Pandas.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pandas basically serves as a data analysis and transformation tool. It provides facilities that allow for easier data representation and, as part of the larger python ecosystem, integrates easily with other Python programs."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data is essentially kept as an excel sheet\n",
    "Dictionaries are quite good at modeling pandas structure, as values are grouped\n",
    "under a certain key."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "example_dict = {'name' : [\"annie\", \"bob\", \"charlie\", \"damon\", \"erick\",\"fry\", \"goldman\"],\n",
    "     'age' : [20,27, 35, 55, 18, 21, 35],\n",
    "     'designation': [\"VP\", \"CEO\", \"CFO\", \"VP\", \"VP\", \"CEO\", \"MD\"]\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Columns in the dataframe may not be in the same order, due to the nature of python dicts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "pandas_dataframe =pd.DataFrame(example_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>age</th>\n",
       "      <th>designation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>annie</td>\n",
       "      <td>20</td>\n",
       "      <td>VP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>bob</td>\n",
       "      <td>27</td>\n",
       "      <td>CEO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>charlie</td>\n",
       "      <td>35</td>\n",
       "      <td>CFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>damon</td>\n",
       "      <td>55</td>\n",
       "      <td>VP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>erick</td>\n",
       "      <td>18</td>\n",
       "      <td>VP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>fry</td>\n",
       "      <td>21</td>\n",
       "      <td>CEO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>goldman</td>\n",
       "      <td>35</td>\n",
       "      <td>MD</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      name  age designation\n",
       "0    annie   20          VP\n",
       "1      bob   27         CEO\n",
       "2  charlie   35         CFO\n",
       "3    damon   55          VP\n",
       "4    erick   18          VP\n",
       "5      fry   21         CEO\n",
       "6  goldman   35          MD"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pandas_dataframe"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above call lets Pandas create an index from 0 to 6. You can however, pass your own custom index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd_df_cstm_index = pd.DataFrame(example_dict, index=[1,2,3,4,5,6,7])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>age</th>\n",
       "      <th>designation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>annie</td>\n",
       "      <td>20</td>\n",
       "      <td>VP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>bob</td>\n",
       "      <td>27</td>\n",
       "      <td>CEO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>charlie</td>\n",
       "      <td>35</td>\n",
       "      <td>CFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>damon</td>\n",
       "      <td>55</td>\n",
       "      <td>VP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>erick</td>\n",
       "      <td>18</td>\n",
       "      <td>VP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>fry</td>\n",
       "      <td>21</td>\n",
       "      <td>CEO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>goldman</td>\n",
       "      <td>35</td>\n",
       "      <td>MD</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      name  age designation\n",
       "1    annie   20          VP\n",
       "2      bob   27         CEO\n",
       "3  charlie   35         CFO\n",
       "4    damon   55          VP\n",
       "5    erick   18          VP\n",
       "6      fry   21         CEO\n",
       "7  goldman   35          MD"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_df_cstm_index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Indexes however need not be numeric. Strings serve this purpose just as well"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd_df_cstm_index = pd.DataFrame(example_dict, index=[\"First\", \"Second\", \"Third\", \"Fourth\", \"Fifth\", \"Sixth\", \"Seventh\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>age</th>\n",
       "      <th>designation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>First</th>\n",
       "      <td>annie</td>\n",
       "      <td>20</td>\n",
       "      <td>VP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Second</th>\n",
       "      <td>bob</td>\n",
       "      <td>27</td>\n",
       "      <td>CEO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Third</th>\n",
       "      <td>charlie</td>\n",
       "      <td>35</td>\n",
       "      <td>CFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fourth</th>\n",
       "      <td>damon</td>\n",
       "      <td>55</td>\n",
       "      <td>VP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fifth</th>\n",
       "      <td>erick</td>\n",
       "      <td>18</td>\n",
       "      <td>VP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sixth</th>\n",
       "      <td>fry</td>\n",
       "      <td>21</td>\n",
       "      <td>CEO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Seventh</th>\n",
       "      <td>goldman</td>\n",
       "      <td>35</td>\n",
       "      <td>MD</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            name  age designation\n",
       "First      annie   20          VP\n",
       "Second       bob   27         CEO\n",
       "Third    charlie   35         CFO\n",
       "Fourth     damon   55          VP\n",
       "Fifth      erick   18          VP\n",
       "Sixth        fry   21         CEO\n",
       "Seventh  goldman   35          MD"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_df_cstm_index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Numpy arrays may also be used as indexes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "np_arr = np.array([10,20,30,40,50,60,70])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Series objects are restricted to one column, meaning they can serve as references for very frequently\n",
    "used data rows, such as transaction types, tickers and the like\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10\n"
     ]
    }
   ],
   "source": [
    "pd_series = pd.Series(np_arr)\n",
    "print (pd_series[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reading csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pandas can read data from many types of files, but one of the most common is CSV, so we'll be using that.\n",
    "The example file comes from an art gallery and provides a great variety of data, so that we can demonstrate Pandas\n",
    "various features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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",
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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>accession_number</th>\n",
       "      <th>artist</th>\n",
       "      <th>artistRole</th>\n",
       "      <th>artistId</th>\n",
       "      <th>title</th>\n",
       "      <th>dateText</th>\n",
       "      <th>medium</th>\n",
       "      <th>creditLine</th>\n",
       "      <th>year</th>\n",
       "      <th>acquisitionYear</th>\n",
       "      <th>dimensions</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>depth</th>\n",
       "      <th>units</th>\n",
       "      <th>inscription</th>\n",
