session - 1 packages and basic.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b7d8172",
   "metadata": {},
   "outputs": [],
   "source": [
    "###########################PACKAGES###############################\n",
    "*****************************EDA**********************************\n",
    "1) pandas : Data frames analysis\n",
    "2) numpy  : Numerical python/Number python[maths]\n",
    "3) matplotlib : plot\n",
    "4) seaborn\n",
    "5) plotly\n",
    "6) bokhe\n",
    "\n",
    "***************************ML PACKAGES****************************\n",
    "7) scikit-learn(sklearn)\n",
    "8) pickle: save the ml model\n",
    "9) joblib : save the ml model\n",
    "    \n",
    "********************************DL PACKAGES*************************\n",
    "10) Tenserflow\n",
    "11) Kears\n",
    "12) pytorch\n",
    "\n",
    "*****************************NLP PACKAGES***********************\n",
    "13) NLTK\n",
    "14) scipy\n",
    "\n",
    "******************************BERT MODEL(Hugging face transfromers)******\n",
    "15) Transfromers\n",
    "**************************GEN AI*************************************\n",
    "16) chatgpt : openai+ Azure    : Azure packet seperately\n",
    "17) makersuit: google          : google packages\n",
    "18) Amazon Q  : Amazon         : AWS packages\n",
    "        \n",
    "**************OTHERS***********************************************\n",
    "random\n",
    "math\n",
    "time\n",
    "sys\n",
    "os"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd685bb8",
   "metadata": {},
   "source": [
    "$STEP:-1$\n",
    "\n",
    "**Import Required Packages**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9d58ca43",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "723ee6b2",
   "metadata": {},
   "source": [
    "$STEP:-2$\n",
    "    \n",
    "**Read the Data**\n",
    "\n",
    "**Visa Dataset**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e820fce7",
   "metadata": {},
   "outputs": [],
   "source": [
    "file_path=\"C:\\\\Users\\\\hp\\\\Downloads\\\\Visadataset - Visadataset.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "824a4abc",
   "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>case_id</th>\n",
       "      <th>continent</th>\n",
       "      <th>education_of_employee</th>\n",
       "      <th>has_job_experience</th>\n",
       "      <th>requires_job_training</th>\n",
       "      <th>no_of_employees</th>\n",
       "      <th>yr_of_estab</th>\n",
       "      <th>region_of_employment</th>\n",
       "      <th>prevailing_wage</th>\n",
       "      <th>unit_of_wage</th>\n",
       "      <th>full_time_position</th>\n",
       "      <th>case_status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>EZYV01</td>\n",
       "      <td>Asia</td>\n",
       "      <td>High School</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>14513</td>\n",
       "      <td>2007</td>\n",
       "      <td>West</td>\n",
       "      <td>592.2029</td>\n",
       "      <td>Hour</td>\n",
       "      <td>Y</td>\n",
       "      <td>Denied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>EZYV02</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Master's</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "      <td>2412</td>\n",
       "      <td>2002</td>\n",
       "      <td>Northeast</td>\n",
       "      <td>83425.6500</td>\n",
       "      <td>Year</td>\n",
       "      <td>Y</td>\n",
       "      <td>Certified</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>EZYV03</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Bachelor's</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>44444</td>\n",
       "      <td>2008</td>\n",
       "      <td>West</td>\n",
       "      <td>122996.8600</td>\n",
       "      <td>Year</td>\n",
       "      <td>Y</td>\n",
       "      <td>Denied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>EZYV04</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Bachelor's</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>98</td>\n",
       "      <td>1897</td>\n",
       "      <td>West</td>\n",
       "      <td>83434.0300</td>\n",
       "      <td>Year</td>\n",
       "      <td>Y</td>\n",
       "      <td>Denied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>EZYV05</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Master's</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "      <td>1082</td>\n",
       "      <td>2005</td>\n",
       "      <td>South</td>\n",
       "      <td>149907.3900</td>\n",
       "      <td>Year</td>\n",
       "      <td>Y</td>\n",
       "      <td>Certified</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25475</th>\n",
       "      <td>EZYV25476</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Bachelor's</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>2601</td>\n",
       "      <td>2008</td>\n",
       "      <td>South</td>\n",
       "      <td>77092.5700</td>\n",
       "      <td>Year</td>\n",
       "      <td>Y</td>\n",
       "      <td>Certified</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25476</th>\n",
       "      <td>EZYV25477</td>\n",
       "      <td>Asia</td>\n",
       "      <td>High School</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "      <td>3274</td>\n",
