Task_7_Merge_Function.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ee19b45d",
   "metadata": {},
   "source": [
    "# Daily Task - 7 \n",
    "## Explore Merge Function\n",
    "# ---------------------------------------------------------------------------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1987572c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f52cdb02",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   id   Name_x     Lang_x  Name_y    Lang_y\n",
      "0   1    Shanu    English    John   English\n",
      "1   2     Amar      Hindi  Dinesh     Hindi\n",
      "2   3  Santosh    Marathi  Ranbir     Tamil\n",
      "3   4    Rahul     Telugu   Rahul   Bangali\n",
      "4   5   Jayesh  Gujarathi  Jayesh  Malyalam\n"
     ]
    }
   ],
   "source": [
    "left = pd.DataFrame({\n",
    "   'id':[1,2,3,4,5],\n",
    "   'Name': ['Shanu', 'Amar', 'Santosh', 'Rahul', 'Jayesh'],\n",
    "   'Lang':['English','Hindi','Marathi','Telugu','Gujarathi']})\n",
    "right = pd.DataFrame(\n",
    "   {'id':[1,2,3,4,5],\n",
    "   'Name': ['John', 'Dinesh', 'Ranbir', 'Rahul', 'Jayesh'],\n",
    "   'Lang':['English','Hindi','Tamil','Bangali','Malyalam']})\n",
    "\n",
    "print (pd.merge(left,right,on='id'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "88e4771e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   id_x    Name     Lang_x  id_y    Lang_y\n",
      "0     4   Rahul     Telugu     4   Bangali\n",
      "1     5  Jayesh  Gujarathi     5  Malyalam\n"
     ]
    }
   ],
   "source": [
    "left = pd.DataFrame({\n",
    "   'id':[1,2,3,4,5],\n",
    "   'Name': ['Shanu', 'Amar', 'Santosh', 'Rahul', 'Jayesh'],\n",
    "   'Lang':['English','Hindi','Marathi','Telugu','Gujarathi']})\n",
    "right = pd.DataFrame(\n",
    "   {'id':[1,2,3,4,5],\n",
    "   'Name': ['John', 'Dinesh', 'Ranbir', 'Rahul', 'Jayesh'],\n",
    "   'Lang':['English','Hindi','Tamil','Bangali','Malyalam']})\n",
    "\n",
    "print (pd.merge(left,right,on='Name'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "af4af27b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>Date</th>\n",
       "      <th>Voucher</th>\n",
       "      <th>Party</th>\n",
       "      <th>Product</th>\n",
       "      <th>Qty</th>\n",
       "      <th>Rate</th>\n",
       "      <th>Gross</th>\n",
       "      <th>Disc</th>\n",
       "      <th>Voucher Amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>RUBBER</td>\n",
       "      <td>5</td>\n",
       "      <td>290</td>\n",
       "      <td>1,450.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>DURGA 10*12 Blue</td>\n",
       "      <td>1,600.00</td>\n",
       "      <td>5.5</td>\n",
       "      <td>8,800.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>DURGA 13*16 BLUE</td>\n",
       "      <td>400</td>\n",
       "      <td>11</td>\n",
       "      <td>4,400.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>10*12 SARAS-NAT</td>\n",
       "      <td>600</td>\n",
       "      <td>8.1</td>\n",
       "      <td>4,860.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Date  Voucher Party            Product       Qty Rate     Gross Disc  \\\n",
       "0  1/4/2018  Sal:146  TP13  SILVER POUCH 9*12        50   85  4,250.00  NaN   \n",
       "1  1/4/2018  Sal:146  TP13             RUBBER         5  290  1,450.00  NaN   \n",
       "2  1/4/2018  Sal:146  TP13   DURGA 10*12 Blue  1,600.00  5.5  8,800.00  NaN   \n",
       "3  1/4/2018  Sal:146  TP13   DURGA 13*16 BLUE       400   11  4,400.00  NaN   \n",
       "4  1/4/2018  Sal:146  TP13    10*12 SARAS-NAT       600  8.1  4,860.00  NaN   \n",
       "\n",
       "  Voucher Amount  \n",
       "0      66,724.00  \n",
       "1            NaN  \n",
       "2            NaN  \n",
       "3            NaN  \n",
       "4            NaN  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "st_18 = pd.read_csv('D:\\John Sir\\Pandas\\Sales Transactions-2018.csv')\n",
    "st_18.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9f9b948d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Voucher</th>\n",
       "      <th>Party</th>\n",
       "      <th>Product</th>\n",
       "      <th>Qty</th>\n",
       "      <th>Rate</th>\n",
       "      <th>Gross</th>\n",
       "      <th>Disc</th>\n",
       "      <th>Voucher Amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/4/2019</td>\n",
       "      <td>Sal:687</td>\n",
       "      <td>BALAJI PLASTICS</td>\n",
       "      <td>DONA-VAI-9100</td>\n",
       "      <td>1</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3,460.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/4/2019</td>\n",
       "      <td>Sal:687</td>\n",
       "      <td>BALAJI PLASTICS</td>\n",
       "      <td>SMART BOUL(48)</td>\n",
       "      <td>1</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/4/2019</td>\n",
       "      <td>Sal:688</td>\n",
       "      <td>BALAJI PLASTICS</td>\n",
       "      <td>Vishnu Ice</td>\n",
       "      <td>110</td>\n",
       "      <td>18.5</td>\n",
       "      <td>2,035.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,035.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>28/3</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/4/2019</td>\n",
       "      <td>Sal:689</td>\n",
       "      <td>BALAJI PLASTICS</td>\n",
       "      <td>100LEAF -SP</td>\n",
       "      <td>3</td>\n",
       "      <td>585</td>\n",
       "      <td>1,755.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,755.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Date  Voucher            Party         Product  Qty      Rate  \\\n",
       "0  1/4/2019  Sal:687  BALAJI PLASTICS   DONA-VAI-9100    1  1,730.00   \n",
       "1  1/4/2019  Sal:687  BALAJI PLASTICS  SMART BOUL(48)    1  1,730.00   \n",
       "2  1/4/2019  Sal:688  BALAJI PLASTICS      Vishnu Ice  110      18.5   \n",
       "3                                28/3                    0         0   \n",
       "4  1/4/2019  Sal:689  BALAJI PLASTICS     100LEAF -SP    3       585   \n",
       "\n",
       "      Gross Disc Voucher Amount  \n",
       "0  1,730.00  NaN       3,460.00  \n",
       "1  1,730.00  NaN            NaN  \n",
       "2  2,035.00  NaN       2,035.00  \n",
       "3                                \n",
       "4  1,755.00  NaN       1,755.00  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "st_19 = pd.read_csv('D:\\John Sir\\Pandas\\Sales Transactions-2019.csv')\n",
    "st_19.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2d8f7ea",
   "metadata": {},
   "source": [
    "## Left Merge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "06586872",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date_x</th>\n",
       "      <th>Voucher_x</th>\n",
       "      <th>Party_x</th>\n",
       "      <th>Product</th>\n",
       "      <th>Qty_x</th>\n",
       "      <th>Rate_x</th>\n",
       "      <th>Gross_x</th>\n",
       "      <th>Disc_x</th>\n",
       "      <th>Voucher Amount_x</th>\n",
       "      <th>Date_y</th>\n",
       "      <th>Voucher_y</th>\n",
       "      <th>Party_y</th>\n",
       "      <th>Qty_y</th>\n",
       "      <th>Rate_y</th>\n",
       "      <th>Gross_y</th>\n",
       "      <th>Disc_y</th>\n",
       "      <th>Voucher Amount_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>2/4/2019</td>\n",
       "      <td>Sal:2</td>\n",
       "      <td>BSR</td>\n",
       "      <td>50</td>\n",
       "      <td>95</td>\n",
       "      <td>4,750.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4,750.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>3/4/2019</td>\n",
       "      <td>Sal:45</td>\n",
       "      <td>GANESHMESS</td>\n",
       "      <td>250</td>\n",
       "      <td>110</td>\n",
       "      <td>27,500.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>4/4/2019</td>\n",
       "      <td>Sal:75</td>\n",
       "      <td>Vkp</td>\n",
       "      <td>50</td>\n",
       "      <td>96</td>\n",
       "      <td>4,800.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>8/4/2019</td>\n",
       "      <td>Sal:160</td>\n",
       "      <td>BRHAMADEVI SUDHEER</td>\n",
       "      <td>50</td>\n",
       "      <td>96</td>\n",
       "      <td>4,800.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>8/4/2019</td>\n",
       "      <td>Sal:185</td>\n",
       "      <td>KPR</td>\n",
       "      <td>10</td>\n",
       "      <td>95</td>\n",
       "      <td>950</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>15114533</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ET</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15114534</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15114535</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15114536</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>99,284.90</td>\n",