       "      <th>thumbnailCopyright</th>\n",
       "      <th>thumbnailUrl</th>\n",
       "      <th>url</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1035</td>\n",
       "      <td>A00001</td>\n",
       "      <td>Blake, Robert</td>\n",
       "      <td>artist</td>\n",
       "      <td>38</td>\n",
       "      <td>A Figure Bowing before a Seated Old Man with h...</td>\n",
       "      <td>date not known</td>\n",
       "      <td>Watercolour, ink, chalk and graphite on paper....</td>\n",
       "      <td>Presented by Mrs John Richmond 1922</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1922</td>\n",
       "      <td>support: 394 x 419 mm</td>\n",
       "      <td>394</td>\n",
       "      <td>419</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.tate.org.uk/art/images/work/A/A00/A...</td>\n",
       "      <td>http://www.tate.org.uk/art/artworks/blake-a-fi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1036</td>\n",
       "      <td>A00002</td>\n",
       "      <td>Blake, Robert</td>\n",
       "      <td>artist</td>\n",
       "      <td>38</td>\n",
       "      <td>Two Drawings of Frightened Figures, Probably f...</td>\n",
       "      <td>date not known</td>\n",
       "      <td>Graphite on paper</td>\n",
       "      <td>Presented by Mrs John Richmond 1922</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1922</td>\n",
       "      <td>support: 311 x 213 mm</td>\n",
       "      <td>311</td>\n",
       "      <td>213</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.tate.org.uk/art/images/work/A/A00/A...</td>\n",
       "      <td>http://www.tate.org.uk/art/artworks/blake-two-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1037</td>\n",
       "      <td>A00003</td>\n",
       "      <td>Blake, Robert</td>\n",
       "      <td>artist</td>\n",
       "      <td>38</td>\n",
       "      <td>The Preaching of Warning. Verso: An Old Man En...</td>\n",
       "      <td>?c.1785</td>\n",
       "      <td>Graphite on paper. Verso: graphite on paper</td>\n",
       "      <td>Presented by Mrs John Richmond 1922</td>\n",
       "      <td>1785.0</td>\n",
       "      <td>1922</td>\n",
       "      <td>support: 343 x 467 mm</td>\n",
       "      <td>343</td>\n",
       "      <td>467</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.tate.org.uk/art/images/work/A/A00/A...</td>\n",
       "      <td>http://www.tate.org.uk/art/artworks/blake-the-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1038</td>\n",
       "      <td>A00004</td>\n",
       "      <td>Blake, Robert</td>\n",
       "      <td>artist</td>\n",
       "      <td>38</td>\n",
       "      <td>Six Drawings of Figures with Outstretched Arms</td>\n",
       "      <td>date not known</td>\n",
       "      <td>Graphite on paper</td>\n",
       "      <td>Presented by Mrs John Richmond 1922</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1922</td>\n",
       "      <td>support: 318 x 394 mm</td>\n",
       "      <td>318</td>\n",
       "      <td>394</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.tate.org.uk/art/images/work/A/A00/A...</td>\n",
       "      <td>http://www.tate.org.uk/art/artworks/blake-six-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1039</td>\n",
       "      <td>A00005</td>\n",
       "      <td>Blake, William</td>\n",
       "      <td>artist</td>\n",
       "      <td>39</td>\n",
       "      <td>The Circle of the Lustful: Francesca da Rimini...</td>\n",
       "      <td>1826–7, reprinted 1892</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>Purchased with the assistance of a special gra...</td>\n",
       "      <td>1826.0</td>\n",
       "      <td>1919</td>\n",
       "      <td>image: 243 x 335 mm</td>\n",
       "      <td>243</td>\n",
       "      <td>335</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.tate.org.uk/art/images/work/A/A00/A...</td>\n",
       "      <td>http://www.tate.org.uk/art/artworks/blake-the-...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     id accession_number          artist artistRole  artistId  \\\n",
       "0  1035           A00001   Blake, Robert     artist        38   \n",
       "1  1036           A00002   Blake, Robert     artist        38   \n",
       "2  1037           A00003   Blake, Robert     artist        38   \n",
       "3  1038           A00004   Blake, Robert     artist        38   \n",
       "4  1039           A00005  Blake, William     artist        39   \n",
       "\n",
       "                                               title                dateText  \\\n",
       "0  A Figure Bowing before a Seated Old Man with h...          date not known   \n",
       "1  Two Drawings of Frightened Figures, Probably f...          date not known   \n",
       "2  The Preaching of Warning. Verso: An Old Man En...                 ?c.1785   \n",
       "3     Six Drawings of Figures with Outstretched Arms          date not known   \n",
       "4  The Circle of the Lustful: Francesca da Rimini...  1826–7, reprinted 1892   \n",
       "\n",
       "                                              medium  \\\n",
       "0  Watercolour, ink, chalk and graphite on paper....   \n",
       "1                                  Graphite on paper   \n",
       "2        Graphite on paper. Verso: graphite on paper   \n",
       "3                                  Graphite on paper   \n",
       "4                            Line engraving on paper   \n",
       "\n",
       "                                          creditLine    year  acquisitionYear  \\\n",
       "0                Presented by Mrs John Richmond 1922     NaN             1922   \n",
       "1                Presented by Mrs John Richmond 1922     NaN             1922   \n",
       "2                Presented by Mrs John Richmond 1922  1785.0             1922   \n",
       "3                Presented by Mrs John Richmond 1922     NaN             1922   \n",
       "4  Purchased with the assistance of a special gra...  1826.0             1919   \n",
       "\n",
       "              dimensions  width  height  depth units  inscription  \\\n",
       "0  support: 394 x 419 mm    394     419    NaN    mm          NaN   \n",
       "1  support: 311 x 213 mm    311     213    NaN    mm          NaN   \n",
       "2  support: 343 x 467 mm    343     467    NaN    mm          NaN   \n",
       "3  support: 318 x 394 mm    318     394    NaN    mm          NaN   \n",
       "4    image: 243 x 335 mm    243     335    NaN    mm          NaN   \n",
       "\n",
       "   thumbnailCopyright                                       thumbnailUrl  \\\n",
       "0                 NaN  http://www.tate.org.uk/art/images/work/A/A00/A...   \n",
       "1                 NaN  http://www.tate.org.uk/art/images/work/A/A00/A...   \n",
       "2                 NaN  http://www.tate.org.uk/art/images/work/A/A00/A...   \n",
       "3                 NaN  http://www.tate.org.uk/art/images/work/A/A00/A...   \n",
       "4                 NaN  http://www.tate.org.uk/art/images/work/A/A00/A...   \n",
       "\n",
       "                                                 url  \n",
       "0  http://www.tate.org.uk/art/artworks/blake-a-fi...  \n",
       "1  http://www.tate.org.uk/art/artworks/blake-two-...  \n",
       "2  http://www.tate.org.uk/art/artworks/blake-the-...  \n",
       "3  http://www.tate.org.uk/art/artworks/blake-six-...  \n",
       "4  http://www.tate.org.uk/art/artworks/blake-the-...  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv_path = 'https://raw.githubusercontent.com/tategallery/collection/master/artwork_data.csv'\n",
