Merging, Joining, and Concatenating DataFrames.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "539286dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ec026a2f",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>First Name</th>\n",
       "      <th>Last Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Company</th>\n",
       "      <th>Occupation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Joseph</td>\n",
       "      <td>Perkins</td>\n",
       "      <td>Male</td>\n",
       "      <td>Dynazzy</td>\n",
       "      <td>Community Outreach Specialist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Jennifer</td>\n",
       "      <td>Alvarez</td>\n",
       "      <td>Female</td>\n",
       "      <td>DabZ</td>\n",
       "      <td>Senior Quality Engineer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Roger</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>Tagfeed</td>\n",
       "      <td>Account Executive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Steven</td>\n",
       "      <td>Evans</td>\n",
       "      <td>Male</td>\n",
       "      <td>Fatz</td>\n",
       "      <td>Registered Nurse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Judy</td>\n",
       "      <td>Morrison</td>\n",
       "      <td>Female</td>\n",
       "      <td>Demivee</td>\n",
       "      <td>Legal Assistant</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>996</td>\n",
       "      <td>Debra</td>\n",
       "      <td>Garcia</td>\n",
       "      <td>Female</td>\n",
       "      <td>Dazzlesphere</td>\n",
       "      <td>Structural Engineer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>997</td>\n",
       "      <td>Douglas</td>\n",
       "      <td>Bishop</td>\n",
       "      <td>Male</td>\n",
       "      <td>Livepath</td>\n",
       "      <td>Developer I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>998</td>\n",
       "      <td>Frank</td>\n",
       "      <td>Franklin</td>\n",
       "      <td>Male</td>\n",
       "      <td>Brainverse</td>\n",
       "      <td>Nurse Practicioner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>999</td>\n",
       "      <td>Jessica</td>\n",
       "      <td>Burns</td>\n",
       "      <td>Female</td>\n",
       "      <td>Babbleblab</td>\n",
       "      <td>Financial Advisor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>1000</td>\n",
       "      <td>Brian</td>\n",
       "      <td>Daniels</td>\n",
       "      <td>Male</td>\n",
       "      <td>Tazzy</td>\n",
       "      <td>Physical Therapy Assistant</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ID First Name Last Name  Gender       Company  \\\n",
       "0       1     Joseph   Perkins    Male       Dynazzy   \n",
       "1       2   Jennifer   Alvarez  Female          DabZ   \n",
       "2       3      Roger     Black    Male       Tagfeed   \n",
       "3       4     Steven     Evans    Male          Fatz   \n",
       "4       5       Judy  Morrison  Female       Demivee   \n",
       "..    ...        ...       ...     ...           ...   \n",
       "995   996      Debra    Garcia  Female  Dazzlesphere   \n",
       "996   997    Douglas    Bishop    Male      Livepath   \n",
       "997   998      Frank  Franklin    Male    Brainverse   \n",
       "998   999    Jessica     Burns  Female    Babbleblab   \n",
       "999  1000      Brian   Daniels    Male         Tazzy   \n",
       "\n",
       "                        Occupation  \n",
       "0    Community Outreach Specialist  \n",
       "1          Senior Quality Engineer  \n",
       "2                Account Executive  \n",
       "3                 Registered Nurse  \n",
       "4                  Legal Assistant  \n",
       "..                             ...  \n",
       "995            Structural Engineer  \n",
       "996                    Developer I  \n",
       "997             Nurse Practicioner  \n",
       "998              Financial Advisor  \n",
       "999     Physical Therapy Assistant  \n",
       "\n",
       "[1000 rows x 6 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv(\"Restaurant - Customers.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "abef8f52",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Food ID</th>\n",
       "      <th>Food Item</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Sushi</td>\n",
       "      <td>3.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Burrito</td>\n",
       "      <td>9.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Taco</td>\n",
       "      <td>2.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Quesadilla</td>\n",
       "      <td>4.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Pizza</td>\n",
       "      <td>2.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>Pasta</td>\n",
       "      <td>13.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>Steak</td>\n",
       "      <td>24.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>Salad</td>\n",
       "      <td>11.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>Donut</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>Drink</td>\n",
       "      <td>1.75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Food ID   Food Item  Price\n",
       "0        1       Sushi   3.99\n",
       "1        2     Burrito   9.99\n",
       "2        3        Taco   2.99\n",
       "3        4  Quesadilla   4.25\n",
       "4        5       Pizza   2.49\n",
       "5        6       Pasta  13.99\n",
       "6        7       Steak  24.99\n",
       "7        8       Salad  11.25\n",
       "8        9       Donut   0.99\n",
       "9       10       Drink   1.75"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv(\"Restaurant - Foods.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ac3defda",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Food ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "</table>\n",
       "<p>250 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer ID  Food ID\n",
       "0            537        9\n",
       "1             97        4\n",
       "2            658        1\n",
       "3            202        2\n",
       "4            155        9\n",
       "..           ...      ...\n",
       "245          413        9\n",
       "246          926        6\n",
       "247          134        3\n",
       "248          396        6\n",
       "249          535       10\n",
       "\n",
       "[250 rows x 2 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv(\"Restaurant - Week 1 Sales.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e04d6233",
   "metadata": {},
   "outputs": [],
   "source": [
    "week1 = pd.read_csv(\"Restaurant - Week 1 Sales.csv\")\n",
    "week2 = pd.read_csv(\"Restaurant - Week 2 Sales.csv\")\n",
    "customers = pd.read_csv(\"Restaurant - Customers.csv\")\n",
    "foods = pd.read_csv(\"Restaurant - Foods.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c7b3c66e",
   "metadata": {},
   "outputs": [
    {
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       "      <th>Customer ID</th>\n",
       "      <th>Food ID</th>\n",
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       "      <td>249</td>\n",
       "      <td>6</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer ID  Food ID\n",
       "0            537        9\n",