       "      <td>2006</td>\n",
       "      <td>Northeast</td>\n",
       "      <td>279174.7900</td>\n",
       "      <td>Year</td>\n",
       "      <td>Y</td>\n",
       "      <td>Certified</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25477</th>\n",
       "      <td>EZYV25478</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Master's</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "      <td>1121</td>\n",
       "      <td>1910</td>\n",
       "      <td>South</td>\n",
       "      <td>146298.8500</td>\n",
       "      <td>Year</td>\n",
       "      <td>N</td>\n",
       "      <td>Certified</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25478</th>\n",
       "      <td>EZYV25479</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Master's</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>1918</td>\n",
       "      <td>1887</td>\n",
       "      <td>West</td>\n",
       "      <td>86154.7700</td>\n",
       "      <td>Year</td>\n",
       "      <td>Y</td>\n",
       "      <td>Certified</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25479</th>\n",
       "      <td>EZYV25480</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Bachelor's</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "      <td>3195</td>\n",
       "      <td>1960</td>\n",
       "      <td>Midwest</td>\n",
       "      <td>70876.9100</td>\n",
       "      <td>Year</td>\n",
       "      <td>Y</td>\n",
       "      <td>Certified</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25480 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         case_id continent education_of_employee has_job_experience  \\\n",
       "0         EZYV01      Asia           High School                  N   \n",
       "1         EZYV02      Asia              Master's                  Y   \n",
       "2         EZYV03      Asia            Bachelor's                  N   \n",
       "3         EZYV04      Asia            Bachelor's                  N   \n",
       "4         EZYV05    Africa              Master's                  Y   \n",
       "...          ...       ...                   ...                ...   \n",
       "25475  EZYV25476      Asia            Bachelor's                  Y   \n",
       "25476  EZYV25477      Asia           High School                  Y   \n",
       "25477  EZYV25478      Asia              Master's                  Y   \n",
       "25478  EZYV25479      Asia              Master's                  Y   \n",
       "25479  EZYV25480      Asia            Bachelor's                  Y   \n",
       "\n",
       "      requires_job_training  no_of_employees  yr_of_estab  \\\n",
       "0                         N            14513         2007   \n",
       "1                         N             2412         2002   \n",
       "2                         Y            44444         2008   \n",
       "3                         N               98         1897   \n",
       "4                         N             1082         2005   \n",
       "...                     ...              ...          ...   \n",
       "25475                     Y             2601         2008   \n",
       "25476                     N             3274         2006   \n",
       "25477                     N             1121         1910   \n",
       "25478                     Y             1918         1887   \n",
       "25479                     N             3195         1960   \n",
       "\n",
       "      region_of_employment  prevailing_wage unit_of_wage full_time_position  \\\n",
       "0                     West         592.2029         Hour                  Y   \n",
       "1                Northeast       83425.6500         Year                  Y   \n",
       "2                     West      122996.8600         Year                  Y   \n",
       "3                     West       83434.0300         Year                  Y   \n",
       "4                    South      149907.3900         Year                  Y   \n",
       "...                    ...              ...          ...                ...   \n",
       "25475                South       77092.5700         Year                  Y   \n",
       "25476            Northeast      279174.7900         Year                  Y   \n",
       "25477                South      146298.8500         Year                  N   \n",
       "25478                 West       86154.7700         Year                  Y   \n",
       "25479              Midwest       70876.9100         Year                  Y   \n",
       "\n",
       "      case_status  \n",
       "0          Denied  \n",
       "1       Certified  \n",
       "2          Denied  \n",
       "3          Denied  \n",
       "4       Certified  \n",
       "...           ...  \n",
       "25475   Certified  \n",
       "25476   Certified  \n",
       "25477   Certified  \n",
       "25478   Certified  \n",
       "25479   Certified  \n",
       "\n",
       "[25480 rows x 12 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# <packages_names>.<method_name>()\n",
    "pd.read_csv(file_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c1e31c3e",
   "metadata": {},