    "csv_df = pd.read_csv(csv_path,nrows=5)\n",
    "csv_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see, Pandas generated its own id numbers. However, the data collected brings its own ids, so we should take advantage of them.\n",
    "\n",
    "### index_col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\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>accession_number</th>\n",
       "      <th>artist</th>\n",
       "      <th>artistRole</th>\n",
       "      <th>artistId</th>\n",
       "      <th>title</th>\n",
       "      <th>dateText</th>\n",
       "      <th>medium</th>\n",
       "      <th>creditLine</th>\n",
       "      <th>year</th>\n",
       "      <th>acquisitionYear</th>\n",
       "      <th>dimensions</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>depth</th>\n",
       "      <th>units</th>\n",
       "      <th>inscription</th>\n",
       "      <th>thumbnailCopyright</th>\n",
       "      <th>thumbnailUrl</th>\n",
       "      <th>url</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1035</th>\n",
       "      <td>A00001</td>\n",
       "      <td>Blake, Robert</td>\n",
       "      <td>artist</td>\n",
       "      <td>38</td>\n",
       "      <td>A Figure Bowing before a Seated Old Man with h...</td>\n",
       "      <td>date not known</td>\n",
       "      <td>Watercolour, ink, chalk and graphite on paper....</td>\n",
       "      <td>Presented by Mrs John Richmond 1922</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1922</td>\n",
       "      <td>support: 394 x 419 mm</td>\n",
       "      <td>394</td>\n",
       "      <td>419</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.tate.org.uk/art/images/work/A/A00/A...</td>\n",
       "      <td>http://www.tate.org.uk/art/artworks/blake-a-fi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1036</th>\n",
       "      <td>A00002</td>\n",
       "      <td>Blake, Robert</td>\n",
       "      <td>artist</td>\n",
       "      <td>38</td>\n",
       "      <td>Two Drawings of Frightened Figures, Probably f...</td>\n",
       "      <td>date not known</td>\n",
       "      <td>Graphite on paper</td>\n",
       "      <td>Presented by Mrs John Richmond 1922</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1922</td>\n",
       "      <td>support: 311 x 213 mm</td>\n",
       "      <td>311</td>\n",
       "      <td>213</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.tate.org.uk/art/images/work/A/A00/A...</td>\n",
       "      <td>http://www.tate.org.uk/art/artworks/blake-two-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1037</th>\n",
       "      <td>A00003</td>\n",
       "      <td>Blake, Robert</td>\n",
       "      <td>artist</td>\n",
       "      <td>38</td>\n",
       "      <td>The Preaching of Warning. Verso: An Old Man En...</td>\n",
       "      <td>?c.1785</td>\n",
       "      <td>Graphite on paper. Verso: graphite on paper</td>\n",
       "      <td>Presented by Mrs John Richmond 1922</td>\n",
       "      <td>1785.0</td>\n",
       "      <td>1922</td>\n",
       "      <td>support: 343 x 467 mm</td>\n",
       "      <td>343</td>\n",
       "      <td>467</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.tate.org.uk/art/images/work/A/A00/A...</td>\n",
       "      <td>http://www.tate.org.uk/art/artworks/blake-the-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1038</th>\n",
       "      <td>A00004</td>\n",
       "      <td>Blake, Robert</td>\n",
       "      <td>artist</td>\n",
       "      <td>38</td>\n",
       "      <td>Six Drawings of Figures with Outstretched Arms</td>\n",
       "      <td>date not known</td>\n",
       "      <td>Graphite on paper</td>\n",
       "      <td>Presented by Mrs John Richmond 1922</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1922</td>\n",
       "      <td>support: 318 x 394 mm</td>\n",
       "      <td>318</td>\n",
       "      <td>394</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.tate.org.uk/art/images/work/A/A00/A...</td>\n",
       "      <td>http://www.tate.org.uk/art/artworks/blake-six-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1039</th>\n",
       "      <td>A00005</td>\n",
       "      <td>Blake, William</td>\n",
       "      <td>artist</td>\n",
       "      <td>39</td>\n",
       "      <td>The Circle of the Lustful: Francesca da Rimini...</td>\n",
       "      <td>1826–7, reprinted 1892</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>Purchased with the assistance of a special gra...</td>\n",
       "      <td>1826.0</td>\n",
       "      <td>1919</td>\n",
       "      <td>image: 243 x 335 mm</td>\n",
       "      <td>243</td>\n",
       "      <td>335</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.tate.org.uk/art/images/work/A/A00/A...</td>\n",
       "      <td>http://www.tate.org.uk/art/artworks/blake-the-...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     accession_number          artist artistRole  artistId  \\\n",
       "id                                                           \n",
       "1035           A00001   Blake, Robert     artist        38   \n",
       "1036           A00002   Blake, Robert     artist        38   \n",
       "1037           A00003   Blake, Robert     artist        38   \n",
       "1038           A00004   Blake, Robert     artist        38   \n",
       "1039           A00005  Blake, William     artist        39   \n",
       "\n",
       "                                                  title  \\\n",
       "id                                                        \n",
       "1035  A Figure Bowing before a Seated Old Man with h...   \n",
       "1036  Two Drawings of Frightened Figures, Probably f...   \n",
       "1037  The Preaching of Warning. Verso: An Old Man En...   \n",
       "1038     Six Drawings of Figures with Outstretched Arms   \n",
       "1039  The Circle of the Lustful: Francesca da Rimini...   \n",
       "\n",
       "                    dateText  \\\n",
       "id                             \n",
       "1035          date not known   \n",
       "1036          date not known   \n",
       "1037                 ?c.1785   \n",
       "1038          date not known   \n",
       "1039  1826–7, reprinted 1892   \n",
       "\n",
       "                                                 medium  \\\n",
       "id                                                        \n",
       "1035  Watercolour, ink, chalk and graphite on paper....   \n",
       "1036                                  Graphite on paper   \n",
       "1037        Graphite on paper. Verso: graphite on paper   \n",
       "1038                                  Graphite on paper   \n",
       "1039                            Line engraving on paper   \n",
       "\n",
       "                                             creditLine    year  \\\n",
       "id                                                                \n",
       "1035                Presented by Mrs John Richmond 1922     NaN   \n",
       "1036                Presented by Mrs John Richmond 1922     NaN   \n",
       "1037                Presented by Mrs John Richmond 1922  1785.0   \n",
       "1038                Presented by Mrs John Richmond 1922     NaN   \n",
       "1039  Purchased with the assistance of a special gra...  1826.0   \n",
       "\n",
       "      acquisitionYear             dimensions  width  height  depth units  \\\n",
       "id                                                                         \n",
       "1035             1922  support: 394 x 419 mm    394     419    NaN    mm   \n",