       "1             97        4\n",
       "2            658        1\n",
       "3            202        2\n",
       "4            155        9\n",
       "..           ...      ...\n",
       "245          783       10\n",
       "246          556       10\n",
       "247          547        9\n",
       "248          252        9\n",
       "249          249        6\n",
       "\n",
       "[500 rows x 2 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat(objs = [week1, week2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "970bf75f",
   "metadata": {},
   "outputs": [
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       "      <th>Customer ID</th>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer ID  Food ID\n",
       "0            537        9\n",
       "1             97        4\n",
       "2            658        1\n",
       "3            202        2\n",
       "4            155        9\n",
       "..           ...      ...\n",
       "495          783       10\n",
       "496          556       10\n",
       "497          547        9\n",
       "498          252        9\n",
       "499          249        6\n",
       "\n",
       "[500 rows x 2 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat(objs = [week1, week2], ignore_index = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2e02534a",
   "metadata": {},
   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Food ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>537</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>97</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>658</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>202</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>155</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>783</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>556</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>547</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>252</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>249</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer ID  Food ID\n",
       "0            537        9\n",
       "1             97        4\n",
       "2            658        1\n",
       "3            202        2\n",
       "4            155        9\n",
       "..           ...      ...\n",
       "245          783       10\n",
       "246          556       10\n",
       "247          547        9\n",
       "248          252        9\n",
       "249          249        6\n",
       "\n",
       "[500 rows x 2 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "week1.append(week2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8aff024b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>10</td>\n",
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       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>547</td>\n",
       "      <td>9</td>\n",
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       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>252</td>\n",
       "      <td>9</td>\n",
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       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>249</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer ID  Food ID\n",
       "0            537        9\n",
       "1             97        4\n",
       "2            658        1\n",
       "3            202        2\n",
       "4            155        9\n",
       "..           ...      ...\n",
       "495          783       10\n",
       "496          556       10\n",
       "497          547        9\n",
       "498          252        9\n",
       "499          249        6\n",
       "\n",
       "[500 rows x 2 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "week1.append(week2, ignore_index = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1ce6ae57",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Week 2</th>\n",
       "      <th>245</th>\n",
       "      <td>783</td>\n",
       "      <td>10</td>\n",
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       "    <tr>\n",
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       "      <td>10</td>\n",
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       "      <td>547</td>\n",
       "      <td>9</td>\n",
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       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>252</td>\n",
       "      <td>9</td>\n",
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       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>249</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Customer ID  Food ID\n",
       "Week 1 0            537        9\n",
       "       1             97        4\n",
       "       2            658        1\n",
       "       3            202        2\n",
       "       4            155        9\n",
       "...                 ...      ...\n",
       "Week 2 245          783       10\n",
       "       246          556       10\n",
       "       247          547        9\n",
       "       248          252        9\n",
       "       249          249        6\n",
       "\n",
       "[500 rows x 2 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat(objs = [week1, week2], keys = [\"Week 1\", \"Week 2\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "41cadc9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "      <th rowspan=\"5\" valign=\"top\">Week 2</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
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       "      <th>248</th>\n",
       "      <td>252</td>\n",
       "      <td>9</td>\n",
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       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>249</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Customer ID  Food ID\n",
       "Week 1 0            537        9\n",
       "       1             97        4\n",
       "       2            658        1\n",
       "       3            202        2\n",
       "       4            155        9\n",
       "...                 ...      ...\n",
       "Week 2 245          783       10\n",
       "       246          556       10\n",
       "       247          547        9\n",
       "       248          252        9\n",
       "       249          249        6\n",
       "\n",
       "[500 rows x 2 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales = pd.concat(objs = [week1, week2], keys = [\"Week 1\", \"Week 2\"])\n",
    "sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0e1ed057",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>1</td>\n",
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       "      <th>3</th>\n",
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       "      <td>2</td>\n",
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       "      <td>155</td>\n",
       "      <td>9</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>413</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>926</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>134</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>396</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>535</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>250 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer ID  Food ID\n",
       "0            537        9\n",
       "1             97        4\n",
