LEGO Data Analysis - Answered.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3adc098c",
   "metadata": {},
   "source": [
    "# LEGO Data Analysis - Rebrickable"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da2515b3",
   "metadata": {},
   "source": [
    "The dataset is from https://rebrickable.com/downloads/. \n",
    "\n",
    "From the Rebrickable website - \"The LEGO Parts/Sets/Colors and Inventories of every official LEGO set in the Rebrickable database is available for download as csv files here. These files are automatically updated daily. If you need more details, you can use the API which provides real-time data, but has rate limits that prevent bulk downloading of data.\"\n",
    "\n",
    "Rebrickable provides this database to be used for any purpose."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6264928c",
   "metadata": {},
   "source": [
    "## LEGO Data Model"
   ]
  },
  {
   "attachments": {
    "downloads_schema_v3.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "32ec6d94",
   "metadata": {},
   "source": [
    "![downloads_schema_v3.png](attachment:downloads_schema_v3.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65c8d7a4",
   "metadata": {},
   "source": [
    "#### Importing Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a5c441ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "#pip install pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3ee02051",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24ae49a0",
   "metadata": {},
   "source": [
    "#### Getting Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f2dac057",
   "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>set_num</th>\n",
       "      <th>name</th>\n",
       "      <th>year</th>\n",
       "      <th>theme_id</th>\n",
       "      <th>num_parts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>001-1</td>\n",
       "      <td>Gears</td>\n",
       "      <td>1965</td>\n",
       "      <td>1</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0011-2</td>\n",
       "      <td>Town Mini-Figures</td>\n",
       "      <td>1979</td>\n",
       "      <td>67</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0011-3</td>\n",
       "      <td>Castle 2 for 1 Bonus Offer</td>\n",
       "      <td>1987</td>\n",
       "      <td>199</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0012-1</td>\n",
       "      <td>Space Mini-Figures</td>\n",
       "      <td>1979</td>\n",
       "      <td>143</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0013-1</td>\n",
       "      <td>Space Mini-Figures</td>\n",
       "      <td>1979</td>\n",
       "      <td>143</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18909</th>\n",
       "      <td>XWING-1</td>\n",
       "      <td>Mini X-Wing Fighter</td>\n",
       "      <td>2019</td>\n",
       "      <td>158</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18910</th>\n",
       "      <td>XWING-2</td>\n",
       "      <td>X-Wing Trench Run</td>\n",
       "      <td>2019</td>\n",
       "      <td>158</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18911</th>\n",
       "      <td>YODACHRON-1</td>\n",
       "      <td>Yoda Chronicles Promotional Set</td>\n",
       "      <td>2013</td>\n",
       "      <td>158</td>\n",
       "      <td>413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18912</th>\n",
       "      <td>YTERRIER-1</td>\n",
       "      <td>Yorkshire Terrier</td>\n",
       "      <td>2018</td>\n",
       "      <td>598</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18913</th>\n",
       "      <td>ZX8000-1</td>\n",
       "      <td>ZX 8000 LEGO Sneaker</td>\n",
       "      <td>2020</td>\n",
       "      <td>501</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18914 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           set_num                             name  year  theme_id  num_parts\n",
       "0            001-1                            Gears  1965         1         43\n",
       "1           0011-2                Town Mini-Figures  1979        67         12\n",
       "2           0011-3       Castle 2 for 1 Bonus Offer  1987       199          0\n",
       "3           0012-1               Space Mini-Figures  1979       143         12\n",
       "4           0013-1               Space Mini-Figures  1979       143         12\n",
       "...            ...                              ...   ...       ...        ...\n",
       "18909      XWING-1              Mini X-Wing Fighter  2019       158         60\n",
       "18910      XWING-2                X-Wing Trench Run  2019       158         52\n",
       "18911  YODACHRON-1  Yoda Chronicles Promotional Set  2013       158        413\n",
       "18912   YTERRIER-1                Yorkshire Terrier  2018       598          0\n",
       "18913     ZX8000-1             ZX 8000 LEGO Sneaker  2020       501          0\n",
       "\n",
       "[18914 rows x 5 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sets = pd.read_csv('data_source/sets.csv')\n",
    "sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e8576500",
   "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>name</th>\n",
       "      <th>parent_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Technic</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>Competition</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>Expert Builder</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16</td>\n",
       "      <td>RoboRiders</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17</td>\n",
       "      <td>Speed Slammers</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>715</td>\n",
       "      <td>Marvel</td>\n",
       "      <td>535.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>716</td>\n",
       "      <td>Modulex</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>441</th>\n",
       "      <td>717</td>\n",
       "      <td>Speed Racer</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>442</th>\n",
       "      <td>718</td>\n",
       "      <td>Series 22 Minifigures</td>\n",
       "      <td>535.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443</th>\n",
       "      <td>719</td>\n",
       "      <td>BrickLink Designer Program</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>444 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      id                        name  parent_id\n",
       "0      1                     Technic        NaN\n",
       "1      3                 Competition        1.0\n",
       "2      4              Expert Builder        1.0\n",
       "3     16                  RoboRiders        1.0\n",
       "4     17              Speed Slammers        1.0\n",
       "..   ...                         ...        ...\n",
       "439  715                      Marvel      535.0\n",
       "440  716                     Modulex        NaN\n",
       "441  717                 Speed Racer        NaN\n",
       "442  718       Series 22 Minifigures      535.0\n",
       "443  719  BrickLink Designer Program        NaN\n",
       "\n",
       "[444 rows x 3 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "themes = pd.read_csv('data_source/themes.csv')\n",
    "themes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc69c8a5",
   "metadata": {},
   "source": [
    "#### Display Top 10 Rows of the sets dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7e95329e",
   "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>set_num</th>\n",
       "      <th>name</th>\n",
       "      <th>year</th>\n",
       "      <th>theme_id</th>\n",
       "      <th>num_parts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>001-1</td>\n",
       "      <td>Gears</td>\n",
       "      <td>1965</td>\n",
       "      <td>1</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0011-2</td>\n",
       "      <td>Town Mini-Figures</td>\n",