       "1036             1922  support: 311 x 213 mm    311     213    NaN    mm   \n",
       "1037             1922  support: 343 x 467 mm    343     467    NaN    mm   \n",
       "1038             1922  support: 318 x 394 mm    318     394    NaN    mm   \n",
       "1039             1919    image: 243 x 335 mm    243     335    NaN    mm   \n",
       "\n",
       "      inscription  thumbnailCopyright  \\\n",
       "id                                      \n",
       "1035          NaN                 NaN   \n",
       "1036          NaN                 NaN   \n",
       "1037          NaN                 NaN   \n",
       "1038          NaN                 NaN   \n",
       "1039          NaN                 NaN   \n",
       "\n",
       "                                           thumbnailUrl  \\\n",
       "id                                                        \n",
       "1035  http://www.tate.org.uk/art/images/work/A/A00/A...   \n",
       "1036  http://www.tate.org.uk/art/images/work/A/A00/A...   \n",
       "1037  http://www.tate.org.uk/art/images/work/A/A00/A...   \n",
       "1038  http://www.tate.org.uk/art/images/work/A/A00/A...   \n",
       "1039  http://www.tate.org.uk/art/images/work/A/A00/A...   \n",
       "\n",
       "                                                    url  \n",
       "id                                                       \n",
       "1035  http://www.tate.org.uk/art/artworks/blake-a-fi...  \n",
       "1036  http://www.tate.org.uk/art/artworks/blake-two-...  \n",
       "1037  http://www.tate.org.uk/art/artworks/blake-the-...  \n",
       "1038  http://www.tate.org.uk/art/artworks/blake-six-...  \n",
       "1039  http://www.tate.org.uk/art/artworks/blake-the-...  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv_df = pd.read_csv(csv_path,nrows=5, index_col='id')\n",
    "csv_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see, by adding that last parameter, we managed to change the id column used by Pandas. This column could be any other and doesn't need to be an id. All Pandas needs is a column name and it will do the rest."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### usecols\n",
    "\n",
    "This parameters allows you to select which columns should actually be recovered from the file. You can refer to them by name or by index but you cannot mix them, meaning, a single call may contain only numbers or only names."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>artist</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1035</th>\n",
       "      <td>Blake, Robert</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1036</th>\n",
       "      <td>Blake, Robert</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1037</th>\n",
       "      <td>Blake, Robert</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1038</th>\n",
       "      <td>Blake, Robert</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1039</th>\n",
       "      <td>Blake, William</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              artist\n",
       "id                  \n",
       "1035   Blake, Robert\n",
       "1036   Blake, Robert\n",
       "1037   Blake, Robert\n",
       "1038   Blake, Robert\n",
       "1039  Blake, William"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv_df = pd.read_csv(csv_path,nrows=5, index_col='id',usecols=['id','artist'])\n",
    "csv_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To keep the code clean, let's define an array of columns that we'll need going forward.\n",
    "We'll also drop the nrows parameter so that we can read all the rows at once."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\waee\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3020: DtypeWarning: Columns (9,13) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    },
    {
     "data": {
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       "\n",
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       "      <th>1035</th>\n",
       "      <td>Blake, Robert</td>\n",
       "      <td>A Figure Bowing before a Seated Old Man with h...</td>\n",
       "      <td>Watercolour, ink, chalk and graphite on paper....</td>\n",
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       "      <th>1036</th>\n",
       "      <td>Blake, Robert</td>\n",
       "      <td>Two Drawings of Frightened Figures, Probably f...</td>\n",
       "      <td>Graphite on paper</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>311</td>\n",
       "      <td>213</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1037</th>\n",
       "      <td>Blake, Robert</td>\n",
       "      <td>The Preaching of Warning. Verso: An Old Man En...</td>\n",
       "      <td>Graphite on paper. Verso: graphite on paper</td>\n",
       "      <td>1785</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>343</td>\n",
       "      <td>467</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1038</th>\n",
       "      <td>Blake, Robert</td>\n",
       "      <td>Six Drawings of Figures with Outstretched Arms</td>\n",
       "      <td>Graphite on paper</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>318</td>\n",
       "      <td>394</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1039</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>The Circle of the Lustful: Francesca da Rimini...</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1826</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>243</td>\n",
       "      <td>335</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1040</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>Ciampolo the Barrator Tormented by the Devils</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1826</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>240</td>\n",
       "      <td>338</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1041</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>The Baffled Devils Fighting</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1826</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>242</td>\n",
       "      <td>334</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1042</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>The Six-Footed Serpent Attacking Agnolo Brunel...</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1826</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>246</td>\n",
       "      <td>340</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1043</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>The Serpent Attacking Buoso Donati</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1826</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>241</td>\n",
       "      <td>335</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1044</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>The Pit of Disease: The Falsifiers</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1826</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>243</td>\n",
       "      <td>340</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1045</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>Dante Striking against Bocca Degli Abati</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1826</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>236</td>\n",
       "      <td>340</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1046</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>Job and his Family</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1828</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>184</td>\n",