       "      <td>175,381.65</td>\n",
       "      <td>2,203,649.50</td>\n",
       "      <td>20,680.00</td>\n",
       "      <td>2,189,014.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15114537</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,710,193.00</td>\n",
       "      <td>5,519,888.40</td>\n",
       "      <td>53,360,791.40</td>\n",
       "      <td>672,984.00</td>\n",
       "      <td>52,830,224.40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15114538 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date_x Voucher_x Party_x            Product         Qty_x  \\\n",
       "0         1/4/2018   Sal:146    TP13  SILVER POUCH 9*12            50   \n",
       "1         1/4/2018   Sal:146    TP13  SILVER POUCH 9*12            50   \n",
       "2         1/4/2018   Sal:146    TP13  SILVER POUCH 9*12            50   \n",
       "3         1/4/2018   Sal:146    TP13  SILVER POUCH 9*12            50   \n",
       "4         1/4/2018   Sal:146    TP13  SILVER POUCH 9*12            50   \n",
       "...            ...       ...     ...                ...           ...   \n",
       "15114533       NaN   Total       NaN                NaN  7,097,803.00   \n",
       "15114534       NaN   Total       NaN                NaN  7,097,803.00   \n",
       "15114535       NaN   Total       NaN                NaN  7,097,803.00   \n",
       "15114536       NaN   Total       NaN                NaN  7,097,803.00   \n",
       "15114537       NaN   Total       NaN                NaN  7,097,803.00   \n",
       "\n",
       "                 Rate_x         Gross_x      Disc_x Voucher Amount_x  \\\n",
       "0                    85        4,250.00         NaN        66,724.00   \n",
       "1                    85        4,250.00         NaN        66,724.00   \n",
       "2                    85        4,250.00         NaN        66,724.00   \n",
       "3                    85        4,250.00         NaN        66,724.00   \n",
       "4                    85        4,250.00         NaN        66,724.00   \n",
       "...                 ...             ...         ...              ...   \n",
       "15114533  10,024,197.00  117,897,671.80  720,204.00   117,427,983.80   \n",
       "15114534  10,024,197.00  117,897,671.80  720,204.00   117,427,983.80   \n",
       "15114535  10,024,197.00  117,897,671.80  720,204.00   117,427,983.80   \n",
       "15114536  10,024,197.00  117,897,671.80  720,204.00   117,427,983.80   \n",
       "15114537  10,024,197.00  117,897,671.80  720,204.00   117,427,983.80   \n",
       "\n",
       "            Date_y Voucher_y             Party_y         Qty_y        Rate_y  \\\n",
       "0         2/4/2019     Sal:2                 BSR            50            95   \n",
       "1         3/4/2019    Sal:45          GANESHMESS           250           110   \n",
       "2         4/4/2019    Sal:75                 Vkp            50            96   \n",
       "3         8/4/2019   Sal:160  BRHAMADEVI SUDHEER            50            96   \n",
       "4         8/4/2019   Sal:185                 KPR            10            95   \n",
       "...            ...       ...                 ...           ...           ...   \n",
       "15114533       NaN       NaN                  ET           NaN           NaN   \n",
       "15114534       NaN       NaN                 NaN           NaN           NaN   \n",
       "15114535       NaN       NaN                 NaN           NaN           NaN   \n",
       "15114536       NaN   Total                   NaN     99,284.90    175,381.65   \n",
       "15114537       NaN   Total                   NaN  2,710,193.00  5,519,888.40   \n",
       "\n",
       "                Gross_y      Disc_y Voucher Amount_y  \n",
       "0              4,750.00         NaN         4,750.00  \n",
       "1             27,500.00         NaN              NaN  \n",
       "2              4,800.00         NaN              NaN  \n",
       "3              4,800.00         NaN              NaN  \n",
       "4                   950         NaN              NaN  \n",
       "...                 ...         ...              ...  \n",
       "15114533            NaN         NaN              NaN  \n",
       "15114534            NaN         NaN              NaN  \n",
       "15114535            NaN         NaN              NaN  \n",
       "15114536   2,203,649.50   20,680.00     2,189,014.50  \n",
       "15114537  53,360,791.40  672,984.00    52,830,224.40  \n",
       "\n",
       "[15114538 rows x 17 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ast18_19 = pd.merge(st_18,st_19, on='Product', how='left')\n",
    "ast18_19"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1f707bbb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Voucher_x</th>\n",
       "      <th>Party_x</th>\n",
       "      <th>Product_x</th>\n",
       "      <th>Qty_x</th>\n",
       "      <th>Rate_x</th>\n",
       "      <th>Gross_x</th>\n",
       "      <th>Disc_x</th>\n",
       "      <th>Voucher Amount_x</th>\n",
       "      <th>Voucher_y</th>\n",
       "      <th>Party_y</th>\n",
       "      <th>Product_y</th>\n",
       "      <th>Qty_y</th>\n",
       "      <th>Rate_y</th>\n",
       "      <th>Gross_y</th>\n",
       "      <th>Disc_y</th>\n",
       "      <th>Voucher Amount_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>RUBBER</td>\n",
       "      <td>5</td>\n",
       "      <td>290</td>\n",
       "      <td>1,450.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>DURGA 10*12 Blue</td>\n",
       "      <td>1,600.00</td>\n",
       "      <td>5.5</td>\n",
       "      <td>8,800.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>DURGA 13*16 BLUE</td>\n",
       "      <td>400</td>\n",
       "      <td>11</td>\n",
       "      <td>4,400.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>10*12 SARAS-NAT</td>\n",
       "      <td>600</td>\n",
       "      <td>8.1</td>\n",
       "      <td>4,860.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <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>10312274</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ET</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10312275</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>10312276</th>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10312277</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>99,284.90</td>\n",
       "      <td>175,381.65</td>\n",
       "      <td>2,203,649.50</td>\n",
       "      <td>20,680.00</td>\n",
       "      <td>2,189,014.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10312278</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,710,193.00</td>\n",
       "      <td>5,519,888.40</td>\n",
       "      <td>53,360,791.40</td>\n",
       "      <td>672,984.00</td>\n",
       "      <td>52,830,224.40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10312279 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Date Voucher_x Party_x          Product_x         Qty_x  \\\n",
       "0         1/4/2018   Sal:146    TP13  SILVER POUCH 9*12            50   \n",
       "1         1/4/2018   Sal:146    TP13             RUBBER             5   \n",
       "2         1/4/2018   Sal:146    TP13   DURGA 10*12 Blue      1,600.00   \n",
       "3         1/4/2018   Sal:146    TP13   DURGA 13*16 BLUE           400   \n",
       "4         1/4/2018   Sal:146    TP13    10*12 SARAS-NAT           600   \n",
       "...            ...       ...     ...                ...           ...   \n",
       "10312274       NaN   Total       NaN                NaN  7,097,803.00   \n",
       "10312275       NaN   Total       NaN                NaN  7,097,803.00   \n",
       "10312276       NaN   Total       NaN                NaN  7,097,803.00   \n",
       "10312277       NaN   Total       NaN                NaN  7,097,803.00   \n",
       "10312278       NaN   Total       NaN                NaN  7,097,803.00   \n",
       "\n",
       "                 Rate_x         Gross_x      Disc_x Voucher Amount_x  \\\n",
       "0                    85        4,250.00         NaN        66,724.00   \n",
       "1                   290        1,450.00         NaN              NaN   \n",
       "2                   5.5        8,800.00         NaN              NaN   \n",
       "3                    11        4,400.00         NaN              NaN   \n",
       "4                   8.1        4,860.00         NaN              NaN   \n",
       "...                 ...             ...         ...              ...   \n",