       "      <td>1979</td>\n",
       "      <td>67</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0011-3</td>\n",
       "      <td>Castle 2 for 1 Bonus Offer</td>\n",
       "      <td>1987</td>\n",
       "      <td>199</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0012-1</td>\n",
       "      <td>Space Mini-Figures</td>\n",
       "      <td>1979</td>\n",
       "      <td>143</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0013-1</td>\n",
       "      <td>Space Mini-Figures</td>\n",
       "      <td>1979</td>\n",
       "      <td>143</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0014-1</td>\n",
       "      <td>Space Mini-Figures</td>\n",
       "      <td>1979</td>\n",
       "      <td>143</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0015-1</td>\n",
       "      <td>Space Mini-Figures</td>\n",
       "      <td>1979</td>\n",
       "      <td>143</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0016-1</td>\n",
       "      <td>Castle Mini Figures</td>\n",
       "      <td>1979</td>\n",
       "      <td>186</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>002-1</td>\n",
       "      <td>4.5V Samsonite Gears Motor Set</td>\n",
       "      <td>1965</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>003-1</td>\n",
       "      <td>Master Mechanic Set</td>\n",
       "      <td>1966</td>\n",
       "      <td>366</td>\n",
       "      <td>403</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  set_num                            name  year  theme_id  num_parts\n",
       "0   001-1                           Gears  1965         1         43\n",
       "1  0011-2               Town Mini-Figures  1979        67         12\n",
       "2  0011-3      Castle 2 for 1 Bonus Offer  1987       199          0\n",
       "3  0012-1              Space Mini-Figures  1979       143         12\n",
       "4  0013-1              Space Mini-Figures  1979       143         12\n",
       "5  0014-1              Space Mini-Figures  1979       143         12\n",
       "6  0015-1              Space Mini-Figures  1979       143         18\n",
       "7  0016-1             Castle Mini Figures  1979       186         15\n",
       "8   002-1  4.5V Samsonite Gears Motor Set  1965         1          3\n",
       "9   003-1             Master Mechanic Set  1966       366        403"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sets.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9914c48",
   "metadata": {},
   "source": [
    "#### Display Last 10 Rows of the sets dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "460a7729",
   "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>set_num</th>\n",
       "      <th>name</th>\n",
       "      <th>year</th>\n",
       "      <th>theme_id</th>\n",
       "      <th>num_parts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18904</th>\n",
       "      <td>XBOXGAME-1</td>\n",
       "      <td>Batman the Videogame - Xbox 360</td>\n",
       "      <td>2008</td>\n",
       "      <td>501</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18905</th>\n",
       "      <td>XBOXGAME-2</td>\n",
       "      <td>Bionicle Heroes - Xbox 360</td>\n",
       "      <td>2006</td>\n",
       "      <td>501</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18906</th>\n",
       "      <td>XBOXGAME-3</td>\n",
       "      <td>DC Super-Villains - Xbox One</td>\n",
       "      <td>2018</td>\n",
       "      <td>501</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18907</th>\n",
       "      <td>XBOXGAME-9</td>\n",
       "      <td>Star Wars: The Video Game - Xbox</td>\n",
       "      <td>2005</td>\n",
       "      <td>501</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18908</th>\n",
       "      <td>XMASTREE-1</td>\n",
       "      <td>Christmas Tree</td>\n",
       "      <td>2019</td>\n",
       "      <td>410</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18909</th>\n",
       "      <td>XWING-1</td>\n",
       "      <td>Mini X-Wing Fighter</td>\n",
       "      <td>2019</td>\n",
       "      <td>158</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18910</th>\n",
       "      <td>XWING-2</td>\n",
       "      <td>X-Wing Trench Run</td>\n",
       "      <td>2019</td>\n",
       "      <td>158</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18911</th>\n",
       "      <td>YODACHRON-1</td>\n",
       "      <td>Yoda Chronicles Promotional Set</td>\n",
       "      <td>2013</td>\n",
       "      <td>158</td>\n",
       "      <td>413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18912</th>\n",
       "      <td>YTERRIER-1</td>\n",
       "      <td>Yorkshire Terrier</td>\n",
       "      <td>2018</td>\n",
       "      <td>598</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18913</th>\n",
       "      <td>ZX8000-1</td>\n",
       "      <td>ZX 8000 LEGO Sneaker</td>\n",
       "      <td>2020</td>\n",
       "      <td>501</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           set_num                              name  year  theme_id  \\\n",
       "18904   XBOXGAME-1   Batman the Videogame - Xbox 360  2008       501   \n",
       "18905   XBOXGAME-2        Bionicle Heroes - Xbox 360  2006       501   \n",
       "18906   XBOXGAME-3      DC Super-Villains - Xbox One  2018       501   \n",
       "18907   XBOXGAME-9  Star Wars: The Video Game - Xbox  2005       501   \n",
       "18908   XMASTREE-1                    Christmas Tree  2019       410   \n",
       "18909      XWING-1               Mini X-Wing Fighter  2019       158   \n",
       "18910      XWING-2                 X-Wing Trench Run  2019       158   \n",
       "18911  YODACHRON-1   Yoda Chronicles Promotional Set  2013       158   \n",
       "18912   YTERRIER-1                 Yorkshire Terrier  2018       598   \n",
       "18913     ZX8000-1              ZX 8000 LEGO Sneaker  2020       501   \n",
       "\n",
       "       num_parts  \n",
       "18904          0  \n",
       "18905          0  \n",
       "18906          0  \n",
       "18907          0  \n",
       "18908         26  \n",
       "18909         60  \n",
       "18910         52  \n",
       "18911        413  \n",
       "18912          0  \n",
       "18913          0  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sets.tail(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "117a51fc",
   "metadata": {},
   "source": [
    "#### Check Datatype of Each Column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "af47af0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "set_num      object\n",
       "name         object\n",
       "year          int64\n",
       "theme_id      int64\n",
       "num_parts     int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sets.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b087e21",
   "metadata": {},
   "source": [
    "#### Check NULL Values in Sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "ffe7a416",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "set_num      0\n",
       "name         0\n",
       "year         0\n",
       "theme_id     0\n",
       "num_parts    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sets.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "202463bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id             0\n",
       "name           0\n",
       "parent_id    138\n",
       "dtype: int64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "themes.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50274329",
   "metadata": {},
   "source": [