       "      <td>150</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1047</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>Satan before the Throne of God</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>197</td>\n",
       "      <td>151</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>Job’s Sons and Daughters Overwhelmed by Satan</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>197</td>\n",
       "      <td>153</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1049</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>The Messengers tell Job of his Misfortunes</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>200</td>\n",
       "      <td>152</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1050</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>Satan Going Forth from the Presence of the Lor...</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>198</td>\n",
       "      <td>152</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1051</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>Satan Smiting Job with Sore Boils</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>198</td>\n",
       "      <td>153</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1052</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>Job’s Comforters</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>198</td>\n",
       "      <td>153</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1053</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>Job’s Despair</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>199</td>\n",
       "      <td>150</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1054</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>The Vision of Eliphaz</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>198</td>\n",
       "      <td>152</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1055</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>Job Rebuked by his Friends</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>198</td>\n",
       "      <td>152</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1056</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>Job’s Evil Dreams</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>197</td>\n",
       "      <td>152</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1057</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>The Wrath of Elihu</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>200</td>\n",
       "      <td>151</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1058</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>The Lord Answering Job out of the Whirlwind</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>198</td>\n",
       "      <td>151</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1059</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>When the Morning Stars Sang Together</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>191</td>\n",
       "      <td>150</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1060</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>Behemoth and Leviathan</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>200</td>\n",
       "      <td>151</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1061</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>The Fall of Satan</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>186</td>\n",
       "      <td>150</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1062</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>The Vision of Christ</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>200</td>\n",
       "      <td>151</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1063</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>Job’s Sacrifice</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>198</td>\n",
       "      <td>150</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1064</th>\n",
       "      <td>Blake, William</td>\n",
       "      <td>Every Man also Gave him a Piece of Money</td>\n",
       "      <td>Line engraving on paper</td>\n",
       "      <td>1825</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>197</td>\n",
       "      <td>150</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121196</th>\n",
       "      <td>Barlow, Phyllida</td>\n",
       "      <td>Untitled</td>\n",
       "      <td>Acrylic paint on paper</td>\n",
       "      <td>2003</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>558</td>\n",
       "      <td>760</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121197</th>\n",
       "      <td>Barlow, Phyllida</td>\n",
       "      <td>Untitled</td>\n",
       "      <td>Acrylic paint on paper</td>\n",
       "      <td>2004</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>380</td>\n",
       "      <td>566</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121198</th>\n",
       "      <td>Barlow, Phyllida</td>\n",
       "      <td>Untitled</td>\n",
       "      <td>Acrylic paint on paper</td>\n",
       "      <td>2006</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>560</td>\n",
       "      <td>762</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115637</th>\n",
       "      <td>Latham, John</td>\n",
       "      <td>Unedited Material From the Star</td>\n",
       "      <td>Film, 16mm, projection, colour and sound</td>\n",
       "      <td>1960</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115638</th>\n",
       "      <td>Latham, John</td>\n",
       "      <td>Encyclopedia Britannica</td>\n",
       "      <td>Film, 16mm, projection, black and white</td>\n",
       "      <td>1971</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122545</th>\n",
       "      <td>Kirkeby, Per</td>\n",
       "      <td>Composition</td>\n",
       "      <td>Oil paint on canvas</td>\n",
       "      <td>1978</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>2093</td>\n",
       "      <td>1679</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120104</th>\n",
       "      <td>Karamustafa, Gulsun</td>\n",
       "      <td>Memory of a Square</td>\n",
       "      <td>Video, 2 projections, black and white and sound</td>\n",
       "      <td>2005</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121565</th>\n",
       "      <td>Walker, Kelley</td>\n",
       "      <td>Will We Ever Kill The Bug</td>\n",
       "      <td>2 screenprints on fibreboard</td>\n",
       "      <td>2010</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116157</th>\n",
       "      <td>Bulloch, Angela</td>\n",
       "      <td>Aluminium 4</td>\n",
       "      <td>4 aluminium pixel boxes with DMX control box, ...</td>\n",
       "      <td>2012</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117761</th>\n",
       "      <td>Atlas, Charles</td>\n",
       "      <td>Joints 4tet Ensemble</td>\n",
       "      <td>Film, Super 8 mm, shown as video, 10 monitors,...</td>\n",
       "      <td>1971</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115217</th>\n",
       "      <td>T R Uthco (Doug Hall born 1944, Diane Andrews ...</td>\n",
       "      <td>The Eternal Frame</td>\n",
       "      <td>2 sofas, lamp, television, JFK mementos, tapes...</td>\n",
       "      <td>1975</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122537</th>\n",
       "      <td>Gordon, Douglas</td>\n",
       "      <td>Feature Film</td>\n",
       "      <td>Video, projection, colour and sound</td>\n",
       "      <td>1999</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120527</th>\n",
       "      <td>Black, Karla</td>\n",