       "2            658        1\n",
       "3            202        2\n",
       "4            155        9\n",
       "..           ...      ...\n",
       "245          413        9\n",
       "246          926        6\n",
       "247          134        3\n",
       "248          396        6\n",
       "249          535       10\n",
       "\n",
       "[250 rows x 2 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales.loc[(\"Week 1\",)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "80f6aad7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Customer ID    537\n",
       "Food ID          9\n",
       "Name: (Week 1, 0), dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales.loc[(\"Week 1\", 0)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "41b60843",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales.loc[(\"Week 1\", 0), \"Food ID\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95d7e259",
   "metadata": {},
   "source": [
    "# Inner Joins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0ae29ee3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "      <th>3</th>\n",
       "      <td>503</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>503</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>945</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>343</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>343</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>343</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>621</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>62 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Customer ID  Food ID - Week 1  Food ID - Week 2\n",
       "0           537                 9                 5\n",
       "1           155                 9                 3\n",
       "2           155                 1                 3\n",
       "3           503                 5                 8\n",
       "4           503                 5                 9\n",
       "..          ...               ...               ...\n",
       "57          945                 5                 4\n",
       "58          343                 3                 5\n",
       "59          343                 3                 2\n",
       "60          343                 3                 7\n",
       "61          621                 9                 6\n",
       "\n",
       "[62 rows x 3 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "week1.merge(week2, how = \"inner\", on = \"Customer ID\", suffixes = [\" - Week 1\", \" - Week 2\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4231392b",
   "metadata": {},
   "source": [
    "# Inner Joins Part 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "737c1901",
   "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",
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       "\n",
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       "        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>Customer ID</th>\n",
       "      <th>Food ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>304</td>\n",
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       "      <th>2</th>\n",
       "      <td>937</td>\n",
       "      <td>10</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>233</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>21</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
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       "      <th>5</th>\n",
       "      <td>21</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>922</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>578</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>578</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Customer ID  Food ID\n",
       "0          304        3\n",
       "1          540        3\n",
       "2          937       10\n",
       "3          233        3\n",
       "4           21        4\n",
       "5           21        4\n",
       "6          922        1\n",
       "7          578        5\n",
       "8          578        5"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "week1.merge(week2, how = \"inner\", on = [\"Customer ID\", \"Food ID\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1876c8f6",
   "metadata": {},
   "source": [
    "# Outer Joins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d9c46f28",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Food ID - Week 1</th>\n",
       "      <th>Food ID - Week 2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>537</td>\n",
       "      <td>9.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>97</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>658</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>202</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>155</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>855</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>559</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451</th>\n",
       "      <td>276</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>556</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>252</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>454 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer ID  Food ID - Week 1  Food ID - Week 2\n",
       "0            537               9.0               5.0\n",
       "1             97               4.0               NaN\n",
       "2            658               1.0               NaN\n",
       "3            202               2.0               NaN\n",
       "4            155               9.0               3.0\n",
       "..           ...               ...               ...\n",
       "449          855               NaN               4.0\n",
       "450          559               NaN              10.0\n",
       "451          276               NaN               4.0\n",
       "452          556               NaN              10.0\n",
       "453          252               NaN               9.0\n",
       "\n",
       "[454 rows x 3 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "week1.merge(week2, how = \"outer\", on = \"Customer ID\", suffixes = [\" - Week 1\", \" - Week 2\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0ef075aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "merged = week1.merge(week2, how = \"outer\", on = \"Customer ID\", suffixes = [\" - Week 1\", \" - Week 2\"], indicator = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ff5fca52",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "      <th></th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Food ID - Week 1</th>\n",
       "      <th>Food ID - Week 2</th>\n",
       "      <th>_merge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>537</td>\n",
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       "      <td>both</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>97</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>left_only</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>658</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>left_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>202</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>left_only</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>155</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>both</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>855</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>right_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>559</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "      <td>right_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451</th>\n",