    "#### How many Rows and Columns are there in our dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e5f3672a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(18914, 5)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sets.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "6b4a53e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(sets.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "7e0e5dbd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "18914"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(sets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "b9cd9c5a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 18914 entries, 0 to 18913\n",
      "Data columns (total 5 columns):\n",
      " #   Column     Non-Null Count  Dtype \n",
      "---  ------     --------------  ----- \n",
      " 0   set_num    18914 non-null  object\n",
      " 1   name       18914 non-null  object\n",
      " 2   year       18914 non-null  int64 \n",
      " 3   theme_id   18914 non-null  int64 \n",
      " 4   num_parts  18914 non-null  int64 \n",
      "dtypes: int64(3), object(2)\n",
      "memory usage: 739.0+ KB\n"
     ]
    }
   ],
   "source": [
    "sets.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88d8debe",
   "metadata": {},
   "source": [
    "## MERGE DATA\n",
    "#### Joining the two datasets to answer questions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "84152152",
   "metadata": {},
   "outputs": [],
   "source": [
    "sets_themes = pd.merge(sets, themes, how = 'left', left_on = 'theme_id', right_on = 'id', suffixes = ('_sets', '_themes'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "9eac02ea",
   "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>set_num</th>\n",
       "      <th>name_sets</th>\n",
       "      <th>year</th>\n",
       "      <th>theme_id</th>\n",
       "      <th>num_parts</th>\n",
       "      <th>id</th>\n",
       "      <th>name_themes</th>\n",
       "      <th>parent_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>001-1</td>\n",
       "      <td>Gears</td>\n",
       "      <td>1965</td>\n",
       "      <td>1</td>\n",
       "      <td>43</td>\n",
       "      <td>1</td>\n",
       "      <td>Technic</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0011-2</td>\n",
       "      <td>Town Mini-Figures</td>\n",
       "      <td>1979</td>\n",
       "      <td>67</td>\n",
       "      <td>12</td>\n",
       "      <td>67</td>\n",
       "      <td>Classic Town</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0011-3</td>\n",
       "      <td>Castle 2 for 1 Bonus Offer</td>\n",
       "      <td>1987</td>\n",
       "      <td>199</td>\n",
       "      <td>0</td>\n",
       "      <td>199</td>\n",
       "      <td>Lion Knights</td>\n",
       "      <td>186.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0012-1</td>\n",
       "      <td>Space Mini-Figures</td>\n",
       "      <td>1979</td>\n",
       "      <td>143</td>\n",
       "      <td>12</td>\n",
       "      <td>143</td>\n",
       "      <td>Supplemental</td>\n",
       "      <td>126.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0013-1</td>\n",
       "      <td>Space Mini-Figures</td>\n",
       "      <td>1979</td>\n",
       "      <td>143</td>\n",
       "      <td>12</td>\n",
       "      <td>143</td>\n",
       "      <td>Supplemental</td>\n",
       "      <td>126.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  set_num                   name_sets  year  theme_id  num_parts   id  \\\n",
       "0   001-1                       Gears  1965         1         43    1   \n",
       "1  0011-2           Town Mini-Figures  1979        67         12   67   \n",
       "2  0011-3  Castle 2 for 1 Bonus Offer  1987       199          0  199   \n",
       "3  0012-1          Space Mini-Figures  1979       143         12  143   \n",
       "4  0013-1          Space Mini-Figures  1979       143         12  143   \n",
       "\n",
       "    name_themes  parent_id  \n",
       "0       Technic        NaN  \n",
       "1  Classic Town       50.0  \n",
       "2  Lion Knights      186.0  \n",
       "3  Supplemental      126.0  \n",
       "4  Supplemental      126.0  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sets_themes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "c3880b41",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 18914 entries, 0 to 18913\n",
      "Data columns (total 8 columns):\n",
      " #   Column       Non-Null Count  Dtype  \n",
      "---  ------       --------------  -----  \n",
      " 0   set_num      18914 non-null  object \n",
      " 1   name_sets    18914 non-null  object \n",
      " 2   year         18914 non-null  int64  \n",
      " 3   theme_id     18914 non-null  int64  \n",
      " 4   num_parts    18914 non-null  int64  \n",
      " 5   id           18914 non-null  int64  \n",
      " 6   name_themes  18914 non-null  object \n",
      " 7   parent_id    8672 non-null   float64\n",
      "dtypes: float64(1), int64(4), object(3)\n",
      "memory usage: 1.3+ MB\n"
     ]
    }
   ],
   "source": [
    "sets_themes.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "87d9abab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['set_num', 'name_sets', 'year', 'theme_id', 'num_parts', 'id',\n",
       "       'name_themes', 'parent_id'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sets_themes.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3cdbc54f",
   "metadata": {},
   "source": [
    "### Now Let's Answer some Questions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22a11bfc",
   "metadata": {},
   "source": [
    "#### 1.) What is the total number of parts per theme"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "d6c42dd7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name_themes</th>\n",
       "      <th>num_parts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>303</th>\n",
       "      <td>Technic</td>\n",
       "      <td>221198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>292</th>\n",
       "      <td>Star Wars</td>\n",
       "      <td>220914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>Creator Expert</td>\n",
       "      <td>128829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>Creator</td>\n",
       "      <td>102356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>Ninjago</td>\n",
       "      <td>96550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Aquazone</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>354</th>\n",
       "      <td>Zooters</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229</th>\n",
       "      <td>Powered Up</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>339</th>\n",
       "      <td>Value Packs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Adventurers</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>356 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        name_themes  num_parts\n",
       "303         Technic     221198\n",
       "292       Star Wars     220914\n",
       "66   Creator Expert     128829\n",
       "64          Creator     102356\n",
       "209         Ninjago      96550\n",
       "..              ...        ...\n",
       "16         Aquazone         26\n",
       "354         Zooters         25\n",
       "229      Powered Up         21\n",
       "339     Value Packs          1\n",
       "6       Adventurers          0\n",
       "\n",
       "[356 rows x 2 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Num_Parts_per_Theme = sets_themes.groupby('name_themes').sum().reset_index()\n",
    "Num_Parts_per_Theme = Num_Parts_per_Theme[['name_themes', 'num_parts']].sort_values('num_parts', ascending = False)\n",
    "Num_Parts_per_Theme"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9bbe2fbe",
   "metadata": {},
   "source": [
    "#### 2.) What is the total number of parts per year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "47817343",
   "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>year</th>\n",
       "      <th>num_parts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2021</td>\n",
       "      <td>264827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2020</td>\n",