       "10312274  10,024,197.00  117,897,671.80  720,204.00   117,427,983.80   \n",
       "10312275  10,024,197.00  117,897,671.80  720,204.00   117,427,983.80   \n",
       "10312276  10,024,197.00  117,897,671.80  720,204.00   117,427,983.80   \n",
       "10312277  10,024,197.00  117,897,671.80  720,204.00   117,427,983.80   \n",
       "10312278  10,024,197.00  117,897,671.80  720,204.00   117,427,983.80   \n",
       "\n",
       "         Voucher_y Party_y Product_y         Qty_y        Rate_y  \\\n",
       "0              NaN     NaN       NaN           NaN           NaN   \n",
       "1              NaN     NaN       NaN           NaN           NaN   \n",
       "2              NaN     NaN       NaN           NaN           NaN   \n",
       "3              NaN     NaN       NaN           NaN           NaN   \n",
       "4              NaN     NaN       NaN           NaN           NaN   \n",
       "...            ...     ...       ...           ...           ...   \n",
       "10312274       NaN      ET       NaN           NaN           NaN   \n",
       "10312275       NaN     NaN       NaN           NaN           NaN   \n",
       "10312276       NaN     NaN       NaN           NaN           NaN   \n",
       "10312277   Total       NaN       NaN     99,284.90    175,381.65   \n",
       "10312278   Total       NaN       NaN  2,710,193.00  5,519,888.40   \n",
       "\n",
       "                Gross_y      Disc_y Voucher Amount_y  \n",
       "0                   NaN         NaN              NaN  \n",
       "1                   NaN         NaN              NaN  \n",
       "2                   NaN         NaN              NaN  \n",
       "3                   NaN         NaN              NaN  \n",
       "4                   NaN         NaN              NaN  \n",
       "...                 ...         ...              ...  \n",
       "10312274            NaN         NaN              NaN  \n",
       "10312275            NaN         NaN              NaN  \n",
       "10312276            NaN         NaN              NaN  \n",
       "10312277   2,203,649.50   20,680.00     2,189,014.50  \n",
       "10312278  53,360,791.40  672,984.00    52,830,224.40  \n",
       "\n",
       "[10312279 rows x 17 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wst18_19 = pd.merge(st_18,st_19, on='Date', how='left')\n",
    "wst18_19"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a62f4c32",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   id_x   Name_x       Lang  id_y  Name_y\n",
      "0     1    Shanu    English   1.0    John\n",
      "1     2     Amar      Hindi   2.0  Dinesh\n",
      "2     3  Santosh    Marathi   NaN     NaN\n",
      "3     4    Rahul     Telugu   NaN     NaN\n",
      "4     5   Jayesh  Gujarathi   NaN     NaN\n"
     ]
    }
   ],
   "source": [
    "left = pd.DataFrame({\n",
    "   'id':[1,2,3,4,5],\n",
    "   'Name': ['Shanu', 'Amar', 'Santosh', 'Rahul', 'Jayesh'],\n",
    "   'Lang':['English','Hindi','Marathi','Telugu','Gujarathi']})\n",
    "right = pd.DataFrame(\n",
    "   {'id':[1,2,3,4,5],\n",
    "   'Name': ['John', 'Dinesh', 'Ranbir', 'Rahul', 'Jayesh'],\n",
    "   'Lang':['English','Hindi','Tamil','Bangali','Malyalam']})\n",
    "\n",
    "print (pd.merge(left, right, on='Lang', how='left'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba05e8eb",
   "metadata": {},
   "source": [
    "## Right Merge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0c4bf6df",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date_x</th>\n",
       "      <th>Voucher_x</th>\n",
       "      <th>Party_x</th>\n",
       "      <th>Product</th>\n",
       "      <th>Qty_x</th>\n",
       "      <th>Rate_x</th>\n",
       "      <th>Gross_x</th>\n",
       "      <th>Disc_x</th>\n",
       "      <th>Voucher Amount_x</th>\n",
       "      <th>Date_y</th>\n",
       "      <th>Voucher_y</th>\n",
       "      <th>Party_y</th>\n",
       "      <th>Qty_y</th>\n",
       "      <th>Rate_y</th>\n",
       "      <th>Gross_y</th>\n",
       "      <th>Disc_y</th>\n",
       "      <th>Voucher Amount_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3/4/2018</td>\n",
       "      <td>Sal:33</td>\n",
       "      <td>M.BHASKER</td>\n",
       "      <td>DONA-VAI-9100</td>\n",
       "      <td>1</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>800</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1/4/2019</td>\n",
       "      <td>Sal:687</td>\n",
       "      <td>BALAJI PLASTICS</td>\n",
       "      <td>1</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3,460.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4/4/2018</td>\n",
       "      <td>Sal:42</td>\n",
       "      <td>LAKSHMISAI FANCY-KO</td>\n",
       "      <td>DONA-VAI-9100</td>\n",
       "      <td>1</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1/4/2019</td>\n",
       "      <td>Sal:687</td>\n",
       "      <td>BALAJI PLASTICS</td>\n",
       "      <td>1</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3,460.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4/4/2018</td>\n",
       "      <td>Sal:156</td>\n",
       "      <td>TP13</td>\n",
       "      <td>DONA-VAI-9100</td>\n",
       "      <td>1</td>\n",
       "      <td>1,680.00</td>\n",
       "      <td>1,680.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1/4/2019</td>\n",
       "      <td>Sal:687</td>\n",
       "      <td>BALAJI PLASTICS</td>\n",
       "      <td>1</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3,460.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5/4/2018</td>\n",
       "      <td>Sal:61</td>\n",
       "      <td>RAVIKANTH GDR</td>\n",
       "      <td>DONA-VAI-9100</td>\n",
       "      <td>5</td>\n",
       "      <td>1,640.00</td>\n",
       "      <td>8,200.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1/4/2019</td>\n",
       "      <td>Sal:687</td>\n",
       "      <td>BALAJI PLASTICS</td>\n",
       "      <td>1</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3,460.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7/4/2018</td>\n",
       "      <td>Sal:105</td>\n",
       "      <td>CHEKKA SUDHAKAR</td>\n",
       "      <td>DONA-VAI-9100</td>\n",
       "      <td>1</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1/4/2019</td>\n",
       "      <td>Sal:687</td>\n",
       "      <td>BALAJI PLASTICS</td>\n",
       "      <td>1</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3,460.00</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>15114732</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RKINN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,710,193.00</td>\n",
       "      <td>5,519,888.40</td>\n",
       "      <td>53,360,791.40</td>\n",
       "      <td>672,984.00</td>\n",
       "      <td>52,830,224.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15114733</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,710,193.00</td>\n",
       "      <td>5,519,888.40</td>\n",
       "      <td>53,360,791.40</td>\n",
       "      <td>672,984.00</td>\n",
       "      <td>52,830,224.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15114734</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,710,193.00</td>\n",
       "      <td>5,519,888.40</td>\n",
       "      <td>53,360,791.40</td>\n",
       "      <td>672,984.00</td>\n",
       "      <td>52,830,224.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15114735</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>666,056.00</td>\n",
       "      <td>1,067,808.80</td>\n",
       "      <td>10,796,991.30</td>\n",
       "      <td>29,999.00</td>\n",
       "      <td>10,787,647.30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,710,193.00</td>\n",
       "      <td>5,519,888.40</td>\n",
       "      <td>53,360,791.40</td>\n",
       "      <td>672,984.00</td>\n",
       "      <td>52,830,224.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15114736</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,710,193.00</td>\n",
       "      <td>5,519,888.40</td>\n",
       "      <td>53,360,791.40</td>\n",
       "      <td>672,984.00</td>\n",
       "      <td>52,830,224.40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15114737 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date_x Voucher_x              Party_x        Product  \\\n",
       "0         3/4/2018    Sal:33            M.BHASKER  DONA-VAI-9100   \n",
       "1         4/4/2018    Sal:42  LAKSHMISAI FANCY-KO  DONA-VAI-9100   \n",
       "2         4/4/2018   Sal:156                 TP13  DONA-VAI-9100   \n",
       "3         5/4/2018    Sal:61        RAVIKANTH GDR  DONA-VAI-9100   \n",