       "      <td>276</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>right_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>556</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "      <td>right_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>252</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>right_only</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>454 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer ID  Food ID - Week 1  Food ID - Week 2      _merge\n",
       "0            537               9.0               5.0        both\n",
       "1             97               4.0               NaN   left_only\n",
       "2            658               1.0               NaN   left_only\n",
       "3            202               2.0               NaN   left_only\n",
       "4            155               9.0               3.0        both\n",
       "..           ...               ...               ...         ...\n",
       "449          855               NaN               4.0  right_only\n",
       "450          559               NaN              10.0  right_only\n",
       "451          276               NaN               4.0  right_only\n",
       "452          556               NaN              10.0  right_only\n",
       "453          252               NaN               9.0  right_only\n",
       "\n",
       "[454 rows x 4 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5b8fccb",
   "metadata": {},
   "source": [
    "# 4. either set a or set b but not both\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c289782c",
   "metadata": {
    "scrolled": true
   },
   "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>Customer ID</th>\n",
       "      <th>Food ID - Week 1</th>\n",
       "      <th>Food ID - Week 2</th>\n",
       "      <th>_merge</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>97</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>left_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>658</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>left_only</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>202</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>left_only</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>213</td>\n",
       "      <td>8.0</td>\n",
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       "      <td>left_only</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>600</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>left_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>855</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>right_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>559</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "      <td>right_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451</th>\n",
       "      <td>276</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>right_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>556</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "      <td>right_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>252</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>right_only</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>392 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer ID  Food ID - Week 1  Food ID - Week 2      _merge\n",
       "1             97               4.0               NaN   left_only\n",
       "2            658               1.0               NaN   left_only\n",
       "3            202               2.0               NaN   left_only\n",
       "6            213               8.0               NaN   left_only\n",
       "7            600               1.0               NaN   left_only\n",
       "..           ...               ...               ...         ...\n",
       "449          855               NaN               4.0  right_only\n",
       "450          559               NaN              10.0  right_only\n",
       "451          276               NaN               4.0  right_only\n",
       "452          556               NaN              10.0  right_only\n",
       "453          252               NaN               9.0  right_only\n",
       "\n",
       "[392 rows x 4 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged[merged[\"_merge\"].isin([\"left_only\",\"right_only\"])]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec24d0b7",
   "metadata": {},
   "source": [
    "# Left Joins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "0f3b6f1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "week1 = pd.read_csv(\"Restaurant - Week 1 Sales.csv\")\n",
    "week2 = pd.read_csv(\"Restaurant - Week 2 Sales.csv\")\n",
    "customers = pd.read_csv(\"Restaurant - Customers.csv\")\n",
    "foods = pd.read_csv(\"Restaurant - Foods.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "6befa732",
   "metadata": {
    "scrolled": true
   },
   "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>Customer ID</th>\n",
       "      <th>Food ID</th>\n",
       "      <th>Food Item</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>537</td>\n",
       "      <td>9</td>\n",
       "      <td>Donut</td>\n",
       "      <td>0.99</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>97</td>\n",
       "      <td>4</td>\n",
       "      <td>Quesadilla</td>\n",
       "      <td>4.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>658</td>\n",
       "      <td>1</td>\n",
       "      <td>Sushi</td>\n",
       "      <td>3.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>202</td>\n",
       "      <td>2</td>\n",
       "      <td>Burrito</td>\n",
       "      <td>9.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>155</td>\n",
       "      <td>9</td>\n",
       "      <td>Donut</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>413</td>\n",
       "      <td>9</td>\n",
       "      <td>Donut</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>926</td>\n",
       "      <td>6</td>\n",
       "      <td>Pasta</td>\n",
       "      <td>13.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>134</td>\n",
       "      <td>3</td>\n",
       "      <td>Taco</td>\n",
       "      <td>2.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>396</td>\n",
       "      <td>6</td>\n",
       "      <td>Pasta</td>\n",
       "      <td>13.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>535</td>\n",
       "      <td>10</td>\n",
       "      <td>Drink</td>\n",
       "      <td>1.75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>250 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer ID  Food ID   Food Item  Price\n",
       "0            537        9       Donut   0.99\n",
       "1             97        4  Quesadilla   4.25\n",
       "2            658        1       Sushi   3.99\n",
       "3            202        2     Burrito   9.99\n",
       "4            155        9       Donut   0.99\n",
       "..           ...      ...         ...    ...\n",
       "245          413        9       Donut   0.99\n",
       "246          926        6       Pasta  13.99\n",