   "outputs": [],
   "source": [
    "f1=\"C:\\\\Users\\\\hp\\\\Downloads\\\\bank.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "604eade5",
   "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>job</th>\n",
       "      <th>marital</th>\n",
       "      <th>education</th>\n",
       "      <th>default</th>\n",
       "      <th>balance</th>\n",
       "      <th>housing</th>\n",
       "      <th>loan</th>\n",
       "      <th>contact</th>\n",
       "      <th>day</th>\n",
       "      <th>month</th>\n",
       "      <th>duration</th>\n",
       "      <th>campaign</th>\n",
       "      <th>pdays</th>\n",
       "      <th>previous</th>\n",
       "      <th>poutcome</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>30</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>married</td>\n",
       "      <td>primary</td>\n",
       "      <td>no</td>\n",
       "      <td>1787</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>19</td>\n",
       "      <td>oct</td>\n",
       "      <td>79</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>unknown</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>33</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>secondary</td>\n",
       "      <td>no</td>\n",
       "      <td>4789</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>cellular</td>\n",
       "      <td>11</td>\n",
       "      <td>may</td>\n",
       "      <td>220</td>\n",
       "      <td>1</td>\n",
       "      <td>339</td>\n",
       "      <td>4</td>\n",
       "      <td>failure</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>35</td>\n",
       "      <td>management</td>\n",
       "      <td>single</td>\n",
       "      <td>tertiary</td>\n",
       "      <td>no</td>\n",
       "      <td>1350</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>16</td>\n",
       "      <td>apr</td>\n",
       "      <td>185</td>\n",
       "      <td>1</td>\n",
       "      <td>330</td>\n",
       "      <td>1</td>\n",
       "      <td>failure</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>30</td>\n",
       "      <td>management</td>\n",
       "      <td>married</td>\n",
       "      <td>tertiary</td>\n",
       "      <td>no</td>\n",
       "      <td>1476</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>unknown</td>\n",
       "      <td>3</td>\n",
       "      <td>jun</td>\n",
       "      <td>199</td>\n",
       "      <td>4</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>unknown</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>59</td>\n",
       "      <td>blue-collar</td>\n",
       "      <td>married</td>\n",
       "      <td>secondary</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>unknown</td>\n",
       "      <td>5</td>\n",
       "      <td>may</td>\n",
       "      <td>226</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>unknown</td>\n",
       "      <td>no</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\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>4516</th>\n",
       "      <td>33</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>secondary</td>\n",
       "      <td>no</td>\n",
       "      <td>-333</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>30</td>\n",
       "      <td>jul</td>\n",
       "      <td>329</td>\n",
       "      <td>5</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>unknown</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4517</th>\n",
       "      <td>57</td>\n",
       "      <td>self-employed</td>\n",
       "      <td>married</td>\n",
       "      <td>tertiary</td>\n",
       "      <td>yes</td>\n",
       "      <td>-3313</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>unknown</td>\n",
       "      <td>9</td>\n",
       "      <td>may</td>\n",
       "      <td>153</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>unknown</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4518</th>\n",
       "      <td>57</td>\n",
       "      <td>technician</td>\n",
       "      <td>married</td>\n",
       "      <td>secondary</td>\n",
       "      <td>no</td>\n",
       "      <td>295</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>19</td>\n",
       "      <td>aug</td>\n",
       "      <td>151</td>\n",
       "      <td>11</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>unknown</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4519</th>\n",
       "      <td>28</td>\n",
       "      <td>blue-collar</td>\n",
       "      <td>married</td>\n",
       "      <td>secondary</td>\n",
       "      <td>no</td>\n",
       "      <td>1137</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>6</td>\n",
       "      <td>feb</td>\n",
       "      <td>129</td>\n",
       "      <td>4</td>\n",
       "      <td>211</td>\n",
       "      <td>3</td>\n",
       "      <td>other</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4520</th>\n",
       "      <td>44</td>\n",
       "      <td>entrepreneur</td>\n",
       "      <td>single</td>\n",
       "      <td>tertiary</td>\n",
       "      <td>no</td>\n",
       "      <td>1136</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>cellular</td>\n",
       "      <td>3</td>\n",
       "      <td>apr</td>\n",
       "      <td>345</td>\n",
