sneak_peak.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Sneak Peak\n",
    "\n",
    "This file gives a simple overview of each of the datasets for the project. You can use this as a quick reference guide for what the base datasets look like before doing further exploratory analysis."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reading in the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We import the `pandas` library as well as a helper function `read_in_data` to get the provided datasets into `DataFrames` so we can see what they look like. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from helpers import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "dish_df, menu_df, menu_item_df, menu_page_df = read_in_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dish Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>name</th>\n",
       "      <th>description</th>\n",
       "      <th>menus_appeared</th>\n",
       "      <th>times_appeared</th>\n",
       "      <th>first_appeared</th>\n",
       "      <th>last_appeared</th>\n",
       "      <th>lowest_price</th>\n",
       "      <th>highest_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Consomme printaniere royal</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>1897</td>\n",
       "      <td>1927</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Chicken gumbo</td>\n",
       "      <td>NaN</td>\n",
       "      <td>111</td>\n",
       "      <td>117</td>\n",
       "      <td>1895</td>\n",
       "      <td>1960</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Tomato aux croutons</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>1893</td>\n",
       "      <td>1917</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Onion au gratin</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41</td>\n",
       "      <td>41</td>\n",
       "      <td>1900</td>\n",
       "      <td>1971</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>St. Emilion</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66</td>\n",
       "      <td>68</td>\n",
       "      <td>1881</td>\n",
       "      <td>1981</td>\n",
       "      <td>0.00</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id                        name  description  menus_appeared  \\\n",
       "0   1  Consomme printaniere royal          NaN               8   \n",
       "1   2               Chicken gumbo          NaN             111   \n",
       "2   3         Tomato aux croutons          NaN              13   \n",
       "3   4             Onion au gratin          NaN              41   \n",
       "4   5                 St. Emilion          NaN              66   \n",
       "\n",
       "   times_appeared  first_appeared  last_appeared  lowest_price  highest_price  \n",
       "0               8            1897           1927          0.20            0.4  \n",
       "1             117            1895           1960          0.10            0.8  \n",
       "2              13            1893           1917          0.25            0.4  \n",
       "3              41            1900           1971          0.25            1.0  \n",
       "4              68            1881           1981          0.00           18.0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dish_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 423397 entries, 0 to 423396\n",
      "Data columns (total 9 columns):\n",
      " #   Column          Non-Null Count   Dtype  \n",
      "---  ------          --------------   -----  \n",
      " 0   id              423397 non-null  int64  \n",
      " 1   name            423397 non-null  object \n",
      " 2   description     0 non-null       float64\n",
      " 3   menus_appeared  423397 non-null  int64  \n",
      " 4   times_appeared  423397 non-null  int64  \n",
      " 5   first_appeared  423397 non-null  int64  \n",
      " 6   last_appeared   423397 non-null  int64  \n",
      " 7   lowest_price    394297 non-null  float64\n",
      " 8   highest_price   394297 non-null  float64\n",
      "dtypes: float64(3), int64(5), object(1)\n",
      "memory usage: 29.1+ MB\n"
     ]
    }
   ],
   "source": [
    "dish_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Menu Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>name</th>\n",
       "      <th>sponsor</th>\n",
       "      <th>event</th>\n",
       "      <th>venue</th>\n",
       "      <th>place</th>\n",
       "      <th>physical_description</th>\n",
       "      <th>occasion</th>\n",
       "      <th>notes</th>\n",
       "      <th>call_number</th>\n",
       "      <th>keywords</th>\n",
       "      <th>language</th>\n",
       "      <th>date</th>\n",
       "      <th>location</th>\n",
       "      <th>location_type</th>\n",
       "      <th>currency</th>\n",
       "      <th>currency_symbol</th>\n",
       "      <th>status</th>\n",
       "      <th>page_count</th>\n",