       "247          134        3        Taco   2.99\n",
       "248          396        6       Pasta  13.99\n",
       "249          535       10       Drink   1.75\n",
       "\n",
       "[250 rows x 4 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "week1.merge(foods, how = \"left\", on = \"Food ID\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d1e748b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "left_merge = week1.merge(foods, how = \"left\", on = \"Food ID\")\n",
    "left_merge[\"Food Item\"].hasnans"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "472cd891",
   "metadata": {},
   "source": [
    "# left_on and right_on parameter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c2db571d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Food ID</th>\n",
       "      <th>ID</th>\n",
       "      <th>First Name</th>\n",
       "      <th>Last Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Company</th>\n",
       "      <th>Occupation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>Frances</td>\n",
       "      <td>Adams</td>\n",
       "      <td>Female</td>\n",
       "      <td>Dabshots</td>\n",
       "      <td>Developer III</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>Ruth</td>\n",
       "      <td>Alvarez</td>\n",
       "      <td>Female</td>\n",
       "      <td>Twitterlist</td>\n",
       "      <td>Mechanical Systems Engineer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21</td>\n",
       "      <td>4</td>\n",
       "      <td>21</td>\n",
       "      <td>Albert</td>\n",
       "      <td>Burns</td>\n",
       "      <td>Male</td>\n",
       "      <td>Rhynoodle</td>\n",
       "      <td>Junior Executive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24</td>\n",
       "      <td>8</td>\n",
       "      <td>24</td>\n",
       "      <td>Donna</td>\n",
       "      <td>Thomas</td>\n",
       "      <td>Female</td>\n",
       "      <td>Jaxbean</td>\n",
       "      <td>Chief Design Engineer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>27</td>\n",
       "      <td>4</td>\n",
       "      <td>27</td>\n",
       "      <td>Jessica</td>\n",
       "      <td>Bennett</td>\n",
       "      <td>Female</td>\n",
       "      <td>Twitternation</td>\n",
       "      <td>Account Executive</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>968</td>\n",
       "      <td>4</td>\n",
       "      <td>968</td>\n",
       "      <td>Teresa</td>\n",
       "      <td>Reynolds</td>\n",
       "      <td>Female</td>\n",
       "      <td>Flashdog</td>\n",
       "      <td>Budget/Accounting Analyst IV</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>969</td>\n",
       "      <td>3</td>\n",
       "      <td>969</td>\n",
       "      <td>Marie</td>\n",
       "      <td>Ortiz</td>\n",
       "      <td>Female</td>\n",
       "      <td>Meejo</td>\n",
       "      <td>Research Associate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>977</td>\n",
       "      <td>7</td>\n",
       "      <td>977</td>\n",
       "      <td>Cynthia</td>\n",
       "      <td>Dixon</td>\n",
       "      <td>Female</td>\n",
       "      <td>Skalith</td>\n",
       "      <td>Automation Specialist II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>994</td>\n",
       "      <td>2</td>\n",
       "      <td>994</td>\n",
       "      <td>Clarence</td>\n",
       "      <td>Morgan</td>\n",
       "      <td>Male</td>\n",
       "      <td>Edgewire</td>\n",
       "      <td>Geologist II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>996</td>\n",
       "      <td>10</td>\n",
       "      <td>996</td>\n",
       "      <td>Debra</td>\n",
       "      <td>Garcia</td>\n",
       "      <td>Female</td>\n",
       "      <td>Dazzlesphere</td>\n",
       "      <td>Structural Engineer</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>250 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer ID  Food ID   ID First Name Last Name  Gender        Company  \\\n",
       "0              8        6    8    Frances     Adams  Female       Dabshots   \n",
       "1             13        2   13       Ruth   Alvarez  Female    Twitterlist   \n",
       "2             21        4   21     Albert     Burns    Male      Rhynoodle   \n",
       "3             24        8   24      Donna    Thomas  Female        Jaxbean   \n",
       "4             27        4   27    Jessica   Bennett  Female  Twitternation   \n",
       "..           ...      ...  ...        ...       ...     ...            ...   \n",
       "245          968        4  968     Teresa  Reynolds  Female       Flashdog   \n",
       "246          969        3  969      Marie     Ortiz  Female          Meejo   \n",
       "247          977        7  977    Cynthia     Dixon  Female        Skalith   \n",
       "248          994        2  994   Clarence    Morgan    Male       Edgewire   \n",
       "249          996       10  996      Debra    Garcia  Female   Dazzlesphere   \n",
       "\n",
       "                       Occupation  \n",
       "0                   Developer III  \n",
       "1     Mechanical Systems Engineer  \n",
       "2                Junior Executive  \n",
       "3           Chief Design Engineer  \n",
       "4               Account Executive  \n",
       "..                            ...  \n",
       "245  Budget/Accounting Analyst IV  \n",
       "246            Research Associate  \n",
       "247      Automation Specialist II  \n",
       "248                  Geologist II  \n",
       "249           Structural Engineer  \n",
       "\n",
       "[250 rows x 8 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "week2.merge(customers, how = \"left\", left_on = \"Customer ID\", right_on = \"ID\", sort = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "024827b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Food ID</th>\n",
       "      <th>First Name</th>\n",
       "      <th>Last Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Company</th>\n",
       "      <th>Occupation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>Frances</td>\n",
       "      <td>Adams</td>\n",
       "      <td>Female</td>\n",
       "      <td>Dabshots</td>\n",
       "      <td>Developer III</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>Ruth</td>\n",
       "      <td>Alvarez</td>\n",
       "      <td>Female</td>\n",
       "      <td>Twitterlist</td>\n",
       "      <td>Mechanical Systems Engineer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21</td>\n",
       "      <td>4</td>\n",
       "      <td>Albert</td>\n",
       "      <td>Burns</td>\n",
       "      <td>Male</td>\n",
       "      <td>Rhynoodle</td>\n",
       "      <td>Junior Executive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24</td>\n",
       "      <td>8</td>\n",
       "      <td>Donna</td>\n",
       "      <td>Thomas</td>\n",
       "      <td>Female</td>\n",
       "      <td>Jaxbean</td>\n",
       "      <td>Chief Design Engineer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>27</td>\n",
       "      <td>4</td>\n",
       "      <td>Jessica</td>\n",
       "      <td>Bennett</td>\n",
       "      <td>Female</td>\n",
       "      <td>Twitternation</td>\n",
       "      <td>Account Executive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>968</td>\n",