       "      <td>211842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2019</td>\n",
       "      <td>191505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2017</td>\n",
       "      <td>178606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>2018</td>\n",
       "      <td>171717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1956</td>\n",
       "      <td>246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1954</td>\n",
       "      <td>117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1959</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1953</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1950</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>72 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    year  num_parts\n",
       "70  2021     264827\n",
       "69  2020     211842\n",
       "68  2019     191505\n",
       "66  2017     178606\n",
       "67  2018     171717\n",
       "..   ...        ...\n",
       "5   1956        246\n",
       "3   1954        117\n",
       "8   1959         65\n",
       "2   1953         50\n",
       "1   1950          6\n",
       "\n",
       "[72 rows x 2 columns]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Num_Parts_per_Year = sets_themes.groupby('year').sum().reset_index()\n",
    "Num_Parts_per_Year = Num_Parts_per_Year[['year', 'num_parts']].sort_values('num_parts', ascending = False)\n",
    "Num_Parts_per_Year"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25dc250c",
   "metadata": {},
   "source": [
    "#### 3.) How many sets where created in each Century in the dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e5c5f14",
   "metadata": {},
   "source": [
    "We have to add Century as a derived column to the sets_themes dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "e775f1c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1949, 1950, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961,\n",
       "       1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972,\n",
       "       1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983,\n",
       "       1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994,\n",
       "       1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005,\n",
       "       2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016,\n",
       "       2017, 2018, 2019, 2020, 2021, 2022], dtype=int64)"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_year = sets_themes['year'].unique()\n",
    "unique_year.sort()\n",
    "unique_year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "38e33e6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "sets_themes['year'] > 2000\n",
    "\n",
    "sets_themes['Century'] = np.where(sets_themes['year'] > 2000, '21st_Century', '20th_Century')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "04342237",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>set_num</th>\n",
       "      <th>name_sets</th>\n",
       "      <th>year</th>\n",
       "      <th>theme_id</th>\n",
       "      <th>num_parts</th>\n",
       "      <th>id</th>\n",
       "      <th>name_themes</th>\n",
       "      <th>parent_id</th>\n",
       "      <th>Century</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>001-1</td>\n",
       "      <td>Gears</td>\n",
       "      <td>1965</td>\n",
       "      <td>1</td>\n",
       "      <td>43</td>\n",
       "      <td>1</td>\n",
       "      <td>Technic</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20th_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0011-2</td>\n",
       "      <td>Town Mini-Figures</td>\n",
       "      <td>1979</td>\n",
       "      <td>67</td>\n",
       "      <td>12</td>\n",
       "      <td>67</td>\n",
       "      <td>Classic Town</td>\n",
       "      <td>50.0</td>\n",
       "      <td>20th_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0011-3</td>\n",
       "      <td>Castle 2 for 1 Bonus Offer</td>\n",
       "      <td>1987</td>\n",
       "      <td>199</td>\n",
       "      <td>0</td>\n",
       "      <td>199</td>\n",
       "      <td>Lion Knights</td>\n",
       "      <td>186.0</td>\n",
       "      <td>20th_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0012-1</td>\n",
       "      <td>Space Mini-Figures</td>\n",
       "      <td>1979</td>\n",
       "      <td>143</td>\n",
       "      <td>12</td>\n",
       "      <td>143</td>\n",
       "      <td>Supplemental</td>\n",
       "      <td>126.0</td>\n",
       "      <td>20th_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0013-1</td>\n",
       "      <td>Space Mini-Figures</td>\n",
       "      <td>1979</td>\n",
       "      <td>143</td>\n",
       "      <td>12</td>\n",
       "      <td>143</td>\n",
       "      <td>Supplemental</td>\n",
       "      <td>126.0</td>\n",
       "      <td>20th_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18909</th>\n",
       "      <td>XWING-1</td>\n",
       "      <td>Mini X-Wing Fighter</td>\n",
       "      <td>2019</td>\n",
       "      <td>158</td>\n",
       "      <td>60</td>\n",
       "      <td>158</td>\n",
       "      <td>Star Wars</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21st_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18910</th>\n",
       "      <td>XWING-2</td>\n",
       "      <td>X-Wing Trench Run</td>\n",
       "      <td>2019</td>\n",
       "      <td>158</td>\n",
       "      <td>52</td>\n",
       "      <td>158</td>\n",
       "      <td>Star Wars</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21st_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18911</th>\n",
       "      <td>YODACHRON-1</td>\n",
       "      <td>Yoda Chronicles Promotional Set</td>\n",
       "      <td>2013</td>\n",
       "      <td>158</td>\n",
       "      <td>413</td>\n",
       "      <td>158</td>\n",
       "      <td>Star Wars</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21st_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18912</th>\n",
       "      <td>YTERRIER-1</td>\n",
       "      <td>Yorkshire Terrier</td>\n",
       "      <td>2018</td>\n",
       "      <td>598</td>\n",
       "      <td>0</td>\n",
       "      <td>598</td>\n",
       "      <td>Promotional</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21st_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18913</th>\n",
       "      <td>ZX8000-1</td>\n",
       "      <td>ZX 8000 LEGO Sneaker</td>\n",
       "      <td>2020</td>\n",
       "      <td>501</td>\n",
       "      <td>0</td>\n",
       "      <td>501</td>\n",
       "      <td>Gear</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21st_Century</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18914 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           set_num                        name_sets  year  theme_id  \\\n",
       "0            001-1                            Gears  1965         1   \n",
       "1           0011-2                Town Mini-Figures  1979        67   \n",
       "2           0011-3       Castle 2 for 1 Bonus Offer  1987       199   \n",
       "3           0012-1               Space Mini-Figures  1979       143   \n",
       "4           0013-1               Space Mini-Figures  1979       143   \n",
       "...            ...                              ...   ...       ...   \n",
       "18909      XWING-1              Mini X-Wing Fighter  2019       158   \n",
       "18910      XWING-2                X-Wing Trench Run  2019       158   \n",
       "18911  YODACHRON-1  Yoda Chronicles Promotional Set  2013       158   \n",
       "18912   YTERRIER-1                Yorkshire Terrier  2018       598   \n",
       "18913     ZX8000-1             ZX 8000 LEGO Sneaker  2020       501   \n",
       "\n",
       "       num_parts   id   name_themes  parent_id       Century  \n",
       "0             43    1       Technic        NaN  20th_Century  \n",