       "      <th>dish_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12463</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HOTEL EASTMAN</td>\n",
       "      <td>BREAKFAST</td>\n",
       "      <td>COMMERCIAL</td>\n",
       "      <td>HOT SPRINGS, AR</td>\n",
       "      <td>CARD; 4.75X7.5;</td>\n",
       "      <td>EASTER;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1900-2822</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1900-04-15</td>\n",
       "      <td>Hotel Eastman</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>complete</td>\n",
       "      <td>2</td>\n",
       "      <td>67</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12464</td>\n",
       "      <td>NaN</td>\n",
       "      <td>REPUBLICAN HOUSE</td>\n",
       "      <td>[DINNER]</td>\n",
       "      <td>COMMERCIAL</td>\n",
       "      <td>MILWAUKEE, [WI];</td>\n",
       "      <td>CARD; ILLUS; COL; 7.0X9.0;</td>\n",
       "      <td>EASTER;</td>\n",
       "      <td>WEDGEWOOD BLUE CARD; WHITE EMBOSSED GREEK KEY ...</td>\n",
       "      <td>1900-2825</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1900-04-15</td>\n",
       "      <td>Republican House</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>under review</td>\n",
       "      <td>2</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12465</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NORDDEUTSCHER LLOYD BREMEN</td>\n",
       "      <td>FRUHSTUCK/BREAKFAST;</td>\n",
       "      <td>COMMERCIAL</td>\n",
       "      <td>DAMPFER KAISER WILHELM DER GROSSE;</td>\n",
       "      <td>CARD; ILLU; COL; 5.5X8.0;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MENU IN GERMAN AND ENGLISH; ILLUS, STEAMSHIP A...</td>\n",
       "      <td>1900-2827</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1900-04-16</td>\n",
       "      <td>Norddeutscher Lloyd Bremen</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>complete</td>\n",
       "      <td>2</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12466</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NORDDEUTSCHER LLOYD BREMEN</td>\n",
       "      <td>LUNCH;</td>\n",
       "      <td>COMMERCIAL</td>\n",
       "      <td>DAMPFER KAISER WILHELM DER GROSSE;</td>\n",
       "      <td>CARD; ILLU; COL; 5.5X8.0;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MENU IN GERMAN AND ENGLISH; ILLUS, HARBOR SCEN...</td>\n",
       "      <td>1900-2828</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1900-04-16</td>\n",
       "      <td>Norddeutscher Lloyd Bremen</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>complete</td>\n",
       "      <td>2</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12467</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NORDDEUTSCHER LLOYD BREMEN</td>\n",
       "      <td>DINNER;</td>\n",
       "      <td>COMMERCIAL</td>\n",
       "      <td>DAMPFER KAISER WILHELM DER GROSSE;</td>\n",
       "      <td>FOLDER; ILLU; COL; 5.5X7.5;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MENU IN GERMAN AND ENGLISH; ILLUS, HARBOR SCEN...</td>\n",
       "      <td>1900-2829</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1900-04-16</td>\n",
       "      <td>Norddeutscher Lloyd Bremen</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>complete</td>\n",
       "      <td>4</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "      id name                     sponsor                 event       venue  \\\n",
       "0  12463  NaN               HOTEL EASTMAN             BREAKFAST  COMMERCIAL   \n",
       "1  12464  NaN            REPUBLICAN HOUSE              [DINNER]  COMMERCIAL   \n",
       "2  12465  NaN  NORDDEUTSCHER LLOYD BREMEN  FRUHSTUCK/BREAKFAST;  COMMERCIAL   \n",
       "3  12466  NaN  NORDDEUTSCHER LLOYD BREMEN                LUNCH;  COMMERCIAL   \n",
       "4  12467  NaN  NORDDEUTSCHER LLOYD BREMEN               DINNER;  COMMERCIAL   \n",
       "\n",
       "                                place         physical_description occasion  \\\n",
       "0                     HOT SPRINGS, AR              CARD; 4.75X7.5;  EASTER;   \n",
       "1                    MILWAUKEE, [WI];   CARD; ILLUS; COL; 7.0X9.0;  EASTER;   \n",
       "2  DAMPFER KAISER WILHELM DER GROSSE;    CARD; ILLU; COL; 5.5X8.0;      NaN   \n",
       "3  DAMPFER KAISER WILHELM DER GROSSE;    CARD; ILLU; COL; 5.5X8.0;      NaN   \n",
       "4  DAMPFER KAISER WILHELM DER GROSSE;  FOLDER; ILLU; COL; 5.5X7.5;      NaN   \n",
       "\n",
       "                                               notes call_number  keywords  \\\n",
       "0                                                NaN   1900-2822       NaN   \n",
       "1  WEDGEWOOD BLUE CARD; WHITE EMBOSSED GREEK KEY ...   1900-2825       NaN   \n",
       "2  MENU IN GERMAN AND ENGLISH; ILLUS, STEAMSHIP A...   1900-2827       NaN   \n",