       "      <td>2</td>\n",
       "      <td>249</td>\n",
       "      <td>7</td>\n",
       "      <td>other</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4521 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      age            job  marital  education default  balance housing loan  \\\n",
       "0      30     unemployed  married    primary      no     1787      no   no   \n",
       "1      33       services  married  secondary      no     4789     yes  yes   \n",
       "2      35     management   single   tertiary      no     1350     yes   no   \n",
       "3      30     management  married   tertiary      no     1476     yes  yes   \n",
       "4      59    blue-collar  married  secondary      no        0     yes   no   \n",
       "...   ...            ...      ...        ...     ...      ...     ...  ...   \n",
       "4516   33       services  married  secondary      no     -333     yes   no   \n",
       "4517   57  self-employed  married   tertiary     yes    -3313     yes  yes   \n",
       "4518   57     technician  married  secondary      no      295      no   no   \n",
       "4519   28    blue-collar  married  secondary      no     1137      no   no   \n",
       "4520   44   entrepreneur   single   tertiary      no     1136     yes  yes   \n",
       "\n",
       "       contact  day month  duration  campaign  pdays  previous poutcome   y  \n",
       "0     cellular   19   oct        79         1     -1         0  unknown  no  \n",
       "1     cellular   11   may       220         1    339         4  failure  no  \n",
       "2     cellular   16   apr       185         1    330         1  failure  no  \n",
       "3      unknown    3   jun       199         4     -1         0  unknown  no  \n",
       "4      unknown    5   may       226         1     -1         0  unknown  no  \n",
       "...        ...  ...   ...       ...       ...    ...       ...      ...  ..  \n",
       "4516  cellular   30   jul       329         5     -1         0  unknown  no  \n",
       "4517   unknown    9   may       153         1     -1         0  unknown  no  \n",
       "4518  cellular   19   aug       151        11     -1         0  unknown  no  \n",
       "4519  cellular    6   feb       129         4    211         3    other  no  \n",
       "4520  cellular    3   apr       345         2    249         7    other  no  \n",
       "\n",
       "[4521 rows x 17 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv(f1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9cf85591",
   "metadata": {},
   "source": [
    "$STEP:-3$\n",
    "    \n",
    "**Create Data Frames**\n",
    "- A) Using list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3f72e38f",
   "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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ajinkya</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Deepak</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sairaj</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rohan</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mani</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Name  Age\n",
       "0  Ajinkya   23\n",
       "1   Deepak   24\n",
       "2   Sairaj   25\n",
       "3    Rohan   20\n",
       "4     Mani   22"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list1=[\"Ajinkya\",\"Deepak\",\"Sairaj\",\"Rohan\",\"Mani\"]\n",
    "list2=[23,24,25,20,22]\n",
    "cols=['Name','Age']\n",
    "name=pd.DataFrame(zip(list1,list2),columns=cols)\n",
    "name\n",
    "# I created a dataframes and i saved in a variables names"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b9eba55",
   "metadata": {},
   "source": [
    "- B) Save the Data in local "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4348cd18",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\hp\\\\OneDrive\\\\Documents\\\\EDA session'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os\n",
    "os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e62a9148",
   "metadata": {},
   "outputs": [],
   "source": [
    "name.to_csv('friends_names.csv')\n",
    "\n",
    "# extra index column created"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "459a2475",
   "metadata": {},
   "outputs": [],
   "source": [
    "name.to_csv(\"C:\\\\Users\\\\hp\\\\OneDrive\\\\Pictures\\\\Screenshots\\\\friends1_name.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e0e227ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "name.to_csv('friends_name.csv',index=False)\n",
    "# there is no extra index column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6cf3b56d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# In fille handling we read the file in two ways\n",
    "# python file and data file both are different location \n",
    "#      we need to provide the full path \n",
    "\n",
    "# python - file and data file both are in same location \n",
    "\n",
    "#    we  provide only data data file names"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f25713d",
   "metadata": {},
   "source": [
    "- we create a dataframes using list data frames name : name\n",
    "- we saved the dataframes in local with index: friends_name.csv\n",
