3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Importing pandas module "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "# keyword module_name as alias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_col = ['Age', 'Sex','Location'] # column list \n",
    "my_idx = ['Yash','Sakashi','Kunal'] # index list\n",
    "my_data = [[20, 'male', 'pune'],\n",
    "           [19, 'female', 'pune'],\n",
    "           [21, 'male', 'pune'],\n",
    "          ]# data list"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Syntax :- \n",
    "DataFrameObject = pd.DataFrame(data = data_list, index = idx_list, coloumns = col_list ) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(data = my_data, index = my_idx, columns = my_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>Age</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Yash</th>\n",
       "      <td>20</td>\n",
       "      <td>male</td>\n",
       "      <td>pune</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sakashi</th>\n",
       "      <td>19</td>\n",
       "      <td>female</td>\n",
       "      <td>pune</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kunal</th>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>pune</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Age     Sex Location\n",
       "Yash      20    male     pune\n",
       "Sakashi   19  female     pune\n",
       "Kunal     21    male     pune"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.8.6 64-bit",
   "language": "python",
   "name": "python38664bit4822670b26e8438dbb2f63c7f38ab160"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}