       "3  MENU IN GERMAN AND ENGLISH; ILLUS, HARBOR SCEN...   1900-2828       NaN   \n",
       "4  MENU IN GERMAN AND ENGLISH; ILLUS, HARBOR SCEN...   1900-2829       NaN   \n",
       "\n",
       "   language        date                    location  location_type currency  \\\n",
       "0       NaN  1900-04-15               Hotel Eastman            NaN      NaN   \n",
       "1       NaN  1900-04-15            Republican House            NaN      NaN   \n",
       "2       NaN  1900-04-16  Norddeutscher Lloyd Bremen            NaN      NaN   \n",
       "3       NaN  1900-04-16  Norddeutscher Lloyd Bremen            NaN      NaN   \n",
       "4       NaN  1900-04-16  Norddeutscher Lloyd Bremen            NaN      NaN   \n",
       "\n",
       "  currency_symbol        status  page_count  dish_count  \n",
       "0             NaN      complete           2          67  \n",
       "1             NaN  under review           2          34  \n",
       "2             NaN      complete           2          84  \n",
       "3             NaN      complete           2          63  \n",
       "4             NaN      complete           4          33  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "menu_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 17545 entries, 0 to 17544\n",
      "Data columns (total 20 columns):\n",
      " #   Column                Non-Null Count  Dtype  \n",
      "---  ------                --------------  -----  \n",
      " 0   id                    17545 non-null  int64  \n",
      " 1   name                  3197 non-null   object \n",
      " 2   sponsor               15984 non-null  object \n",
      " 3   event                 8154 non-null   object \n",
      " 4   venue                 8119 non-null   object \n",
      " 5   place                 8123 non-null   object \n",
      " 6   physical_description  14763 non-null  object \n",
      " 7   occasion              3791 non-null   object \n",
      " 8   notes                 10613 non-null  object \n",
      " 9   call_number           15983 non-null  object \n",
      " 10  keywords              0 non-null      float64\n",
      " 11  language              0 non-null      float64\n",
      " 12  date                  16959 non-null  object \n",
      " 13  location              17545 non-null  object \n",
      " 14  location_type         0 non-null      float64\n",
      " 15  currency              6456 non-null   object \n",
      " 16  currency_symbol       6456 non-null   object \n",
      " 17  status                17545 non-null  object \n",
      " 18  page_count            17545 non-null  int64  \n",
      " 19  dish_count            17545 non-null  int64  \n",
      "dtypes: float64(3), int64(3), object(14)\n",
      "memory usage: 2.7+ MB\n"
     ]
    }
   ],
   "source": [
    "menu_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MenuItem Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
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       "      <th>menu_page_id</th>\n",
       "      <th>price</th>\n",
       "      <th>high_price</th>\n",
       "      <th>dish_id</th>\n",
       "      <th>created_at</th>\n",
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       "      <td>2011-03-28 15:00:44 UTC</td>\n",
       "      <td>2011-04-19 04:33:15 UTC</td>\n",
       "      <td>0.111429</td>\n",
       "      <td>0.254735</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1389</td>\n",
       "      <td>0.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2011-03-28 15:01:13 UTC</td>\n",
       "      <td>2011-04-19 15:00:54 UTC</td>\n",
       "      <td>0.438571</td>\n",
       "      <td>0.254735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1389</td>\n",
       "      <td>0.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2011-03-28 15:01:40 UTC</td>\n",
       "      <td>2011-04-19 19:10:05 UTC</td>\n",
       "      <td>0.140000</td>\n",
       "      <td>0.261922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1389</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2011-03-28 15:01:51 UTC</td>\n",
       "      <td>2011-04-19 19:07:01 UTC</td>\n",
       "      <td>0.377143</td>\n",
       "      <td>0.262720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>3079</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2011-03-28 15:21:26 UTC</td>\n",
       "      <td>2011-04-13 15:25:27 UTC</td>\n",
       "      <td>0.105714</td>\n",
       "      <td>0.313178</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  menu_page_id  price  high_price  dish_id               created_at  \\\n",
       "0   1          1389    0.4         NaN      1.0  2011-03-28 15:00:44 UTC   \n",
       "1   2          1389    0.6         NaN      2.0  2011-03-28 15:01:13 UTC   \n",
       "2   3          1389    0.4         NaN      3.0  2011-03-28 15:01:40 UTC   \n",
       "3   4          1389    0.5         NaN      4.0  2011-03-28 15:01:51 UTC   \n",