       "      <td>4</td>\n",
       "      <td>Teresa</td>\n",
       "      <td>Reynolds</td>\n",
       "      <td>Female</td>\n",
       "      <td>Flashdog</td>\n",
       "      <td>Budget/Accounting Analyst IV</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>969</td>\n",
       "      <td>3</td>\n",
       "      <td>Marie</td>\n",
       "      <td>Ortiz</td>\n",
       "      <td>Female</td>\n",
       "      <td>Meejo</td>\n",
       "      <td>Research Associate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>977</td>\n",
       "      <td>7</td>\n",
       "      <td>Cynthia</td>\n",
       "      <td>Dixon</td>\n",
       "      <td>Female</td>\n",
       "      <td>Skalith</td>\n",
       "      <td>Automation Specialist II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>994</td>\n",
       "      <td>2</td>\n",
       "      <td>Clarence</td>\n",
       "      <td>Morgan</td>\n",
       "      <td>Male</td>\n",
       "      <td>Edgewire</td>\n",
       "      <td>Geologist II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>996</td>\n",
       "      <td>10</td>\n",
       "      <td>Debra</td>\n",
       "      <td>Garcia</td>\n",
       "      <td>Female</td>\n",
       "      <td>Dazzlesphere</td>\n",
       "      <td>Structural Engineer</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>250 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer ID  Food ID First Name Last Name  Gender        Company  \\\n",
       "0              8        6    Frances     Adams  Female       Dabshots   \n",
       "1             13        2       Ruth   Alvarez  Female    Twitterlist   \n",
       "2             21        4     Albert     Burns    Male      Rhynoodle   \n",
       "3             24        8      Donna    Thomas  Female        Jaxbean   \n",
       "4             27        4    Jessica   Bennett  Female  Twitternation   \n",
       "..           ...      ...        ...       ...     ...            ...   \n",
       "245          968        4     Teresa  Reynolds  Female       Flashdog   \n",
       "246          969        3      Marie     Ortiz  Female          Meejo   \n",
       "247          977        7    Cynthia     Dixon  Female        Skalith   \n",
       "248          994        2   Clarence    Morgan    Male       Edgewire   \n",
       "249          996       10      Debra    Garcia  Female   Dazzlesphere   \n",
       "\n",
       "                       Occupation  \n",
       "0                   Developer III  \n",
       "1     Mechanical Systems Engineer  \n",
       "2                Junior Executive  \n",
       "3           Chief Design Engineer  \n",
       "4               Account Executive  \n",
       "..                            ...  \n",
       "245  Budget/Accounting Analyst IV  \n",
       "246            Research Associate  \n",
       "247      Automation Specialist II  \n",
       "248                  Geologist II  \n",
       "249           Structural Engineer  \n",
       "\n",
       "[250 rows x 7 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "week2.merge(customers, how = \"left\", left_on = \"Customer ID\", right_on = \"ID\", sort = True).drop(\"ID\", axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "290a4c81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>2</th>\n",
       "      <td>21</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24</td>\n",
       "      <td>8</td>\n",
       "      <td>Donna</td>\n",
       "      <td>Thomas</td>\n",
       "      <td>Female</td>\n",
       "      <td>Jaxbean</td>\n",
       "      <td>Chief Design Engineer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>27</td>\n",
       "      <td>4</td>\n",
       "      <td>Jessica</td>\n",
       "      <td>Bennett</td>\n",
       "      <td>Female</td>\n",
       "      <td>Twitternation</td>\n",
       "      <td>Account Executive</td>\n",
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       "      <td>...</td>\n",
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       "      <td>3</td>\n",
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       "      <td>Ortiz</td>\n",
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       "      <td>Meejo</td>\n",
       "      <td>Research Associate</td>\n",
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       "      <th>247</th>\n",
       "      <td>977</td>\n",
       "      <td>7</td>\n",
       "      <td>Cynthia</td>\n",
       "      <td>Dixon</td>\n",
       "      <td>Female</td>\n",
       "      <td>Skalith</td>\n",
       "      <td>Automation Specialist II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>994</td>\n",
       "      <td>2</td>\n",
       "      <td>Clarence</td>\n",
       "      <td>Morgan</td>\n",
       "      <td>Male</td>\n",
       "      <td>Edgewire</td>\n",
       "      <td>Geologist II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>996</td>\n",
       "      <td>10</td>\n",
       "      <td>Debra</td>\n",
       "      <td>Garcia</td>\n",
       "      <td>Female</td>\n",
       "      <td>Dazzlesphere</td>\n",
       "      <td>Structural Engineer</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>250 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer ID  Food ID First Name Last Name  Gender        Company  \\\n",
       "0              8        6    Frances     Adams  Female       Dabshots   \n",
       "1             13        2       Ruth   Alvarez  Female    Twitterlist   \n",
       "2             21        4     Albert     Burns    Male      Rhynoodle   \n",
       "3             24        8      Donna    Thomas  Female        Jaxbean   \n",
       "4             27        4    Jessica   Bennett  Female  Twitternation   \n",
       "..           ...      ...        ...       ...     ...            ...   \n",
       "245          968        4     Teresa  Reynolds  Female       Flashdog   \n",
       "246          969        3      Marie     Ortiz  Female          Meejo   \n",
       "247          977        7    Cynthia     Dixon  Female        Skalith   \n",
       "248          994        2   Clarence    Morgan    Male       Edgewire   \n",
       "249          996       10      Debra    Garcia  Female   Dazzlesphere   \n",
       "\n",
       "                       Occupation  \n",
       "0                   Developer III  \n",
       "1     Mechanical Systems Engineer  \n",
       "2                Junior Executive  \n",
       "3           Chief Design Engineer  \n",
       "4               Account Executive  \n",
       "..                            ...  \n",
       "245  Budget/Accounting Analyst IV  \n",
       "246            Research Associate  \n",
       "247      Automation Specialist II  \n",
       "248                  Geologist II  \n",
       "249           Structural Engineer  \n",
       "\n",
       "[250 rows x 7 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "week2.merge(customers, how = \"left\", left_on = \"Customer ID\", right_on = \"ID\", sort = True).drop(\"ID\", axis = \"columns\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff83d7fc",
   "metadata": {},
   "source": [
    "# Merging by Indexes with left_index and right_index Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "d38e36f2",
   "metadata": {},
   "outputs": [],
   "source": [
    "week1 = pd.read_csv(\"Restaurant - Week 1 Sales.csv\")\n",