       "4         7/4/2018   Sal:105      CHEKKA SUDHAKAR  DONA-VAI-9100   \n",
       "...            ...       ...                  ...            ...   \n",
       "15114732       NaN       NaN                RKINN            NaN   \n",
       "15114733       NaN       NaN                  NaN            NaN   \n",
       "15114734       NaN       NaN                  NaN            NaN   \n",
       "15114735       NaN   Total                    NaN            NaN   \n",
       "15114736       NaN   Total                    NaN            NaN   \n",
       "\n",
       "                 Qty_x         Rate_x         Gross_x      Disc_x  \\\n",
       "0                    1       1,730.00        1,730.00         800   \n",
       "1                    1       1,730.00        1,730.00         NaN   \n",
       "2                    1       1,680.00        1,680.00         NaN   \n",
       "3                    5       1,640.00        8,200.00         NaN   \n",
       "4                    1       1,730.00        1,730.00         NaN   \n",
       "...                ...            ...             ...         ...   \n",
       "15114732           NaN            NaN             NaN         NaN   \n",
       "15114733           NaN            NaN             NaN         NaN   \n",
       "15114734           NaN            NaN             NaN         NaN   \n",
       "15114735    666,056.00   1,067,808.80   10,796,991.30   29,999.00   \n",
       "15114736  7,097,803.00  10,024,197.00  117,897,671.80  720,204.00   \n",
       "\n",
       "         Voucher Amount_x    Date_y Voucher_y          Party_y         Qty_y  \\\n",
       "0                     NaN  1/4/2019   Sal:687  BALAJI PLASTICS             1   \n",
       "1                     NaN  1/4/2019   Sal:687  BALAJI PLASTICS             1   \n",
       "2                     NaN  1/4/2019   Sal:687  BALAJI PLASTICS             1   \n",
       "3                     NaN  1/4/2019   Sal:687  BALAJI PLASTICS             1   \n",
       "4                     NaN  1/4/2019   Sal:687  BALAJI PLASTICS             1   \n",
       "...                   ...       ...       ...              ...           ...   \n",
       "15114732              NaN       NaN   Total                NaN  2,710,193.00   \n",
       "15114733              NaN       NaN   Total                NaN  2,710,193.00   \n",
       "15114734              NaN       NaN   Total                NaN  2,710,193.00   \n",
       "15114735    10,787,647.30       NaN   Total                NaN  2,710,193.00   \n",
       "15114736   117,427,983.80       NaN   Total                NaN  2,710,193.00   \n",
       "\n",
       "                Rate_y        Gross_y      Disc_y Voucher Amount_y  \n",
       "0             1,730.00       1,730.00         NaN         3,460.00  \n",
       "1             1,730.00       1,730.00         NaN         3,460.00  \n",
       "2             1,730.00       1,730.00         NaN         3,460.00  \n",
       "3             1,730.00       1,730.00         NaN         3,460.00  \n",
       "4             1,730.00       1,730.00         NaN         3,460.00  \n",
       "...                ...            ...         ...              ...  \n",
       "15114732  5,519,888.40  53,360,791.40  672,984.00    52,830,224.40  \n",
       "15114733  5,519,888.40  53,360,791.40  672,984.00    52,830,224.40  \n",
       "15114734  5,519,888.40  53,360,791.40  672,984.00    52,830,224.40  \n",
       "15114735  5,519,888.40  53,360,791.40  672,984.00    52,830,224.40  \n",
       "15114736  5,519,888.40  53,360,791.40  672,984.00    52,830,224.40  \n",
       "\n",
       "[15114737 rows x 17 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bst18_19 = pd.merge(st_18,st_19, on='Product', how='right')\n",
    "bst18_19"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9614d1c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Voucher_x</th>\n",
       "      <th>Party_x</th>\n",
       "      <th>Product_x</th>\n",
       "      <th>Qty_x</th>\n",
       "      <th>Rate_x</th>\n",
       "      <th>Gross_x</th>\n",
       "      <th>Disc_x</th>\n",
       "      <th>Voucher Amount_x</th>\n",
       "      <th>Voucher_y</th>\n",
       "      <th>Party_y</th>\n",
       "      <th>Product_y</th>\n",
       "      <th>Qty_y</th>\n",
       "      <th>Rate_y</th>\n",
       "      <th>Gross_y</th>\n",
       "      <th>Disc_y</th>\n",
       "      <th>Voucher Amount_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/4/2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sal:687</td>\n",
       "      <td>BALAJI PLASTICS</td>\n",
       "      <td>DONA-VAI-9100</td>\n",
       "      <td>1</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3,460.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/4/2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sal:687</td>\n",
       "      <td>BALAJI PLASTICS</td>\n",
       "      <td>SMART BOUL(48)</td>\n",
       "      <td>1</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>1,730.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/4/2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sal:688</td>\n",
       "      <td>BALAJI PLASTICS</td>\n",
       "      <td>Vishnu Ice</td>\n",
       "      <td>110</td>\n",
       "      <td>18.5</td>\n",
       "      <td>2,035.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,035.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>d.veerabadram</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>28/3</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>DUMMY ENTRY</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>28/3</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></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>10291093</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RKINN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,710,193.00</td>\n",
       "      <td>5,519,888.40</td>\n",
       "      <td>53,360,791.40</td>\n",
       "      <td>672,984.00</td>\n",
       "      <td>52,830,224.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10291094</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,710,193.00</td>\n",
       "      <td>5,519,888.40</td>\n",
       "      <td>53,360,791.40</td>\n",
       "      <td>672,984.00</td>\n",
       "      <td>52,830,224.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10291095</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,710,193.00</td>\n",
       "      <td>5,519,888.40</td>\n",
       "      <td>53,360,791.40</td>\n",
       "      <td>672,984.00</td>\n",
       "      <td>52,830,224.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10291096</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>666,056.00</td>\n",
       "      <td>1,067,808.80</td>\n",
       "      <td>10,796,991.30</td>\n",
       "      <td>29,999.00</td>\n",
       "      <td>10,787,647.30</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,710,193.00</td>\n",
       "      <td>5,519,888.40</td>\n",
       "      <td>53,360,791.40</td>\n",
       "      <td>672,984.00</td>\n",
       "      <td>52,830,224.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10291097</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,710,193.00</td>\n",
       "      <td>5,519,888.40</td>\n",
       "      <td>53,360,791.40</td>\n",
       "      <td>672,984.00</td>\n",
       "      <td>52,830,224.40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10291098 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Date Voucher_x        Party_x Product_x         Qty_x  \\\n",
       "0         1/4/2019       NaN            NaN       NaN           NaN   \n",
       "1         1/4/2019       NaN            NaN       NaN           NaN   \n",
       "2         1/4/2019       NaN            NaN       NaN           NaN   \n",
       "3                             d.veerabadram                           \n",
       "4                               DUMMY ENTRY                           \n",
       "...            ...       ...            ...       ...           ...   \n",
       "10291093       NaN       NaN          RKINN       NaN           NaN   \n",
       "10291094       NaN       NaN            NaN       NaN           NaN   \n",
       "10291095       NaN       NaN            NaN       NaN           NaN   \n",
       "10291096       NaN   Total              NaN       NaN    666,056.00   \n",
       "10291097       NaN   Total              NaN       NaN  7,097,803.00   \n",
       "\n",
       "                 Rate_x         Gross_x      Disc_x Voucher Amount_x  \\\n",
       "0                   NaN             NaN         NaN              NaN   \n",
       "1                   NaN             NaN         NaN              NaN   \n",