       "      <td>At Fault</td>\n",
       "      <td>Cellophane, paint, sellotape, plaster powder, ...</td>\n",
       "      <td>2011</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127128</th>\n",
       "      <td>Lord, Andrew</td>\n",
       "      <td>Three Vases. Fist</td>\n",
       "      <td>Ceramic and gold</td>\n",
       "      <td>1985</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>368</td>\n",
       "      <td>267</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127129</th>\n",
       "      <td>Lord, Andrew</td>\n",
       "      <td>biting</td>\n",
       "      <td>Ceramic, epoxy, gold leaf, encre de Chine and ...</td>\n",
       "      <td>1996</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>705</td>\n",
       "      <td>470</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127130</th>\n",
       "      <td>Lord, Andrew</td>\n",
       "      <td>breathing</td>\n",
       "      <td>Ceramic, epoxy, gold leaf, encre de Chine and ...</td>\n",
       "      <td>1996</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>408</td>\n",
       "      <td>205</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127131</th>\n",
       "      <td>Lord, Andrew</td>\n",
       "      <td>Untitled (from the Gauguin Series)</td>\n",
       "      <td>Ceramic, silver and epoxy</td>\n",
       "      <td>2004</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>410</td>\n",
       "      <td>317</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121283</th>\n",
       "      <td>Rhodes, Lis</td>\n",
       "      <td>Light Music</td>\n",
       "      <td>Film, 16 mm, 2 projections, black and white, a...</td>\n",
       "      <td>1975</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129068</th>\n",
       "      <td>Lord, Andrew</td>\n",
       "      <td>Coffee service and tray. Impressionist set</td>\n",
       "      <td>Ceramic</td>\n",
       "      <td>1978</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117863</th>\n",
       "      <td>Andrade, Jonathas de</td>\n",
       "      <td>Tropical Hangover</td>\n",
       "      <td>151 text panels, typewritten ink on paper, 53 ...</td>\n",
       "      <td>2009</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120549</th>\n",
       "      <td>Oursler, Tony</td>\n",
       "      <td>The Influence Machine</td>\n",
       "      <td>Video, multiple projections, sound and smoke</td>\n",
       "      <td>2000</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123620</th>\n",
       "      <td>Sterne, Hedda</td>\n",
       "      <td>NY, NY No. X</td>\n",
       "      <td>Oil paint on canvas</td>\n",
       "      <td>1948</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>810</td>\n",
       "      <td>1155</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122900</th>\n",
       "      <td>Flanagan, Barry</td>\n",
       "      <td>sand girl</td>\n",
       "      <td>Film, Super 8mm, projection, colour</td>\n",
       "      <td>1970</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122958</th>\n",
       "      <td>P-Orridge, Genesis</td>\n",
       "      <td>Venus Mound (from Tampax Romana)</td>\n",
       "      <td>Wood, Perspex, plaster, wire, tampons and huma...</td>\n",
       "      <td>1976</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>305</td>\n",
       "      <td>305</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122959</th>\n",
       "      <td>P-Orridge, Genesis</td>\n",
       "      <td>It’s That Time Of The Month (from Tampax Romana)</td>\n",
       "      <td>Wood, Perspex, clock case, tampons and human b...</td>\n",
       "      <td>1975</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>305</td>\n",
       "      <td>305</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122960</th>\n",
       "      <td>P-Orridge, Genesis</td>\n",
       "      <td>Larvae (from Tampax Romana)</td>\n",
       "      <td>Perspex, Wood, hairpiece, tampon and human blood</td>\n",
       "      <td>1975</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>305</td>\n",
       "      <td>305</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122961</th>\n",
       "      <td>P-Orridge, Genesis</td>\n",
       "      <td>Living Womb (from Tampax Romana)</td>\n",
       "      <td>Wood, Perspex, plastic, photograph on paper, t...</td>\n",
       "      <td>1976</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>305</td>\n",
       "      <td>305</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121181</th>\n",
       "      <td>Hatoum, Mona</td>\n",
       "      <td>Present Tense</td>\n",
       "      <td>Soap and glass beads</td>\n",
       "      <td>1996</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>45</td>\n",
       "      <td>2410</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112306</th>\n",
       "      <td>Creed, Martin</td>\n",
       "      <td>Work No. 227: The lights going on and off</td>\n",
       "      <td>Gallery lighting</td>\n",
       "      <td>2000</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127035</th>\n",
       "      <td>Brunias, Agostino</td>\n",
       "      <td>Dancing Scene in the West Indies</td>\n",
       "      <td>Oil paint on canvas</td>\n",
       "      <td>1764</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>508</td>\n",
       "      <td>660</td>\n",
       "      <td>mm</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>69201 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   artist  \\\n",
       "id                                                          \n",
       "1035                                        Blake, Robert   \n",
       "1036                                        Blake, Robert   \n",
       "1037                                        Blake, Robert   \n",
       "1038                                        Blake, Robert   \n",
       "1039                                       Blake, William   \n",
       "1040                                       Blake, William   \n",
       "1041                                       Blake, William   \n",
       "1042                                       Blake, William   \n",
       "1043                                       Blake, William   \n",
       "1044                                       Blake, William   \n",
       "1045                                       Blake, William   \n",
       "1046                                       Blake, William   \n",
       "1047                                       Blake, William   \n",
       "1048                                       Blake, William   \n",
       "1049                                       Blake, William   \n",
       "1050                                       Blake, William   \n",
       "1051                                       Blake, William   \n",
       "1052                                       Blake, William   \n",
       "1053                                       Blake, William   \n",
       "1054                                       Blake, William   \n",
       "1055                                       Blake, William   \n",
       "1056                                       Blake, William   \n",
       "1057                                       Blake, William   \n",
       "1058                                       Blake, William   \n",
       "1059                                       Blake, William   \n",
       "1060                                       Blake, William   \n",
       "1061                                       Blake, William   \n",
       "1062                                       Blake, William   \n",