       "4   5          3079    0.5         1.0      5.0  2011-03-28 15:21:26 UTC   \n",
       "\n",
       "                updated_at      xpos      ypos  \n",
       "0  2011-04-19 04:33:15 UTC  0.111429  0.254735  \n",
       "1  2011-04-19 15:00:54 UTC  0.438571  0.254735  \n",
       "2  2011-04-19 19:10:05 UTC  0.140000  0.261922  \n",
       "3  2011-04-19 19:07:01 UTC  0.377143  0.262720  \n",
       "4  2011-04-13 15:25:27 UTC  0.105714  0.313178  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "menu_item_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1332726 entries, 0 to 1332725\n",
      "Data columns (total 9 columns):\n",
      " #   Column        Non-Null Count    Dtype  \n",
      "---  ------        --------------    -----  \n",
      " 0   id            1332726 non-null  int64  \n",
      " 1   menu_page_id  1332726 non-null  int64  \n",
      " 2   price         886810 non-null   float64\n",
      " 3   high_price    91905 non-null    float64\n",
      " 4   dish_id       1332485 non-null  float64\n",
      " 5   created_at    1332726 non-null  object \n",
      " 6   updated_at    1332726 non-null  object \n",
      " 7   xpos          1332726 non-null  float64\n",
      " 8   ypos          1332726 non-null  float64\n",
      "dtypes: float64(5), int64(2), object(2)\n",
      "memory usage: 91.5+ MB\n"
     ]
    }
   ],
   "source": [
    "menu_item_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MenuPage Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>menu_id</th>\n",
       "      <th>page_number</th>\n",
       "      <th>image_id</th>\n",
       "      <th>full_height</th>\n",
       "      <th>full_width</th>\n",
       "      <th>uuid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>119</td>\n",
       "      <td>12460</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1603595</td>\n",
       "      <td>7230.0</td>\n",
       "      <td>5428.0</td>\n",
       "      <td>510d47e4-2955-a3d9-e040-e00a18064a99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>120</td>\n",
       "      <td>12460</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1603596</td>\n",
       "      <td>5428.0</td>\n",
       "      <td>7230.0</td>\n",
       "      <td>510d47e4-2956-a3d9-e040-e00a18064a99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>121</td>\n",
       "      <td>12460</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1603597</td>\n",
       "      <td>7230.0</td>\n",
       "      <td>5428.0</td>\n",
       "      <td>510d47e4-2957-a3d9-e040-e00a18064a99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>122</td>\n",
       "      <td>12460</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1603598</td>\n",
       "      <td>7230.0</td>\n",
       "      <td>5428.0</td>\n",
       "      <td>510d47e4-2958-a3d9-e040-e00a18064a99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>123</td>\n",
       "      <td>12461</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1603591</td>\n",
       "      <td>7230.0</td>\n",
       "      <td>5428.0</td>\n",
       "      <td>510d47e4-2959-a3d9-e040-e00a18064a99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id  menu_id  page_number image_id  full_height  full_width  \\\n",
       "0  119    12460          1.0  1603595       7230.0      5428.0   \n",
       "1  120    12460          2.0  1603596       5428.0      7230.0   \n",
       "2  121    12460          3.0  1603597       7230.0      5428.0   \n",
       "3  122    12460          4.0  1603598       7230.0      5428.0   \n",
       "4  123    12461          1.0  1603591       7230.0      5428.0   \n",
       "\n",
       "                                   uuid  \n",
       "0  510d47e4-2955-a3d9-e040-e00a18064a99  \n",
       "1  510d47e4-2956-a3d9-e040-e00a18064a99  \n",
       "2  510d47e4-2957-a3d9-e040-e00a18064a99  \n",
       "3  510d47e4-2958-a3d9-e040-e00a18064a99  \n",
       "4  510d47e4-2959-a3d9-e040-e00a18064a99  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "menu_page_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 66937 entries, 0 to 66936\n",
      "Data columns (total 7 columns):\n",
      " #   Column       Non-Null Count  Dtype  \n",
      "---  ------       --------------  -----  \n",
      " 0   id           66937 non-null  int64  \n",
      " 1   menu_id      66937 non-null  int64  \n",
      " 2   page_number  65735 non-null  float64\n",
      " 3   image_id     66937 non-null  object \n",
      " 4   full_height  66608 non-null  float64\n",
      " 5   full_width   66608 non-null  float64\n",
      " 6   uuid         66937 non-null  object \n",
      "dtypes: float64(3), int64(2), object(2)\n",
      "memory usage: 3.6+ MB\n"
     ]
    }
   ],
   "source": [
    "menu_page_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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