", " <td>20</td>\n", " <td>F</td>\n", " <td>K</td>\n", " <td>False</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>Sourav</td>\n", " <td>30</td>\n", " <td>M</td>\n", " <td>L</td>\n", " <td>False</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>Vishal</td>\n", " <td>40</td>\n", " <td>M</td>\n", " <td>P</td>\n", " <td>True</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Name Age Gender City Place of Work\n", "0 Sahil Choudhary 10 M J True\n", "1 Sonia Choudhary 20 F K False\n", "2 Sourav 30 M L False\n", "3 Vishal 40 M P True" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df=pd.DataFrame({\n", "'Name':['Sahil Choudhary','Sonia Choudhary','Sourav','Vishal'],\n", "'Age':[10,20,30,40],\n", "'Gender':['M','F','M','M'],\n", "'City':['J','K','L','P'],\n", "'Work':[True,False,False,True]\n", "}\n", ")\n", "df" ] }, { "cell_type": "code", "execution_count": 3, "id": "3ea773ac", "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>Name</th>\n", " <th>Age</th>\n", " <th>Gender</th>\n", " <th>City</th>\n", " <th>Place of Work</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>Sahil Choudhary</td>\n", " <td>10</td>\n", " <td>M</td>\n", " <td>J</td>\n", " <td>True</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>Sonia Choudhary</td>\n", " <td>20</td>\n", " <td>F</td>\n", " <td>K</td>\n", " <td>False</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>Sourav</td>\n", " <td>30</td>\n", " <td>M</td>\n", " <td>L</td>\n", " <td>False</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>Vishal</td>\n", " <td>40</td>\n", " <td>M</td>\n", " <td>P</td>\n", " <td>True</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Name Age Gender City Place of Work\n", "0 Sahil Choudhary 10 M J True\n", "1 Sonia Choudhary 20 F K False\n", "2 Sourav 30 M L False\n", "3 Vishal 40 M P True" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.reset_index(drop=True)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.8.8" } }, "nbformat": 4, "nbformat_minor": 5 }