    "week2 = pd.read_csv(\"Restaurant - Week 2 Sales.csv\")\n",
    "customers = pd.read_csv(\"Restaurant - Customers.csv\")\n",
    "foods = pd.read_csv(\"Restaurant - Foods.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "17cc1e7e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Food ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>537</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>97</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>658</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>202</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>155</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Customer ID  Food ID\n",
       "0          537        9\n",
       "1           97        4\n",
       "2          658        1\n",
       "3          202        2\n",
       "4          155        9"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "week1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "1cea3e72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>First Name</th>\n",
       "      <th>Last Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Company</th>\n",
       "      <th>Occupation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Joseph</td>\n",
       "      <td>Perkins</td>\n",
       "      <td>Male</td>\n",
       "      <td>Dynazzy</td>\n",
       "      <td>Community Outreach Specialist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Jennifer</td>\n",
       "      <td>Alvarez</td>\n",
       "      <td>Female</td>\n",
       "      <td>DabZ</td>\n",
       "      <td>Senior Quality Engineer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Roger</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>Tagfeed</td>\n",
       "      <td>Account Executive</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID First Name Last Name  Gender  Company                     Occupation\n",
       "0   1     Joseph   Perkins    Male  Dynazzy  Community Outreach Specialist\n",
       "1   2   Jennifer   Alvarez  Female     DabZ        Senior Quality Engineer\n",
       "2   3      Roger     Black    Male  Tagfeed              Account Executive"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customers.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "0ee71fdd",
   "metadata": {},
   "outputs": [],
   "source": [
    "customers.set_index(\"ID\", inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "2ad2bf11",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Food ID</th>\n",
       "      <th>First Name</th>\n",
       "      <th>Last Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Company</th>\n",
       "      <th>Occupation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>537</td>\n",
       "      <td>9</td>\n",
       "      <td>Cheryl</td>\n",
       "      <td>Carroll</td>\n",
       "      <td>Female</td>\n",
       "      <td>Zoombeat</td>\n",
       "      <td>Registered Nurse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>97</td>\n",
       "      <td>4</td>\n",
       "      <td>Amanda</td>\n",
       "      <td>Watkins</td>\n",
       "      <td>Female</td>\n",
       "      <td>Ozu</td>\n",
       "      <td>Account Coordinator</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>658</td>\n",
       "      <td>1</td>\n",
       "      <td>Patrick</td>\n",
       "      <td>Webb</td>\n",
       "      <td>Male</td>\n",
       "      <td>Browsebug</td>\n",
       "      <td>Community Outreach Specialist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>202</td>\n",
       "      <td>2</td>\n",
       "      <td>Louis</td>\n",
       "      <td>Campbell</td>\n",
       "      <td>Male</td>\n",
       "      <td>Rhynoodle</td>\n",
       "      <td>Account Representative III</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>155</td>\n",
       "      <td>9</td>\n",
       "      <td>Carolyn</td>\n",
       "      <td>Diaz</td>\n",
       "      <td>Female</td>\n",
       "      <td>Gigazoom</td>\n",
       "      <td>Database Administrator III</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>413</td>\n",
       "      <td>9</td>\n",
       "      <td>Diane</td>\n",
       "      <td>Bailey</td>\n",
       "      <td>Female</td>\n",
       "      <td>Wikibox</td>\n",
       "      <td>Technical Writer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>926</td>\n",
       "      <td>6</td>\n",
       "      <td>Anne</td>\n",
       "      <td>Wagner</td>\n",
       "      <td>Female</td>\n",
       "      <td>Skyba</td>\n",
       "      <td>Legal Assistant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>134</td>\n",
       "      <td>3</td>\n",
       "      <td>Diana</td>\n",
       "      <td>Hall</td>\n",
       "      <td>Female</td>\n",
       "      <td>Quinu</td>\n",
       "      <td>Financial Advisor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>396</td>\n",
       "      <td>6</td>\n",
       "      <td>Juan</td>\n",
       "      <td>Romero</td>\n",
       "      <td>Male</td>\n",
       "      <td>Zoonder</td>\n",
       "      <td>Analyst Programmer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>535</td>\n",
       "      <td>10</td>\n",
       "      <td>Nancy</td>\n",
       "      <td>Cox</td>\n",
       "      <td>Female</td>\n",
       "      <td>Trudeo</td>\n",
       "      <td>Research Associate</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>250 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer ID  Food ID First Name Last Name  Gender    Company  \\\n",
       "0            537        9     Cheryl   Carroll  Female   Zoombeat   \n",
       "1             97        4     Amanda   Watkins  Female        Ozu   \n",
       "2            658        1    Patrick      Webb    Male  Browsebug   \n",
       "3            202        2      Louis  Campbell    Male  Rhynoodle   \n",
       "4            155        9    Carolyn      Diaz  Female   Gigazoom   \n",
       "..           ...      ...        ...       ...     ...        ...   \n",
       "245          413        9      Diane    Bailey  Female    Wikibox   \n",
       "246          926        6       Anne    Wagner  Female      Skyba   \n",
       "247          134        3      Diana      Hall  Female      Quinu   \n",
       "248          396        6       Juan    Romero    Male    Zoonder   \n",
       "249          535       10      Nancy       Cox  Female     Trudeo   \n",
       "\n",
       "                        Occupation  \n",
       "0                 Registered Nurse  \n",
       "1              Account Coordinator  \n",
       "2    Community Outreach Specialist  \n",
       "3       Account Representative III  \n",
       "4       Database Administrator III  \n",
       "..                             ...  \n",
       "245               Technical Writer  \n",
       "246                Legal Assistant  \n",
       "247              Financial Advisor  \n",
       "248             Analyst Programmer  \n",
       "249             Research Associate  \n",
       "\n",
       "[250 rows x 7 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "week1.merge(customers, how = \"left\", left_on = \"Customer ID\", right_index = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "c5c4c0b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Food ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>537</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>97</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>658</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>202</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>155</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Customer ID  Food ID\n",