    "- we saved the dataframes in local without index: friends1_name.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d46e2b9a",
   "metadata": {},
   "source": [
    "$Task:-1$\n",
    "\n",
    "- read the two dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "8fd78963",
   "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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ajinkya</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Deepak</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sairaj</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rohan</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mani</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Name  Age\n",
       "0  Ajinkya   23\n",
       "1   Deepak   24\n",
       "2   Sairaj   25\n",
       "3    Rohan   20\n",
       "4     Mani   22"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# python files and datafiles are at same location \n",
    "# no need to provide full path location\n",
    "pd.read_csv('friends_name.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1c6a17f8",
   "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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Ajinkya</th>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Deepak</th>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sairaj</th>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rohan</th>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mani</th>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Age\n",
       "Name        \n",
       "Ajinkya   23\n",
       "Deepak    24\n",
       "Sairaj    25\n",
       "Rohan     20\n",
       "Mani      22"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('friends_name.csv',index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c0c42259",
   "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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ajinkya</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Deepak</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sairaj</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rohan</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mani</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Name  Age\n",
       "0  Ajinkya   23\n",
       "1   Deepak   24\n",
       "2   Sairaj   25\n",
       "3    Rohan   20\n",
       "4     Mani   22"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('friends_name.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b3cd5ac7",
   "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>Unnamed: 0</th>\n",
       "      <th>Name</th>\n",
       "      <th>Age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Ajinkya</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Deepak</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Sairaj</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Rohan</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Mani</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0     Name  Age\n",
       "0           0  Ajinkya   23\n",
       "1           1   Deepak   24\n",
       "2           2   Sairaj   25\n",
       "3           3    Rohan   20\n",
       "4           4     Mani   22"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('C:\\\\Users\\\\hp\\\\OneDrive\\\\Pictures\\\\Screenshots\\\\friends1_name.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e7696a13",
   "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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ajinkya</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Deepak</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sairaj</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rohan</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mani</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Name  Age\n",
       "0  Ajinkya   23\n",
       "1   Deepak   24\n",
       "2   Sairaj   25\n",
       "3    Rohan   20\n",
       "4     Mani   22"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('C:\\\\Users\\\\hp\\\\OneDrive\\\\Pictures\\\\Screenshots\\\\friends1_name.csv',index_col=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea4b171f",
   "metadata": {},
   "source": [
    "- Changes the Index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e9006d5f",
   "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>Names</th>\n",
       "      <th>Ages</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>Ajinkya</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>Deepak</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>Sairaj</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D</th>\n",
       "      <td>Rohan</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>Mani</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Names  Ages\n",
       "A  Ajinkya    23\n",
       "B   Deepak    24\n",
       "C   Sairaj    25\n",
       "D    Rohan    20\n",
       "E     Mani    22"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list1=[\"Ajinkya\",\"Deepak\",\"Sairaj\",\"Rohan\",\"Mani\"]\n",
    "list2=[23,24,25,20,22]\n",
    "cols=['Names','Ages']\n",
    "name=pd.DataFrame(zip(list1,list2),columns=cols,index=['A','B','C','D','E'])\n",
    "name"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f3b3f90",
   "metadata": {},