       "2                   NaN             NaN         NaN              NaN   \n",
       "3                                                                      \n",
       "4                                                                      \n",
       "...                 ...             ...         ...              ...   \n",
       "10291093            NaN             NaN         NaN              NaN   \n",
       "10291094            NaN             NaN         NaN              NaN   \n",
       "10291095            NaN             NaN         NaN              NaN   \n",
       "10291096   1,067,808.80   10,796,991.30   29,999.00    10,787,647.30   \n",
       "10291097  10,024,197.00  117,897,671.80  720,204.00   117,427,983.80   \n",
       "\n",
       "         Voucher_y          Party_y       Product_y         Qty_y  \\\n",
       "0          Sal:687  BALAJI PLASTICS   DONA-VAI-9100             1   \n",
       "1          Sal:687  BALAJI PLASTICS  SMART BOUL(48)             1   \n",
       "2          Sal:688  BALAJI PLASTICS      Vishnu Ice           110   \n",
       "3                              28/3                             0   \n",
       "4                              28/3                             0   \n",
       "...            ...              ...             ...           ...   \n",
       "10291093   Total                NaN             NaN  2,710,193.00   \n",
       "10291094   Total                NaN             NaN  2,710,193.00   \n",
       "10291095   Total                NaN             NaN  2,710,193.00   \n",
       "10291096   Total                NaN             NaN  2,710,193.00   \n",
       "10291097   Total                NaN             NaN  2,710,193.00   \n",
       "\n",
       "                Rate_y        Gross_y      Disc_y Voucher Amount_y  \n",
       "0             1,730.00       1,730.00         NaN         3,460.00  \n",
       "1             1,730.00       1,730.00         NaN              NaN  \n",
       "2                 18.5       2,035.00         NaN         2,035.00  \n",
       "3                    0                                              \n",
       "4                    0                                              \n",
       "...                ...            ...         ...              ...  \n",
       "10291093  5,519,888.40  53,360,791.40  672,984.00    52,830,224.40  \n",
       "10291094  5,519,888.40  53,360,791.40  672,984.00    52,830,224.40  \n",
       "10291095  5,519,888.40  53,360,791.40  672,984.00    52,830,224.40  \n",
       "10291096  5,519,888.40  53,360,791.40  672,984.00    52,830,224.40  \n",
       "10291097  5,519,888.40  53,360,791.40  672,984.00    52,830,224.40  \n",
       "\n",
       "[10291098 rows x 17 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xst18_19 = pd.merge(st_18,st_19, on='Date', how='right')\n",
    "xst18_19"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1ff9984b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   id_x Name_x      Lang  id_y  Name_y\n",
      "0   1.0  Shanu   English     1    John\n",
      "1   2.0   Amar     Hindi     2  Dinesh\n",
      "2   NaN    NaN     Tamil     3  Ranbir\n",
      "3   NaN    NaN   Bangali     4   Rahul\n",
      "4   NaN    NaN  Malyalam     5  Jayesh\n"
     ]
    }
   ],
   "source": [
    "left = pd.DataFrame({\n",
    "   'id':[1,2,3,4,5],\n",
    "   'Name': ['Shanu', 'Amar', 'Santosh', 'Rahul', 'Jayesh'],\n",
    "   'Lang':['English','Hindi','Marathi','Telugu','Gujarathi']})\n",
    "right = pd.DataFrame(\n",
    "   {'id':[1,2,3,4,5],\n",
    "   'Name': ['John', 'Dinesh', 'Ranbir', 'Rahul', 'Jayesh'],\n",
    "   'Lang':['English','Hindi','Tamil','Bangali','Malyalam']})\n",
    "\n",
    "print (pd.merge(left, right, on='Lang', how='right'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a4bb9b2",
   "metadata": {},
   "source": [
    "## Outer Merge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f183f25f",
   "metadata": {
    "scrolled": false
   },
   "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>Date_x</th>\n",
       "      <th>Voucher_x</th>\n",
       "      <th>Party_x</th>\n",
       "      <th>Product</th>\n",
       "      <th>Qty_x</th>\n",
       "      <th>Rate_x</th>\n",
       "      <th>Gross_x</th>\n",
       "      <th>Disc_x</th>\n",
       "      <th>Voucher Amount_x</th>\n",
       "      <th>Date_y</th>\n",
       "      <th>Voucher_y</th>\n",
       "      <th>Party_y</th>\n",
       "      <th>Qty_y</th>\n",
       "      <th>Rate_y</th>\n",
       "      <th>Gross_y</th>\n",
       "      <th>Disc_y</th>\n",
       "      <th>Voucher Amount_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>2/4/2019</td>\n",
       "      <td>Sal:2</td>\n",
       "      <td>BSR</td>\n",
       "      <td>50</td>\n",
       "      <td>95</td>\n",
       "      <td>4,750.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4,750.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>3/4/2019</td>\n",
       "      <td>Sal:45</td>\n",
       "      <td>GANESHMESS</td>\n",
       "      <td>250</td>\n",
       "      <td>110</td>\n",
       "      <td>27,500.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>4/4/2019</td>\n",
       "      <td>Sal:75</td>\n",
       "      <td>Vkp</td>\n",
       "      <td>50</td>\n",
       "      <td>96</td>\n",
       "      <td>4,800.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>8/4/2019</td>\n",
       "      <td>Sal:160</td>\n",
       "      <td>BRHAMADEVI SUDHEER</td>\n",
       "      <td>50</td>\n",
       "      <td>96</td>\n",
       "      <td>4,800.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>8/4/2019</td>\n",
       "      <td>Sal:185</td>\n",
       "      <td>KPR</td>\n",
       "      <td>10</td>\n",
       "      <td>95</td>\n",
       "      <td>950</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>15115518</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14 MULTI(8PACK)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9/10/2019</td>\n",
       "      <td>Sal:4857</td>\n",
       "      <td>BSR</td>\n",
       "      <td>80</td>\n",
       "      <td>55</td>\n",
       "      <td>4,400.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15115519</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MAAZA TETRA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28/09/2019</td>\n",
       "      <td>Sal:4696</td>\n",
       "      <td>SURI</td>\n",
       "      <td>1</td>\n",
       "      <td>330</td>\n",
       "      <td>330</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15115520</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SILVER BOULS LOOSE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30/09/2019</td>\n",
       "      <td>Sal:4705</td>\n",
       "      <td>CUSTOMER</td>\n",
       "      <td>49</td>\n",
       "      <td>150</td>\n",
       "      <td>7,350.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15115521</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TIFFIN PLATES-11NO-</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1/10/2019</td>\n",
       "      <td>Sal:4722</td>\n",
       "      <td>VENUGOPAL-INAMADUGU</td>\n",
       "      <td>50</td>\n",
       "      <td>20</td>\n",
       "      <td>1,000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15115522</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RELIANCE GLASS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9/10/2019</td>\n",
       "      <td>Sal:4889</td>\n",
       "      <td>K.SRIHARI</td>\n",
       "      <td>100</td>\n",
       "      <td>35</td>\n",
       "      <td>3,500.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5,340.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15115523 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date_x Voucher_x Party_x              Product Qty_x Rate_x  \\\n",
       "0         1/4/2018   Sal:146    TP13    SILVER POUCH 9*12    50     85   \n",
       "1         1/4/2018   Sal:146    TP13    SILVER POUCH 9*12    50     85   \n",
       "2         1/4/2018   Sal:146    TP13    SILVER POUCH 9*12    50     85   \n",
       "3         1/4/2018   Sal:146    TP13    SILVER POUCH 9*12    50     85   \n",
       "4         1/4/2018   Sal:146    TP13    SILVER POUCH 9*12    50     85   \n",
       "...            ...       ...     ...                  ...   ...    ...   \n",
       "15115518       NaN       NaN     NaN      14 MULTI(8PACK)   NaN    NaN   \n",
       "15115519       NaN       NaN     NaN          MAAZA TETRA   NaN    NaN   \n",
       "15115520       NaN       NaN     NaN   SILVER BOULS LOOSE   NaN    NaN   \n",