       "1             12   67  Classic Town       50.0  20th_Century  \n",
       "2              0  199  Lion Knights      186.0  20th_Century  \n",
       "3             12  143  Supplemental      126.0  20th_Century  \n",
       "4             12  143  Supplemental      126.0  20th_Century  \n",
       "...          ...  ...           ...        ...           ...  \n",
       "18909         60  158     Star Wars        NaN  21st_Century  \n",
       "18910         52  158     Star Wars        NaN  21st_Century  \n",
       "18911        413  158     Star Wars        NaN  21st_Century  \n",
       "18912          0  598   Promotional        NaN  21st_Century  \n",
       "18913          0  501          Gear        NaN  21st_Century  \n",
       "\n",
       "[18914 rows x 9 columns]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sets_themes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "c89fc827",
   "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>Century</th>\n",
       "      <th>set_num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20th_Century</td>\n",
       "      <td>4858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>21st_Century</td>\n",
       "      <td>14056</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Century  set_num\n",
       "0  20th_Century     4858\n",
       "1  21st_Century    14056"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Num_set_per_Century = sets_themes.groupby('Century').count().reset_index()\n",
    "Num_set_per_Century [['Century', 'set_num']]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f55095f",
   "metadata": {},
   "source": [
    "#### 4.) What percentage of sets ever released in the 21st Century were Trains Themed "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "f007901b",
   "metadata": {},
   "outputs": [],
   "source": [
    "Century_21_Data = sets_themes[ sets_themes['Century'] == '21st_Century']\n",
    "Train = Century_21_Data[ Century_21_Data['name_themes'].str.contains('Train')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "c93d1ede",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14056"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Century_21_Data.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "11e59b08",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "63"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Train.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "946d5783",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.4482071713147411"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Train.shape[0] / Century_21_Data.shape[0] * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f452beb",
   "metadata": {},
   "source": [
    "#### 5.) What percentage of sets ever released in the 21st Century were Disney Themed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "2eaea3c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>set_num</th>\n",
       "      <th>name_sets</th>\n",
       "      <th>year</th>\n",
       "      <th>theme_id</th>\n",
       "      <th>num_parts</th>\n",
       "      <th>id</th>\n",
       "      <th>name_themes</th>\n",
       "      <th>parent_id</th>\n",
       "      <th>Century</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>414</th>\n",
       "      <td>10509-1</td>\n",
       "      <td>Dusty and Chug</td>\n",
       "      <td>2013</td>\n",
       "      <td>627</td>\n",
       "      <td>16</td>\n",
       "      <td>627</td>\n",
       "      <td>Disney Planes</td>\n",
       "      <td>504.0</td>\n",
       "      <td>21st_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>416</th>\n",
       "      <td>10510-1</td>\n",
       "      <td>Ripslinger's Air Race</td>\n",
       "      <td>2013</td>\n",
       "      <td>627</td>\n",
       "      <td>40</td>\n",
       "      <td>627</td>\n",
       "      <td>Disney Planes</td>\n",
       "      <td>504.0</td>\n",
       "      <td>21st_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>417</th>\n",
       "      <td>10511-1</td>\n",
       "      <td>Skipper's Flight School</td>\n",
       "      <td>2013</td>\n",
       "      <td>627</td>\n",
       "      <td>53</td>\n",
       "      <td>627</td>\n",
       "      <td>Disney Planes</td>\n",
       "      <td>504.0</td>\n",
       "      <td>21st_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>421</th>\n",
       "      <td>10515-1</td>\n",
       "      <td>Ariel's Undersea Castle</td>\n",
       "      <td>2013</td>\n",
       "      <td>640</td>\n",
       "      <td>39</td>\n",
       "      <td>640</td>\n",
       "      <td>Disney Princess</td>\n",
       "      <td>504.0</td>\n",
       "      <td>21st_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422</th>\n",
       "      <td>10516-1</td>\n",
       "      <td>Ariel's Magical Boat Ride</td>\n",
       "      <td>2012</td>\n",
       "      <td>640</td>\n",
       "      <td>30</td>\n",
       "      <td>640</td>\n",
       "      <td>Disney Princess</td>\n",
       "      <td>504.0</td>\n",
       "      <td>21st_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12343</th>\n",
       "      <td>71044-1</td>\n",
       "      <td>Disney Train and Station</td>\n",
       "      <td>2019</td>\n",
       "      <td>608</td>\n",
       "      <td>2927</td>\n",
       "      <td>608</td>\n",
       "      <td>Disney</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21st_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17918</th>\n",
       "      <td>CINDERELLASCASTLE-1</td>\n",
       "      <td>Cinderella’s Castle</td>\n",
       "      <td>2017</td>\n",
       "      <td>608</td>\n",
       "      <td>102</td>\n",
       "      <td>608</td>\n",
       "      <td>Disney</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21st_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18722</th>\n",
       "      <td>ROSE-1</td>\n",
       "      <td>The Beast's Enchanted Rose</td>\n",
       "      <td>2017</td>\n",
       "      <td>608</td>\n",
       "      <td>0</td>\n",
       "      <td>608</td>\n",
       "      <td>Disney</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21st_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18818</th>\n",
       "      <td>TRUCOGSWORTH-1</td>\n",
       "      <td>Cogsworth</td>\n",
       "      <td>2016</td>\n",
       "      <td>608</td>\n",
       "      <td>48</td>\n",
       "      <td>608</td>\n",
       "      <td>Disney</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21st_Century</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18828</th>\n",
       "      <td>TRULUMIERE-1</td>\n",
       "      <td>Lumiere</td>\n",
       "      <td>2016</td>\n",
       "      <td>608</td>\n",
       "      <td>24</td>\n",
       "      <td>608</td>\n",
       "      <td>Disney</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21st_Century</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>176 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   set_num                   name_sets  year  theme_id  \\\n",
       "414                10509-1              Dusty and Chug  2013       627   \n",
       "416                10510-1       Ripslinger's Air Race  2013       627   \n",
       "417                10511-1     Skipper's Flight School  2013       627   \n",
       "421                10515-1     Ariel's Undersea Castle  2013       640   \n",
       "422                10516-1   Ariel's Magical Boat Ride  2012       640   \n",
       "...                    ...                         ...   ...       ...   \n",
       "12343              71044-1    Disney Train and Station  2019       608   \n",
       "17918  CINDERELLASCASTLE-1         Cinderella’s Castle  2017       608   \n",
       "18722               ROSE-1  The Beast's Enchanted Rose  2017       608   \n",
       "18818       TRUCOGSWORTH-1                   Cogsworth  2016       608   \n",