   "source": [
    "- D) Add to new column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b9a10bd4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# what is your dataframes name: name\n",
    "# what  is the new column that you want to add: city\n",
    "# how many rows in your data: 5\n",
    "# what is the new values of city:['Nagpur','Navi mumbai','Satara','Patna','Andhra Pradesh']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "701be5b5",
   "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>Names</th>\n",
       "      <th>Ages</th>\n",
       "      <th>city</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>Ajinkya</td>\n",
       "      <td>23</td>\n",
       "      <td>Nagpur</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>Deepak</td>\n",
       "      <td>24</td>\n",
       "      <td>Navi mumbai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>Sairaj</td>\n",
       "      <td>25</td>\n",
       "      <td>Satara</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D</th>\n",
       "      <td>Rohan</td>\n",
       "      <td>20</td>\n",
       "      <td>Patna</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>Mani</td>\n",
       "      <td>22</td>\n",
       "      <td>Andhra Pradesh</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Names  Ages            city\n",
       "A  Ajinkya    23          Nagpur\n",
       "B   Deepak    24     Navi mumbai\n",
       "C   Sairaj    25          Satara\n",
       "D    Rohan    20           Patna\n",
       "E     Mani    22  Andhra Pradesh"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name['city']=['Nagpur','Navi mumbai','Satara','Patna','Andhra Pradesh']\n",
    "name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c39351f0",
   "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>Names</th>\n",
       "      <th>Ages</th>\n",
       "      <th>city</th>\n",
       "      <th>fav game</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>Ajinkya</td>\n",
       "      <td>23</td>\n",
       "      <td>Nagpur</td>\n",
       "      <td>football</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>Deepak</td>\n",
       "      <td>24</td>\n",
       "      <td>Navi mumbai</td>\n",
       "      <td>kabaddi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>Sairaj</td>\n",
       "      <td>25</td>\n",
       "      <td>Satara</td>\n",
       "      <td>kho kho</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D</th>\n",
       "      <td>Rohan</td>\n",
       "      <td>20</td>\n",
       "      <td>Patna</td>\n",
       "      <td>volleyball</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>Mani</td>\n",
       "      <td>22</td>\n",
       "      <td>Andhra Pradesh</td>\n",
       "      <td>cricket</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Names  Ages            city    fav game\n",
       "A  Ajinkya    23          Nagpur    football\n",
       "B   Deepak    24     Navi mumbai     kabaddi\n",
       "C   Sairaj    25          Satara     kho kho\n",
       "D    Rohan    20           Patna  volleyball\n",
       "E     Mani    22  Andhra Pradesh     cricket"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name['fav game']=['football','kabaddi','kho kho','volleyball','cricket']\n",
    "name"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b88cfd1",
   "metadata": {},
   "source": [
    "$STEP:-6$\n",
    "\n",
    "- How to drop any Rows and Column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "415d4453",
   "metadata": {},
   "outputs": [],
   "source": [
    "# what is your data frame name : name\n",
    "************* axis*****************\n",
    "# I want to drop column\n",
    "# axis=1 ============= column\n",
    "# axis=0 ============= rows\n",
    "******************************************************\n",
    "# what is the name of the column means\n",
    "*********** inplace*************************\n",
    "#   you are modifying the table\n",
    "#  the dataframes overwiter or\n",
    "# you want to create a dataframes\n",
    "\n",
    "\n",
    "# inplace=True  : data will be overwrite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "f713229d",
   "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>Names</th>\n",
       "      <th>Ages</th>\n",
       "      <th>fav game</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>Ajinkya</td>\n",
       "      <td>23</td>\n",
       "      <td>football</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>Deepak</td>\n",
       "      <td>24</td>\n",
       "      <td>kabaddi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>Sairaj</td>\n",
       "      <td>25</td>\n",
       "      <td>kho kho</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D</th>\n",
       "      <td>Rohan</td>\n",
       "      <td>20</td>\n",
       "      <td>volleyball</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>Mani</td>\n",
       "      <td>22</td>\n",
       "      <td>cricket</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Names  Ages    fav game\n",
       "A  Ajinkya    23    football\n",
       "B   Deepak    24     kabaddi\n",
       "C   Sairaj    25     kho kho\n",
       "D    Rohan    20  volleyball\n",