       "15115521       NaN       NaN     NaN  TIFFIN PLATES-11NO-   NaN    NaN   \n",
       "15115522       NaN       NaN     NaN       RELIANCE GLASS   NaN    NaN   \n",
       "\n",
       "           Gross_x Disc_x Voucher Amount_x      Date_y Voucher_y  \\\n",
       "0         4,250.00    NaN        66,724.00    2/4/2019     Sal:2   \n",
       "1         4,250.00    NaN        66,724.00    3/4/2019    Sal:45   \n",
       "2         4,250.00    NaN        66,724.00    4/4/2019    Sal:75   \n",
       "3         4,250.00    NaN        66,724.00    8/4/2019   Sal:160   \n",
       "4         4,250.00    NaN        66,724.00    8/4/2019   Sal:185   \n",
       "...            ...    ...              ...         ...       ...   \n",
       "15115518       NaN    NaN              NaN   9/10/2019  Sal:4857   \n",
       "15115519       NaN    NaN              NaN  28/09/2019  Sal:4696   \n",
       "15115520       NaN    NaN              NaN  30/09/2019  Sal:4705   \n",
       "15115521       NaN    NaN              NaN   1/10/2019  Sal:4722   \n",
       "15115522       NaN    NaN              NaN   9/10/2019  Sal:4889   \n",
       "\n",
       "                      Party_y Qty_y Rate_y    Gross_y Disc_y Voucher Amount_y  \n",
       "0                         BSR    50     95   4,750.00    NaN         4,750.00  \n",
       "1                  GANESHMESS   250    110  27,500.00    NaN              NaN  \n",
       "2                         Vkp    50     96   4,800.00    NaN              NaN  \n",
       "3          BRHAMADEVI SUDHEER    50     96   4,800.00    NaN              NaN  \n",
       "4                         KPR    10     95        950    NaN              NaN  \n",
       "...                       ...   ...    ...        ...    ...              ...  \n",
       "15115518                  BSR    80     55   4,400.00    NaN              NaN  \n",
       "15115519                 SURI     1    330        330    NaN              NaN  \n",
       "15115520             CUSTOMER    49    150   7,350.00    NaN              NaN  \n",
       "15115521  VENUGOPAL-INAMADUGU    50     20   1,000.00    NaN              NaN  \n",
       "15115522            K.SRIHARI   100     35   3,500.00    NaN         5,340.00  \n",
       "\n",
       "[15115523 rows x 17 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cst18_19 = pd.merge(st_18,st_19, on='Product', how='outer')\n",
    "cst18_19"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d8a02f44",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Voucher_x</th>\n",
       "      <th>Party_x</th>\n",
       "      <th>Product_x</th>\n",
       "      <th>Qty_x</th>\n",
       "      <th>Rate_x</th>\n",
       "      <th>Gross_x</th>\n",
       "      <th>Disc_x</th>\n",
       "      <th>Voucher Amount_x</th>\n",
       "      <th>Voucher_y</th>\n",
       "      <th>Party_y</th>\n",
       "      <th>Product_y</th>\n",
       "      <th>Qty_y</th>\n",
       "      <th>Rate_y</th>\n",
       "      <th>Gross_y</th>\n",
       "      <th>Disc_y</th>\n",
       "      <th>Voucher Amount_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>RUBBER</td>\n",
       "      <td>5</td>\n",
       "      <td>290</td>\n",
       "      <td>1,450.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>DURGA 10*12 Blue</td>\n",
       "      <td>1,600.00</td>\n",
       "      <td>5.5</td>\n",
       "      <td>8,800.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>DURGA 13*16 BLUE</td>\n",
       "      <td>400</td>\n",
       "      <td>11</td>\n",
       "      <td>4,400.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>10*12 SARAS-NAT</td>\n",
       "      <td>600</td>\n",
       "      <td>8.1</td>\n",
       "      <td>4,860.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>10329186</th>\n",
       "      <td>10/10/2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sal:4935</td>\n",
       "      <td>K.SRIHARI</td>\n",
       "      <td>16*20(100-W)</td>\n",
       "      <td>140</td>\n",
       "      <td>26</td>\n",
       "      <td>3,640.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10329187</th>\n",
       "      <td>10/10/2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sal:4935</td>\n",
       "      <td>K.SRIHARI</td>\n",
       "      <td>10*12 KRISHNA-BK(10</td>\n",
       "      <td>600</td>\n",
       "      <td>8.4</td>\n",
       "      <td>5,040.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10329188</th>\n",
       "      <td>10/10/2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sal:4935</td>\n",
       "      <td>K.SRIHARI</td>\n",
       "      <td>13*16 Bk(100)KRISHN</td>\n",
       "      <td>320</td>\n",
       "      <td>16</td>\n",
       "      <td>5,120.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10329189</th>\n",
       "      <td>10/10/2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sal:4935</td>\n",
       "      <td>K.SRIHARI</td>\n",
       "      <td>10*12 RK</td>\n",
       "      <td>800</td>\n",
       "      <td>8.5</td>\n",
       "      <td>6,800.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10329190</th>\n",
       "      <td>10/10/2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sal:4935</td>\n",
       "      <td>K.SRIHARI</td>\n",
       "      <td>13*16 WHITE RK</td>\n",
       "      <td>400</td>\n",
       "      <td>16</td>\n",
       "      <td>6,400.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10329191 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                Date Voucher_x Party_x          Product_x     Qty_x Rate_x  \\\n",
       "0           1/4/2018   Sal:146    TP13  SILVER POUCH 9*12        50     85   \n",
       "1           1/4/2018   Sal:146    TP13             RUBBER         5    290   \n",
       "2           1/4/2018   Sal:146    TP13   DURGA 10*12 Blue  1,600.00    5.5   \n",
       "3           1/4/2018   Sal:146    TP13   DURGA 13*16 BLUE       400     11   \n",
       "4           1/4/2018   Sal:146    TP13    10*12 SARAS-NAT       600    8.1   \n",
       "...              ...       ...     ...                ...       ...    ...   \n",
       "10329186  10/10/2019       NaN     NaN                NaN       NaN    NaN   \n",
       "10329187  10/10/2019       NaN     NaN                NaN       NaN    NaN   \n",
       "10329188  10/10/2019       NaN     NaN                NaN       NaN    NaN   \n",
       "10329189  10/10/2019       NaN     NaN                NaN       NaN    NaN   \n",
       "10329190  10/10/2019       NaN     NaN                NaN       NaN    NaN   \n",
       "\n",
       "           Gross_x Disc_x Voucher Amount_x Voucher_y    Party_y  \\\n",
       "0         4,250.00    NaN        66,724.00       NaN        NaN   \n",
       "1         1,450.00    NaN              NaN       NaN        NaN   \n",
       "2         8,800.00    NaN              NaN       NaN        NaN   \n",
       "3         4,400.00    NaN              NaN       NaN        NaN   \n",
       "4         4,860.00    NaN              NaN       NaN        NaN   \n",
       "...            ...    ...              ...       ...        ...   \n",
       "10329186       NaN    NaN              NaN  Sal:4935  K.SRIHARI   \n",
       "10329187       NaN    NaN              NaN  Sal:4935  K.SRIHARI   \n",
       "10329188       NaN    NaN              NaN  Sal:4935  K.SRIHARI   \n",
       "10329189       NaN    NaN              NaN  Sal:4935  K.SRIHARI   \n",
       "10329190       NaN    NaN              NaN  Sal:4935  K.SRIHARI   \n",
       "\n",
       "                    Product_y Qty_y Rate_y   Gross_y Disc_y Voucher Amount_y  \n",
       "0                         NaN   NaN    NaN       NaN    NaN              NaN  \n",
       "1                         NaN   NaN    NaN       NaN    NaN              NaN  \n",
       "2                         NaN   NaN    NaN       NaN    NaN              NaN  \n",
       "3                         NaN   NaN    NaN       NaN    NaN              NaN  \n",
       "4                         NaN   NaN    NaN       NaN    NaN              NaN  \n",
       "...                       ...   ...    ...       ...    ...              ...  \n",
       "10329186         16*20(100-W)   140     26  3,640.00    NaN              NaN  \n",
       "10329187  10*12 KRISHNA-BK(10   600    8.4  5,040.00    NaN              NaN  \n",
       "10329188  13*16 Bk(100)KRISHN   320     16  5,120.00    NaN              NaN  \n",
       "10329189             10*12 RK   800    8.5  6,800.00    NaN              NaN  \n",
       "10329190       13*16 WHITE RK   400     16  6,400.00    NaN              NaN  \n",
       "\n",
       "[10329191 rows x 17 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yst18_19 = pd.merge(st_18,st_19, on='Date', how='outer')\n",