       "18828         TRULUMIERE-1                     Lumiere  2016       608   \n",
       "\n",
       "       num_parts   id      name_themes  parent_id       Century  \n",
       "414           16  627    Disney Planes      504.0  21st_Century  \n",
       "416           40  627    Disney Planes      504.0  21st_Century  \n",
       "417           53  627    Disney Planes      504.0  21st_Century  \n",
       "421           39  640  Disney Princess      504.0  21st_Century  \n",
       "422           30  640  Disney Princess      504.0  21st_Century  \n",
       "...          ...  ...              ...        ...           ...  \n",
       "12343       2927  608           Disney        NaN  21st_Century  \n",
       "17918        102  608           Disney        NaN  21st_Century  \n",
       "18722          0  608           Disney        NaN  21st_Century  \n",
       "18818         48  608           Disney        NaN  21st_Century  \n",
       "18828         24  608           Disney        NaN  21st_Century  \n",
       "\n",
       "[176 rows x 9 columns]"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Disney = Century_21_Data[ Century_21_Data['name_themes'].str.contains('Disney')]\n",
    "Disney"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "4dedccad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "176"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Disney.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "d0e0bab4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.2521343198634036"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Disney.shape[0] / Century_21_Data.shape[0] * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4de3747",
   "metadata": {},
   "source": [
    "#### 6.) What is the popular theme by year in terms of sets released in the 21st Century"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "4046508a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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>year</th>\n",
       "      <th>name_themes</th>\n",
       "      <th>set_num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1370</th>\n",
       "      <td>2022</td>\n",
       "      <td>City</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1327</th>\n",
       "      <td>2021</td>\n",
       "      <td>Gear</td>\n",
       "      <td>225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1252</th>\n",
       "      <td>2020</td>\n",
       "      <td>Gear</td>\n",
       "      <td>150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1181</th>\n",
       "      <td>2019</td>\n",
       "      <td>Gear</td>\n",
       "      <td>171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1104</th>\n",
       "      <td>2018</td>\n",
       "      <td>Gear</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1035</th>\n",
       "      <td>2017</td>\n",
       "      <td>Gear</td>\n",
       "      <td>141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>953</th>\n",
       "      <td>2016</td>\n",
       "      <td>Gear</td>\n",
       "      <td>97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>866</th>\n",
       "      <td>2015</td>\n",
       "      <td>Gear</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>786</th>\n",
       "      <td>2014</td>\n",
       "      <td>Gear</td>\n",
       "      <td>97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>707</th>\n",
       "      <td>2013</td>\n",
       "      <td>Gear</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>632</th>\n",
       "      <td>2012</td>\n",
       "      <td>Gear</td>\n",
       "      <td>105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>566</th>\n",
       "      <td>2011</td>\n",
       "      <td>Gear</td>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>2010</td>\n",
       "      <td>Gear</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>2009</td>\n",
       "      <td>Gear</td>\n",
       "      <td>104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400</th>\n",
       "      <td>2008</td>\n",
       "      <td>Gear</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>343</th>\n",
       "      <td>2007</td>\n",
       "      <td>Gear</td>\n",
       "      <td>109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>289</th>\n",
       "      <td>2006</td>\n",
       "      <td>Gear</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>2005</td>\n",
       "      <td>Bionicle</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>2004</td>\n",
       "      <td>Bionicle</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2003</td>\n",
       "      <td>Bionicle</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>2002</td>\n",
       "      <td>Technic</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2001</td>\n",
       "      <td>Bionicle</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      year name_themes  set_num\n",
       "1370  2022        City       25\n",
       "1327  2021        Gear      225\n",
       "1252  2020        Gear      150\n",
       "1181  2019        Gear      171\n",
       "1104  2018        Gear      115\n",
       "1035  2017        Gear      141\n",
       "953   2016        Gear       97\n",
       "866   2015        Gear       87\n",
       "786   2014        Gear       97\n",
       "707   2013        Gear       94\n",
       "632   2012        Gear      105\n",
       "566   2011        Gear      102\n",
       "509   2010        Gear       59\n",
       "454   2009        Gear      104\n",
       "400   2008        Gear       84\n",
       "343   2007        Gear      109\n",
       "289   2006        Gear       75\n",
       "214   2005    Bionicle       36\n",
       "165   2004    Bionicle       48\n",
       "109   2003    Bionicle       63\n",
       "96    2002     Technic       65\n",
       "6     2001    Bionicle       47"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Popular_Theme_per_Year = Century_21_Data.groupby(['year', 'name_themes']).count().reset_index()\n",
    "Popular_Theme_per_Year = Popular_Theme_per_Year[['year', 'name_themes', 'set_num']].sort_values('set_num', ascending = False)\n",
    "Popular_Theme_per_Year.drop_duplicates('year').sort_values('year', ascending = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e73daea",
   "metadata": {},
   "source": [
    "#### 7.) What is the most produced color of lego ever in terms of quantity of parts?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "014d7b45",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>rgb</th>\n",
       "      <th>is_trans</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-1</td>\n",
       "      <td>[Unknown]</td>\n",
       "      <td>0033B2</td>\n",
       "      <td>f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>Black</td>\n",
       "      <td>05131D</td>\n",
       "      <td>f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>Blue</td>\n",
       "      <td>0055BF</td>\n",
       "      <td>f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>Green</td>\n",
       "      <td>237841</td>\n",
       "      <td>f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>Dark Turquoise</td>\n",
       "      <td>008F9B</td>\n",
       "      <td>f</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>210</th>\n",
       "      <td>1084</td>\n",
       "      <td>Two-tone Gold</td>\n",
       "      <td>AB673A</td>\n",
       "      <td>f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>1085</td>\n",
       "      <td>Two-tone Silver</td>\n",
       "      <td>737271</td>\n",
       "      <td>f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>1086</td>\n",
       "      <td>Pearl Lime</td>\n",
       "      <td>6A7944</td>\n",
       "      <td>f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>1087</td>\n",
       "      <td>Duplo Pink</td>\n",
       "      <td>FF879C</td>\n",