       "E     Mani    22     cricket"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name.drop('city',axis=1,inplace=True)\n",
    "name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "6b30f473",
   "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>Names</th>\n",
       "      <th>Ages</th>\n",
       "      <th>fav game</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>Ajinkya</td>\n",
       "      <td>23</td>\n",
       "      <td>football</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>Deepak</td>\n",
       "      <td>24</td>\n",
       "      <td>kabaddi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>Sairaj</td>\n",
       "      <td>25</td>\n",
       "      <td>kho kho</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>Mani</td>\n",
       "      <td>22</td>\n",
       "      <td>cricket</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Names  Ages  fav game\n",
       "A  Ajinkya    23  football\n",
       "B   Deepak    24   kabaddi\n",
       "C   Sairaj    25   kho kho\n",
       "E     Mani    22   cricket"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name.drop('D',axis=0,inplace=True)\n",
    "name"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "464f0def",
   "metadata": {},
   "source": [
    "**Create a dataframes using Dictionary**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5f748ce0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Names': ['ram', 'raheem', 'robert'], 'Age': [30, 31, 32]}"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict1={'Names':['ram','raheem','robert'],'Age':[30,31,32]}\n",
    "dict1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "309e4853",
   "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>Names</th>\n",
       "      <th>Age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ram</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>raheem</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>robert</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Names  Age\n",
       "0     ram   30\n",
       "1  raheem   31\n",
       "2  robert   32"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(dict1)\n",
    "\n",
    "# keys autometically becomes column\n",
    "# values becomes rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "05dae5d0",
   "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>A</th>\n",
       "      <th>B</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [A, B]\n",
       "Index: []"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(dict1,columns=['A','B'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "b2fbbab4",
   "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>Names</th>\n",
       "      <th>Age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>ram</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>raheem</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>robert</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Names  Age\n",
       "A     ram   30\n",
       "B  raheem   31\n",
       "C  robert   32"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(dict1,index=['A','B','C'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "cd112ffc",
   "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>Names</th>\n",
       "      <th>city</th>\n",
       "      <th>Age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>Nares_it</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>Nares_it</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>Nares_it</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D</th>\n",
       "      <td>Nares_it</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>Nares_it</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Names       city  Age\n",
       "A  Nares_it  Hyderabad   30\n",
       "B  Nares_it  Hyderabad   30\n",
       "C  Nares_it  Hyderabad   30\n",
       "D  Nares_it  Hyderabad   30\n",
       "E  Nares_it  Hyderabad   30"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict2={'Names':'Nares_it','city':'Hyderabad','Age':30}\n",
    "pd.DataFrame(dict2,index=['A','B','C','D','E'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "59754127",
   "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>Names</th>\n",
       "      <th>city</th>\n",
       "      <th>Age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Nares_it</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Nares_it</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Nares_it</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Nares_it</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Nares_it</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Nares_it</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Names       city  Age\n",
       "1  Nares_it  Hyderabad   30\n",
       "2  Nares_it  Hyderabad   30\n",
       "3  Nares_it  Hyderabad   30\n",
       "4  Nares_it  Hyderabad   30\n",
       "5  Nares_it  Hyderabad   30\n",
       "6  Nares_it  Hyderabad   30"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict2={'Names':'Nares_it','city':'Hyderabad','Age':30}\n",
    "pd.DataFrame(dict2,index=[1,2,3,4,5,6])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "04dfb86d",
   "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": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}