    "yst18_19"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4b07e128",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   id_x   Name_x       Lang  id_y  Name_y\n",
      "0   1.0    Shanu    English   1.0    John\n",
      "1   2.0     Amar      Hindi   2.0  Dinesh\n",
      "2   3.0  Santosh    Marathi   NaN     NaN\n",
      "3   4.0    Rahul     Telugu   NaN     NaN\n",
      "4   5.0   Jayesh  Gujarathi   NaN     NaN\n",
      "5   NaN      NaN      Tamil   3.0  Ranbir\n",
      "6   NaN      NaN    Bangali   4.0   Rahul\n",
      "7   NaN      NaN   Malyalam   5.0  Jayesh\n"
     ]
    }
   ],
   "source": [
    "left = pd.DataFrame({\n",
    "   'id':[1,2,3,4,5],\n",
    "   'Name': ['Shanu', 'Amar', 'Santosh', 'Rahul', 'Jayesh'],\n",
    "   'Lang':['English','Hindi','Marathi','Telugu','Gujarathi']})\n",
    "right = pd.DataFrame(\n",
    "   {'id':[1,2,3,4,5],\n",
    "   'Name': ['John', 'Dinesh', 'Ranbir', 'Rahul', 'Jayesh'],\n",
    "   'Lang':['English','Hindi','Tamil','Bangali','Malyalam']})\n",
    "\n",
    "print (pd.merge(left, right, on='Lang', how='outer'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8c6f291",
   "metadata": {},
   "source": [
    "## Inner Merge "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d65a0917",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date_x</th>\n",
       "      <th>Voucher_x</th>\n",
       "      <th>Party_x</th>\n",
       "      <th>Product</th>\n",
       "      <th>Qty_x</th>\n",
       "      <th>Rate_x</th>\n",
       "      <th>Gross_x</th>\n",
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       "      <th>Date_y</th>\n",
       "      <th>Voucher_y</th>\n",
       "      <th>Party_y</th>\n",
       "      <th>Qty_y</th>\n",
       "      <th>Rate_y</th>\n",
       "      <th>Gross_y</th>\n",
       "      <th>Disc_y</th>\n",
       "      <th>Voucher Amount_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>2/4/2019</td>\n",
       "      <td>Sal:2</td>\n",
       "      <td>BSR</td>\n",
       "      <td>50</td>\n",
       "      <td>95</td>\n",
       "      <td>4,750.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4,750.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>3/4/2019</td>\n",
       "      <td>Sal:45</td>\n",
       "      <td>GANESHMESS</td>\n",
       "      <td>250</td>\n",
       "      <td>110</td>\n",
       "      <td>27,500.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>4/4/2019</td>\n",
       "      <td>Sal:75</td>\n",
       "      <td>Vkp</td>\n",
       "      <td>50</td>\n",
       "      <td>96</td>\n",
       "      <td>4,800.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>8/4/2019</td>\n",
       "      <td>Sal:160</td>\n",
       "      <td>BRHAMADEVI SUDHEER</td>\n",
       "      <td>50</td>\n",
       "      <td>96</td>\n",
       "      <td>4,800.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/4/2018</td>\n",
       "      <td>Sal:146</td>\n",
       "      <td>TP13</td>\n",
       "      <td>SILVER POUCH 9*12</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>4,250.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66,724.00</td>\n",
       "      <td>8/4/2019</td>\n",
       "      <td>Sal:185</td>\n",
       "      <td>KPR</td>\n",
       "      <td>10</td>\n",
       "      <td>95</td>\n",
       "      <td>950</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>15113747</th>\n",
       "      <td>31/03/2019</td>\n",
       "      <td>Sal:9578</td>\n",
       "      <td>SEKHAR MARKET</td>\n",
       "      <td>14\" 3PLY SILVER</td>\n",
       "      <td>10</td>\n",
       "      <td>365</td>\n",
       "      <td>3,650.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1/5/2019</td>\n",
       "      <td>Sal:817</td>\n",
       "      <td>SEKHAR MARKET</td>\n",
       "      <td>10</td>\n",
       "      <td>364</td>\n",
       "      <td>3,640.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3,640.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15113748</th>\n",
       "      <td>31/03/2019</td>\n",
       "      <td>Sal:9578</td>\n",
       "      <td>SEKHAR MARKET</td>\n",
       "      <td>14\" 3PLY SILVER</td>\n",
       "      <td>10</td>\n",
       "      <td>365</td>\n",
       "      <td>3,650.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6/5/2019</td>\n",
       "      <td>Sal:938</td>\n",
       "      <td>BRHAMADEVI SUDHEER</td>\n",
       "      <td>20</td>\n",
       "      <td>185</td>\n",
       "      <td>3,700.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3,700.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15113749</th>\n",
       "      <td>31/03/2019</td>\n",
       "      <td>Sal:9578</td>\n",
       "      <td>SEKHAR MARKET</td>\n",
       "      <td>14\" 3PLY SILVER</td>\n",
       "      <td>10</td>\n",
       "      <td>365</td>\n",
       "      <td>3,650.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6/6/2019</td>\n",
       "      <td>Sal:1830</td>\n",
       "      <td>BRHAMADEVI SUDHEER</td>\n",
       "      <td>10</td>\n",
       "      <td>185</td>\n",
       "      <td>1,850.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15113750</th>\n",
       "      <td>31/03/2019</td>\n",
       "      <td>Sal:9578</td>\n",
       "      <td>SEKHAR MARKET</td>\n",
       "      <td>14\" 3PLY SILVER</td>\n",
       "      <td>10</td>\n",
       "      <td>365</td>\n",
       "      <td>3,650.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1/7/2019</td>\n",
       "      <td>Sal:2339</td>\n",
       "      <td>RAMAKRISHNA GENERAL</td>\n",
       "      <td>78</td>\n",
       "      <td>45</td>\n",
       "      <td>3,510.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3,530.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15113751</th>\n",
       "      <td>31/03/2019</td>\n",
       "      <td>Sal:9578</td>\n",
       "      <td>SEKHAR MARKET</td>\n",
       "      <td>14\" 3PLY SILVER</td>\n",
       "      <td>10</td>\n",
       "      <td>365</td>\n",
       "      <td>3,650.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9/7/2019</td>\n",
       "      <td>Sal:2508</td>\n",
       "      <td>VENUGOPAL-INAMADUGU</td>\n",
       "      <td>3</td>\n",
       "      <td>250</td>\n",
       "      <td>750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15113752 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Date_x Voucher_x        Party_x            Product Qty_x Rate_x  \\\n",
       "0           1/4/2018   Sal:146           TP13  SILVER POUCH 9*12    50     85   \n",
       "1           1/4/2018   Sal:146           TP13  SILVER POUCH 9*12    50     85   \n",
       "2           1/4/2018   Sal:146           TP13  SILVER POUCH 9*12    50     85   \n",
       "3           1/4/2018   Sal:146           TP13  SILVER POUCH 9*12    50     85   \n",
       "4           1/4/2018   Sal:146           TP13  SILVER POUCH 9*12    50     85   \n",
       "...              ...       ...            ...                ...   ...    ...   \n",
       "15113747  31/03/2019  Sal:9578  SEKHAR MARKET    14\" 3PLY SILVER    10    365   \n",
       "15113748  31/03/2019  Sal:9578  SEKHAR MARKET    14\" 3PLY SILVER    10    365   \n",
       "15113749  31/03/2019  Sal:9578  SEKHAR MARKET    14\" 3PLY SILVER    10    365   \n",
       "15113750  31/03/2019  Sal:9578  SEKHAR MARKET    14\" 3PLY SILVER    10    365   \n",
       "15113751  31/03/2019  Sal:9578  SEKHAR MARKET    14\" 3PLY SILVER    10    365   \n",
       "\n",
       "           Gross_x Disc_x Voucher Amount_x    Date_y Voucher_y  \\\n",
       "0         4,250.00    NaN        66,724.00  2/4/2019     Sal:2   \n",
       "1         4,250.00    NaN        66,724.00  3/4/2019    Sal:45   \n",
       "2         4,250.00    NaN        66,724.00  4/4/2019    Sal:75   \n",
       "3         4,250.00    NaN        66,724.00  8/4/2019   Sal:160   \n",
       "4         4,250.00    NaN        66,724.00  8/4/2019   Sal:185   \n",
       "...            ...    ...              ...       ...       ...   \n",
       "15113747  3,650.00    NaN              NaN  1/5/2019   Sal:817   \n",
       "15113748  3,650.00    NaN              NaN  6/5/2019   Sal:938   \n",
       "15113749  3,650.00    NaN              NaN  6/6/2019  Sal:1830   \n",
       "15113750  3,650.00    NaN              NaN  1/7/2019  Sal:2339   \n",
       "15113751  3,650.00    NaN              NaN  9/7/2019  Sal:2508   \n",
       "\n",
       "                      Party_y Qty_y Rate_y    Gross_y Disc_y Voucher Amount_y  \n",
       "0                         BSR    50     95   4,750.00    NaN         4,750.00  \n",