       "1063                                       Blake, William   \n",
       "1064                                       Blake, William   \n",
       "...                                                   ...   \n",
       "121196                                   Barlow, Phyllida   \n",
       "121197                                   Barlow, Phyllida   \n",
       "121198                                   Barlow, Phyllida   \n",
       "115637                                       Latham, John   \n",
       "115638                                       Latham, John   \n",
       "122545                                       Kirkeby, Per   \n",
       "120104                                Karamustafa, Gulsun   \n",
       "121565                                     Walker, Kelley   \n",
       "116157                                    Bulloch, Angela   \n",
       "117761                                     Atlas, Charles   \n",
       "115217  T R Uthco (Doug Hall born 1944, Diane Andrews ...   \n",
       "122537                                    Gordon, Douglas   \n",
       "120527                                       Black, Karla   \n",
       "127128                                       Lord, Andrew   \n",
       "127129                                       Lord, Andrew   \n",
       "127130                                       Lord, Andrew   \n",
       "127131                                       Lord, Andrew   \n",
       "121283                                        Rhodes, Lis   \n",
       "129068                                       Lord, Andrew   \n",
       "117863                               Andrade, Jonathas de   \n",
       "120549                                      Oursler, Tony   \n",
       "123620                                      Sterne, Hedda   \n",
       "122900                                    Flanagan, Barry   \n",
       "122958                                 P-Orridge, Genesis   \n",
       "122959                                 P-Orridge, Genesis   \n",
       "122960                                 P-Orridge, Genesis   \n",
       "122961                                 P-Orridge, Genesis   \n",
       "121181                                       Hatoum, Mona   \n",
       "112306                                      Creed, Martin   \n",
       "127035                                  Brunias, Agostino   \n",
       "\n",
       "                                                    title  \\\n",
       "id                                                          \n",
       "1035    A Figure Bowing before a Seated Old Man with h...   \n",
       "1036    Two Drawings of Frightened Figures, Probably f...   \n",
       "1037    The Preaching of Warning. Verso: An Old Man En...   \n",
       "1038       Six Drawings of Figures with Outstretched Arms   \n",
       "1039    The Circle of the Lustful: Francesca da Rimini...   \n",
       "1040        Ciampolo the Barrator Tormented by the Devils   \n",
       "1041                          The Baffled Devils Fighting   \n",
       "1042    The Six-Footed Serpent Attacking Agnolo Brunel...   \n",
       "1043                   The Serpent Attacking Buoso Donati   \n",
       "1044                   The Pit of Disease: The Falsifiers   \n",
       "1045             Dante Striking against Bocca Degli Abati   \n",
       "1046                                   Job and his Family   \n",
       "1047                       Satan before the Throne of God   \n",
       "1048        Job’s Sons and Daughters Overwhelmed by Satan   \n",
       "1049           The Messengers tell Job of his Misfortunes   \n",
       "1050    Satan Going Forth from the Presence of the Lor...   \n",
       "1051                    Satan Smiting Job with Sore Boils   \n",
       "1052                                     Job’s Comforters   \n",
       "1053                                        Job’s Despair   \n",
       "1054                                The Vision of Eliphaz   \n",
       "1055                           Job Rebuked by his Friends   \n",
       "1056                                    Job’s Evil Dreams   \n",
       "1057                                   The Wrath of Elihu   \n",
       "1058          The Lord Answering Job out of the Whirlwind   \n",
       "1059                 When the Morning Stars Sang Together   \n",
       "1060                               Behemoth and Leviathan   \n",
       "1061                                    The Fall of Satan   \n",
       "1062                                 The Vision of Christ   \n",
       "1063                                      Job’s Sacrifice   \n",
       "1064             Every Man also Gave him a Piece of Money   \n",
       "...                                                   ...   \n",
       "121196                                           Untitled   \n",
       "121197                                           Untitled   \n",
       "121198                                           Untitled   \n",
       "115637                    Unedited Material From the Star   \n",
       "115638                            Encyclopedia Britannica   \n",
       "122545                                        Composition   \n",
       "120104                                 Memory of a Square   \n",
       "121565                          Will We Ever Kill The Bug   \n",
       "116157                                        Aluminium 4   \n",
       "117761                               Joints 4tet Ensemble   \n",
       "115217                                  The Eternal Frame   \n",
       "122537                                       Feature Film   \n",
       "120527                                           At Fault   \n",
       "127128                                  Three Vases. Fist   \n",
       "127129                                             biting   \n",
       "127130                                          breathing   \n",
       "127131                 Untitled (from the Gauguin Series)   \n",
       "121283                                        Light Music   \n",
       "129068         Coffee service and tray. Impressionist set   \n",
       "117863                                  Tropical Hangover   \n",
       "120549                              The Influence Machine   \n",
       "123620                                       NY, NY No. X   \n",
       "122900                                          sand girl   \n",
       "122958                   Venus Mound (from Tampax Romana)   \n",
       "122959   It’s That Time Of The Month (from Tampax Romana)   \n",
       "122960                        Larvae (from Tampax Romana)   \n",
       "122961                   Living Womb (from Tampax Romana)   \n",
       "121181                                      Present Tense   \n",
       "112306          Work No. 227: The lights going on and off   \n",
       "127035                   Dancing Scene in the West Indies   \n",
       "\n",
       "                                                   medium  year  \\\n",
       "id                                                                \n",
       "1035    Watercolour, ink, chalk and graphite on paper....   NaN   \n",
       "1036                                    Graphite on paper   NaN   \n",
       "1037          Graphite on paper. Verso: graphite on paper  1785   \n",
       "1038                                    Graphite on paper   NaN   \n",
       "1039                              Line engraving on paper  1826   \n",
       "1040                              Line engraving on paper  1826   \n",