       "0          537        9\n",
       "1           97        4\n",
       "2          658        1\n",
       "3          202        2\n",
       "4          155        9"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "week1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "bd9c90c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Food ID_x</th>\n",
       "      <th>Food ID_y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Customer ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>966</th>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>968</th>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>985</th>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991</th>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000</th>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>257 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Food ID_x  Food ID_y\n",
       "Customer ID                      \n",
       "3                    2        NaN\n",
       "10                   2        NaN\n",
       "20                   1        NaN\n",
       "21                   4        4.0\n",
       "21                   4        4.0\n",
       "...                ...        ...\n",
       "966                  5        NaN\n",
       "968                  1        4.0\n",
       "985                  5        NaN\n",
       "991                  2        NaN\n",
       "1000                 2        NaN\n",
       "\n",
       "[257 rows x 2 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "week2.set_index(\"Customer ID\", inplace = True)\n",
    "week1.set_index(\"Customer ID\", inplace = True)\n",
    "week1.merge(week2, how = \"left\", left_index = True, right_index = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7612c0f3",
   "metadata": {},
   "source": [
    "# join() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "da1a21b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "week1 = pd.read_csv(\"Restaurant - Week 1 Sales.csv\")\n",
    "week2 = pd.read_csv(\"Restaurant - Week 2 Sales.csv\")\n",
    "customers = pd.read_csv(\"Restaurant - Customers.csv\")\n",
    "foods = pd.read_csv(\"Restaurant - Foods.csv\")\n",
    "satisfaction = pd.read_csv(\"Restaurant - Week 1 Satisfaction.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "9e77ad81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Satisfaction Rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Satisfaction Rating\n",
       "0                    2\n",
       "1                    7\n",
       "2                    3"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "satisfaction.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "49c50218",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Food ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>537</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>97</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>658</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Customer ID  Food ID\n",
       "0          537        9\n",
       "1           97        4\n",
       "2          658        1"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "week1.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e5055f99",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Food ID</th>\n",
       "      <th>Satisfaction Rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>537</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>97</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>658</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>202</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>155</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>413</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>926</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>134</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>396</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>535</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>250 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer ID  Food ID  Satisfaction Rating\n",
       "0            537        9                    2\n",
       "1             97        4                    7\n",
       "2            658        1                    3\n",
       "3            202        2                    7\n",
       "4            155        9                   10\n",
       "..           ...      ...                  ...\n",
       "245          413        9                    1\n",
       "246          926        6                    2\n",
       "247          134        3                    8\n",
       "248          396        6                   10\n",
       "249          535       10                    3\n",
       "\n",
       "[250 rows x 3 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "week1.join(satisfaction)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16531b3d",
   "metadata": {},
   "source": [
    "# pd.merge()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "0c6c442b",
   "metadata": {},
   "outputs": [],
   "source": [
    "week1 = pd.read_csv(\"Restaurant - Week 1 Sales.csv\")\n",
    "week2 = pd.read_csv(\"Restaurant - Week 2 Sales.csv\")\n",
    "customers = pd.read_csv(\"Restaurant - Customers.csv\")\n",
    "foods = pd.read_csv(\"Restaurant - Foods.csv\")\n",
    "satisfaction = pd.read_csv(\"Restaurant - Week 1 Satisfaction.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "621bd13d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Food ID_x</th>\n",
       "      <th>Food ID_y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Customer ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>966</th>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>968</th>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>985</th>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991</th>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000</th>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>257 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Food ID_x  Food ID_y\n",
       "Customer ID                      \n",
       "3                    2        NaN\n",
       "10                   2        NaN\n",
       "20                   1        NaN\n",
       "21                   4        4.0\n",
       "21                   4        4.0\n",
       "...                ...        ...\n",
       "966                  5        NaN\n",
       "968                  1        4.0\n",
       "985                  5        NaN\n",
       "991                  2        NaN\n",
       "1000                 2        NaN\n",
       "\n",
       "[257 rows x 2 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "week2.set_index(\"Customer ID\", inplace = True)\n",
    "week1.set_index(\"Customer ID\", inplace = True)\n",
    "pd.merge(week1, week2, how = \"left\", left_index = True, right_index = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fdbde921",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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