       "1                  GANESHMESS   250    110  27,500.00    NaN              NaN  \n",
       "2                         Vkp    50     96   4,800.00    NaN              NaN  \n",
       "3          BRHAMADEVI SUDHEER    50     96   4,800.00    NaN              NaN  \n",
       "4                         KPR    10     95        950    NaN              NaN  \n",
       "...                       ...   ...    ...        ...    ...              ...  \n",
       "15113747        SEKHAR MARKET    10    364   3,640.00    NaN         3,640.00  \n",
       "15113748   BRHAMADEVI SUDHEER    20    185   3,700.00    NaN         3,700.00  \n",
       "15113749   BRHAMADEVI SUDHEER    10    185   1,850.00    NaN              NaN  \n",
       "15113750  RAMAKRISHNA GENERAL    78     45   3,510.00    NaN         3,530.00  \n",
       "15113751  VENUGOPAL-INAMADUGU     3    250        750    NaN              NaN  \n",
       "\n",
       "[15113752 rows x 17 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dst18_19 = pd.merge(st_18,st_19, on='Product', how='inner')\n",
    "dst18_19"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7f7bc77c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Voucher_x</th>\n",
       "      <th>Party_x</th>\n",
       "      <th>Product_x</th>\n",
       "      <th>Qty_x</th>\n",
       "      <th>Rate_x</th>\n",
       "      <th>Gross_x</th>\n",
       "      <th>Disc_x</th>\n",
       "      <th>Voucher Amount_x</th>\n",
       "      <th>Voucher_y</th>\n",
       "      <th>Party_y</th>\n",
       "      <th>Product_y</th>\n",
       "      <th>Qty_y</th>\n",
       "      <th>Rate_y</th>\n",
       "      <th>Gross_y</th>\n",
       "      <th>Disc_y</th>\n",
       "      <th>Voucher Amount_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>d.veerabadram</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>28/3</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>d.veerabadram</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>25/2</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>d.veerabadram</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>jamal ,khadervali</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>3</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>d.veerabadram</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>by hand</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>4</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>d.veerabadram</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>credit bill</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>...</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>10274181</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ET</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10274182</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10274183</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10274184</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>99,284.90</td>\n",
       "      <td>175,381.65</td>\n",
       "      <td>2,203,649.50</td>\n",
       "      <td>20,680.00</td>\n",
       "      <td>2,189,014.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10274185</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7,097,803.00</td>\n",
       "      <td>10,024,197.00</td>\n",
       "      <td>117,897,671.80</td>\n",
       "      <td>720,204.00</td>\n",
       "      <td>117,427,983.80</td>\n",
       "      <td>Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,710,193.00</td>\n",
       "      <td>5,519,888.40</td>\n",
       "      <td>53,360,791.40</td>\n",
       "      <td>672,984.00</td>\n",
       "      <td>52,830,224.40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10274186 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date Voucher_x        Party_x Product_x         Qty_x         Rate_x  \\\n",
       "0                        d.veerabadram                                          \n",
       "1                        d.veerabadram                                          \n",
       "2                        d.veerabadram                                          \n",
       "3                        d.veerabadram                                          \n",
       "4                        d.veerabadram                                          \n",
       "...       ...       ...            ...       ...           ...            ...   \n",
       "10274181  NaN   Total              NaN       NaN  7,097,803.00  10,024,197.00   \n",
       "10274182  NaN   Total              NaN       NaN  7,097,803.00  10,024,197.00   \n",
       "10274183  NaN   Total              NaN       NaN  7,097,803.00  10,024,197.00   \n",
       "10274184  NaN   Total              NaN       NaN  7,097,803.00  10,024,197.00   \n",
       "10274185  NaN   Total              NaN       NaN  7,097,803.00  10,024,197.00   \n",
       "\n",
       "                 Gross_x      Disc_x Voucher Amount_x Voucher_y  \\\n",
       "0                                                                 \n",
       "1                                                                 \n",
       "2                                                                 \n",
       "3                                                                 \n",
       "4                                                                 \n",
       "...                  ...         ...              ...       ...   \n",
       "10274181  117,897,671.80  720,204.00   117,427,983.80       NaN   \n",
       "10274182  117,897,671.80  720,204.00   117,427,983.80       NaN   \n",
       "10274183  117,897,671.80  720,204.00   117,427,983.80       NaN   \n",
       "10274184  117,897,671.80  720,204.00   117,427,983.80   Total     \n",
       "10274185  117,897,671.80  720,204.00   117,427,983.80   Total     \n",
       "\n",
       "                    Party_y Product_y         Qty_y        Rate_y  \\\n",
       "0                      28/3                       0             0   \n",
       "1                      25/2                       0             0   \n",
       "2         jamal ,khadervali                                         \n",
       "3                   by hand                                         \n",
       "4               credit bill                                         \n",
       "...                     ...       ...           ...           ...   \n",
       "10274181                 ET       NaN           NaN           NaN   \n",
       "10274182                NaN       NaN           NaN           NaN   \n",
       "10274183                NaN       NaN           NaN           NaN   \n",
       "10274184                NaN       NaN     99,284.90    175,381.65   \n",
       "10274185                NaN       NaN  2,710,193.00  5,519,888.40   \n",
       "\n",
       "                Gross_y      Disc_y Voucher Amount_y  \n",
       "0                                                     \n",
       "1                                                     \n",
       "2                                                     \n",
       "3                                                     \n",
       "4                                                     \n",
       "...                 ...         ...              ...  \n",
       "10274181            NaN         NaN              NaN  \n",
       "10274182            NaN         NaN              NaN  \n",
       "10274183            NaN         NaN              NaN  \n",
       "10274184   2,203,649.50   20,680.00     2,189,014.50  \n",
       "10274185  53,360,791.40  672,984.00    52,830,224.40  \n",
       "\n",
       "[10274186 rows x 17 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zst18_19 = pd.merge(st_18,st_19, on='Date', how='inner')\n",
    "zst18_19"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "a6f52cbf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   id_x Name_x     Lang  id_y  Name_y\n",
      "0     1  Shanu  English     1    John\n",
      "1     2   Amar    Hindi     2  Dinesh\n"
     ]
    }
   ],
   "source": [
    "left = pd.DataFrame({\n",
    "   'id':[1,2,3,4,5],\n",
    "   'Name': ['Shanu', 'Amar', 'Santosh', 'Rahul', 'Jayesh'],\n",
    "   'Lang':['English','Hindi','Marathi','Telugu','Gujarathi']})\n",
    "right = pd.DataFrame(\n",
    "   {'id':[1,2,3,4,5],\n",
    "   'Name': ['John', 'Dinesh', 'Ranbir', 'Rahul', 'Jayesh'],\n",
    "   'Lang':['English','Hindi','Tamil','Bangali','Malyalam']})\n",
    "\n",
    "print (pd.merge(left, right, on='Lang', how='inner'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aae577cc",
   "metadata": {},
   "source": [
    "# The End !!! "
   ]
  }
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