       "      <td>f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>9999</td>\n",
       "      <td>[No Color/Any Color]</td>\n",
       "      <td>05131D</td>\n",
       "      <td>f</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>215 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       id                  name     rgb is_trans\n",
       "0      -1             [Unknown]  0033B2        f\n",
       "1       0                 Black  05131D        f\n",
       "2       1                  Blue  0055BF        f\n",
       "3       2                 Green  237841        f\n",
       "4       3        Dark Turquoise  008F9B        f\n",
       "..    ...                   ...     ...      ...\n",
       "210  1084         Two-tone Gold  AB673A        f\n",
       "211  1085       Two-tone Silver  737271        f\n",
       "212  1086            Pearl Lime  6A7944        f\n",
       "213  1087            Duplo Pink  FF879C        f\n",
       "214  9999  [No Color/Any Color]  05131D        f\n",
       "\n",
       "[215 rows x 4 columns]"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "colors = pd.read_csv('data_source/colors.csv')\n",
    "colors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "530ad2fe",
   "metadata": {},
   "outputs": [
    {
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       "      <td>1</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>1005441 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         inventory_id        part_num  color_id  quantity is_spare\n",
       "0                   1        48379c01        72         1        f\n",
       "1                   1           48395         7         1        f\n",
       "2                   1  stickerupn0077      9999         1        f\n",
       "3                   1         upn0342         0         1        f\n",
       "4                   1         upn0350        25         1        f\n",
       "...               ...             ...       ...       ...      ...\n",
       "1005436        128964           19888         0         1        f\n",
       "1005437        128964     3626cpr1670        78         1        f\n",
       "1005438        128964           59276         0         1        f\n",
       "1005439        128964    970c00pr2273         0         1        f\n",
       "1005440        128964   973f017pr6023         0         1        f\n",
       "\n",
       "[1005441 rows x 5 columns]"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inventory_parts = pd.read_csv('data_source/inventory_parts.csv')\n",
    "inventory_parts"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "410d43d3",
   "metadata": {},
   "source": [
    "#### Note - Join two datasets to answer question"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "1dce0367",
   "metadata": {},
   "outputs": [
    {
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       "      <td>72</td>\n",
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       "      <td>6C6E68</td>\n",
       "      <td>f</td>\n",
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       "      <th>1</th>\n",
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      ],
      "text/plain": [
       "         inventory_id        part_num  color_id  quantity is_spare    id  \\\n",
       "0                   1        48379c01        72         1        f    72   \n",
       "1                   1           48395         7         1        f     7   \n",
       "2                   1  stickerupn0077      9999         1        f  9999   \n",
       "3                   1         upn0342         0         1        f     0   \n",
       "4                   1         upn0350        25         1        f    25   \n",
       "...               ...             ...       ...       ...      ...   ...   \n",
       "1005436        128964           19888         0         1        f     0   \n",
       "1005437        128964     3626cpr1670        78         1        f    78   \n",
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       "1005439        128964    970c00pr2273         0         1        f     0   \n",
       "1005440        128964   973f017pr6023         0         1        f     0   \n",
       "\n",
       "                         name     rgb is_trans  \n",
       "0            Dark Bluish Gray  6C6E68        f  \n",
       "1                  Light Gray  9BA19D        f  \n",
       "2        [No Color/Any Color]  05131D        f  \n",
       "3                       Black  05131D        f  \n",
       "4                      Orange  FE8A18        f  \n",
       "...                       ...     ...      ...  \n",
       "1005436                 Black  05131D        f  \n",
       "1005437          Light Nougat  F6D7B3        f  \n",
       "1005438                 Black  05131D        f  \n",
       "1005439                 Black  05131D        f  \n",
       "1005440                 Black  05131D        f  \n",
       "\n",
       "[1005441 rows x 9 columns]"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "color_inventory = pd.merge(inventory_parts, colors, how = 'left', left_on = 'color_id', right_on = 'id')\n",
    "color_inventory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "5af27923",
   "metadata": {},
   "outputs": [],
   "source": [
    "color_inventory.rename(columns={'name': 'color_name'}, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "bef6acfc",
   "metadata": {},
   "outputs": [
    {
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       "      <td>05131D</td>\n",
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       "    <tr>\n",
       "      <th>1005437</th>\n",
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       "      <td>3626cpr1670</td>\n",
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       "      <td>Light Nougat</td>\n",
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       "</div>"
      ],
      "text/plain": [
       "         inventory_id        part_num  color_id  quantity is_spare    id  \\\n",
       "0                   1        48379c01        72         1        f    72   \n",
       "1                   1           48395         7         1        f     7   \n",
       "2                   1  stickerupn0077      9999         1        f  9999   \n",
       "3                   1         upn0342         0         1        f     0   \n",
       "4                   1         upn0350        25         1        f    25   \n",
       "...               ...             ...       ...       ...      ...   ...   \n",
       "1005436        128964           19888         0         1        f     0   \n",
       "1005437        128964     3626cpr1670        78         1        f    78   \n",
       "1005438        128964           59276         0         1        f     0   \n",
       "1005439        128964    970c00pr2273         0         1        f     0   \n",
       "1005440        128964   973f017pr6023         0         1        f     0   \n",
       "\n",
       "                   color_name     rgb is_trans  \n",
       "0            Dark Bluish Gray  6C6E68        f  \n",
       "1                  Light Gray  9BA19D        f  \n",
       "2        [No Color/Any Color]  05131D        f  \n",
       "3                       Black  05131D        f  \n",
       "4                      Orange  FE8A18        f  \n",
       "...                       ...     ...      ...  \n",
       "1005436                 Black  05131D        f  \n",
       "1005437          Light Nougat  F6D7B3        f  \n",
       "1005438                 Black  05131D        f  \n",
       "1005439                 Black  05131D        f  \n",
       "1005440                 Black  05131D        f  \n",
       "\n",
       "[1005441 rows x 9 columns]"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "color_inventory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "46bfa08f",
   "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>color_name</th>\n",
       "      <th>quantity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Black</td>\n",
       "      <td>636633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Light Bluish Gray</td>\n",
       "      <td>378738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>White</td>\n",
       "      <td>375293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Dark Bluish Gray</td>\n",
       "      <td>266282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>Red</td>\n",
       "      <td>253350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Blue</td>\n",
       "      <td>176714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>Yellow</td>\n",
       "      <td>174936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>Tan</td>\n",
       "      <td>123258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>Reddish Brown</td>\n",
       "      <td>104626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Light Gray</td>\n",
       "      <td>101258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>Green</td>\n",
       "      <td>64306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>Trans-Clear</td>\n",
       "      <td>36876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>Orange</td>\n",
       "      <td>36819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Dark Tan</td>\n",
       "      <td>36180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Dark Red</td>\n",
       "      <td>33510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Dark Blue</td>\n",
       "      <td>31736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>Lime</td>\n",
       "      <td>30340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>Pearl Gold</td>\n",
       "      <td>29857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>Trans-Light Blue</td>\n",
       "      <td>24090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Dark Gray</td>\n",
       "      <td>23772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>Trans-Red</td>\n",
       "      <td>20575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Flat Silver</td>\n",
       "      <td>19783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>Medium Nougat</td>\n",
       "      <td>16162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Bright Light Orange</td>\n",
       "      <td>16135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>Medium Azure</td>\n",
       "      <td>15453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>Sand Green</td>\n",
       "      <td>15158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Bright Green</td>\n",
       "      <td>13763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Dark Green</td>\n",
       "      <td>13750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Dark Brown</td>\n",
       "      <td>13618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>Trans-Orange</td>\n",
       "      <td>12840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>Medium Blue</td>\n",
       "      <td>12676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>Trans-Yellow</td>\n",
       "      <td>12628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Dark Orange</td>\n",
       "      <td>11736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Dark Purple</td>\n",
       "      <td>11011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Bright Pink</td>\n",
       "      <td>10497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>Trans-Dark Blue</td>\n",
       "      <td>10303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Dark Turquoise</td>\n",
       "      <td>9972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Brown</td>\n",
       "      <td>9481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Dark Pink</td>\n",
       "      <td>8970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>Trans-Black</td>\n",
       "      <td>8710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Dark Azure</td>\n",
       "      <td>8395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>Magenta</td>\n",
       "      <td>8373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>[No Color/Any Color]</td>\n",
       "      <td>7564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>Trans-Neon Green</td>\n",
       "      <td>7435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>Trans-Neon Orange</td>\n",
       "      <td>6384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>Pearl Dark Gray</td>\n",
       "      <td>5776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>Olive Green</td>\n",
       "      <td>5631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>Sand Blue</td>\n",
       "      <td>5254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>Trans-Green</td>\n",
       "      <td>5201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>Medium Lavender</td>\n",
       "      <td>5156</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               color_name  quantity\n",
       "1                   Black    636633\n",
       "59      Light Bluish Gray    378738\n",
       "197                 White    375293\n",
       "24       Dark Bluish Gray    266282\n",
       "136                   Red    253350\n",
       "2                    Blue    176714\n",
       "198                Yellow    174936\n",
       "154                   Tan    123258\n",
       "137         Reddish Brown    104626\n",
       "60             Light Gray    101258\n",
       "55                  Green     64306\n",
       "159           Trans-Clear     36876\n",
       "120                Orange     36819\n",
       "33               Dark Tan     36180\n",
       "32               Dark Red     33510\n",
       "22              Dark Blue     31736\n",
       "72                   Lime     30340\n",
       "126            Pearl Gold     29857\n",
       "168      Trans-Light Blue     24090\n",
       "26              Dark Gray     23772\n",
       "182             Trans-Red     20575\n",
       "45            Flat Silver     19783\n",
       "82          Medium Nougat     16162\n",
       "6     Bright Light Orange     16135\n",
       "75           Medium Azure     15453\n",
       "146            Sand Green     15158\n",
       "4            Bright Green     13763\n",
       "27             Dark Green     13750\n",
       "25             Dark Brown     13618\n",
       "178          Trans-Orange     12840\n",
       "76            Medium Blue     12676\n",
       "184          Trans-Yellow     12628\n",
       "29            Dark Orange     11736\n",
       "31            Dark Purple     11011\n",
       "8             Bright Pink     10497\n",
       "161       Trans-Dark Blue     10303\n",
       "34         Dark Turquoise      9972\n",
       "9                   Brown      9481\n",
       "30              Dark Pink      8970\n",
       "155           Trans-Black      8710\n",
       "21             Dark Azure      8395\n",
       "74                Magenta      8373\n",
       "200  [No Color/Any Color]      7564\n",
       "175      Trans-Neon Green      7435\n",
       "176     Trans-Neon Orange      6384\n",
       "125       Pearl Dark Gray      5776\n",
       "119           Olive Green      5631\n",
       "145             Sand Blue      5254\n",
       "166           Trans-Green      5201\n",
       "80        Medium Lavender      5156"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Popular_Color = color_inventory.groupby('color_name').sum().reset_index()\n",
    "Popular_Color = Popular_Color[['color_name', 'quantity']].sort_values('quantity', ascending = False)\n",
    "\n",
    "Popular_Color.head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f2b6de52",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5f216a39",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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