       "1041                              Line engraving on paper  1826   \n",
       "1042                              Line engraving on paper  1826   \n",
       "1043                              Line engraving on paper  1826   \n",
       "1044                              Line engraving on paper  1826   \n",
       "1045                              Line engraving on paper  1826   \n",
       "1046                              Line engraving on paper  1828   \n",
       "1047                              Line engraving on paper  1825   \n",
       "1048                          Line engraving on paper      1825   \n",
       "1049                              Line engraving on paper  1825   \n",
       "1050                              Line engraving on paper  1825   \n",
       "1051                              Line engraving on paper  1825   \n",
       "1052                              Line engraving on paper  1825   \n",
       "1053                              Line engraving on paper  1825   \n",
       "1054                              Line engraving on paper  1825   \n",
       "1055                              Line engraving on paper  1825   \n",
       "1056                              Line engraving on paper  1825   \n",
       "1057                              Line engraving on paper  1825   \n",
       "1058                              Line engraving on paper  1825   \n",
       "1059                              Line engraving on paper  1825   \n",
       "1060                              Line engraving on paper  1825   \n",
       "1061                              Line engraving on paper  1825   \n",
       "1062                              Line engraving on paper  1825   \n",
       "1063                              Line engraving on paper  1825   \n",
       "1064                              Line engraving on paper  1825   \n",
       "...                                                   ...   ...   \n",
       "121196                             Acrylic paint on paper  2003   \n",
       "121197                             Acrylic paint on paper  2004   \n",
       "121198                             Acrylic paint on paper  2006   \n",
       "115637           Film, 16mm, projection, colour and sound  1960   \n",
       "115638            Film, 16mm, projection, black and white  1971   \n",
       "122545                                Oil paint on canvas  1978   \n",
       "120104    Video, 2 projections, black and white and sound  2005   \n",
       "121565                       2 screenprints on fibreboard  2010   \n",
       "116157  4 aluminium pixel boxes with DMX control box, ...  2012   \n",
       "117761  Film, Super 8 mm, shown as video, 10 monitors,...  1971   \n",
       "115217  2 sofas, lamp, television, JFK mementos, tapes...  1975   \n",
       "122537             Video, projection, colour and sound     1999   \n",
       "120527  Cellophane, paint, sellotape, plaster powder, ...  2011   \n",
       "127128                                   Ceramic and gold  1985   \n",
       "127129  Ceramic, epoxy, gold leaf, encre de Chine and ...  1996   \n",
       "127130  Ceramic, epoxy, gold leaf, encre de Chine and ...  1996   \n",
       "127131                          Ceramic, silver and epoxy  2004   \n",
       "121283  Film, 16 mm, 2 projections, black and white, a...  1975   \n",
       "129068                                            Ceramic  1978   \n",
       "117863  151 text panels, typewritten ink on paper, 53 ...  2009   \n",
       "120549       Video, multiple projections, sound and smoke  2000   \n",
       "123620                                Oil paint on canvas  1948   \n",
       "122900                Film, Super 8mm, projection, colour  1970   \n",
       "122958  Wood, Perspex, plaster, wire, tampons and huma...  1976   \n",
       "122959  Wood, Perspex, clock case, tampons and human b...  1975   \n",
       "122960   Perspex, Wood, hairpiece, tampon and human blood  1975   \n",
       "122961  Wood, Perspex, plastic, photograph on paper, t...  1976   \n",
       "121181                               Soap and glass beads  1996   \n",
       "112306                                   Gallery lighting  2000   \n",
       "127035                                Oil paint on canvas  1764   \n",
       "\n",
       "        acquisitionYear width height units  \n",
       "id                                          \n",
       "1035             1922.0   394    419    mm  \n",
       "1036             1922.0   311    213    mm  \n",
       "1037             1922.0   343    467    mm  \n",
       "1038             1922.0   318    394    mm  \n",
       "1039             1919.0   243    335    mm  \n",
       "1040             1919.0   240    338    mm  \n",
       "1041             1919.0   242    334    mm  \n",
       "1042             1919.0   246    340    mm  \n",
       "1043             1919.0   241    335    mm  \n",
       "1044             1919.0   243    340    mm  \n",
       "1045             1919.0   236    340    mm  \n",
       "1046             1919.0   184    150    mm  \n",
       "1047             1919.0   197    151    mm  \n",
       "1048             1919.0   197    153    mm  \n",
       "1049             1919.0   200    152    mm  \n",
       "1050             1919.0   198    152    mm  \n",
       "1051             1919.0   198    153    mm  \n",
       "1052             1919.0   198    153    mm  \n",
       "1053             1919.0   199    150    mm  \n",
       "1054             1919.0   198    152    mm  \n",
       "1055             1919.0   198    152    mm  \n",
       "1056             1919.0   197    152    mm  \n",
       "1057             1919.0   200    151    mm  \n",
       "1058             1919.0   198    151    mm  \n",
       "1059             1919.0   191    150    mm  \n",
       "1060             1919.0   200    151    mm  \n",
       "1061             1919.0   186    150    mm  \n",
       "1062             1919.0   200    151    mm  \n",
       "1063             1919.0   198    150    mm  \n",
       "1064             1919.0   197    150    mm  \n",
       "...                 ...   ...    ...   ...  \n",
       "121196           2013.0   558    760    mm  \n",
       "121197           2013.0   380    566    mm  \n",
       "121198           2013.0   560    762    mm  \n",
       "115637           2013.0   NaN    NaN   NaN  \n",
       "115638           2013.0   NaN    NaN   NaN  \n",
       "122545           2013.0  2093   1679    mm  \n",
       "120104           2013.0   NaN    NaN   NaN  \n",
       "121565           2013.0   NaN    NaN   NaN  \n",
       "116157           2013.0   NaN    NaN   NaN  \n",
       "117761           2013.0   NaN    NaN   NaN  \n",
       "115217           2013.0   NaN    NaN   NaN  \n",
       "122537           2013.0   NaN    NaN   NaN  \n",
       "120527           2013.0   NaN    NaN   NaN  \n",
       "127128           2013.0   368    267    mm  \n",
       "127129           2013.0   705    470    mm  \n",
       "127130           2013.0   408    205    mm  \n",
       "127131           2013.0   410    317    mm  \n",
       "121283           2013.0   NaN    NaN   NaN  \n",
       "129068           2013.0    57     57    mm  \n",
       "117863           2013.0   NaN    NaN   NaN  \n",
       "120549           2013.0   NaN    NaN   NaN  \n",
       "123620           2013.0   810   1155    mm  \n",
       "122900           2013.0   NaN    NaN   NaN  \n",
       "122958           2013.0   305    305    mm  \n",
       "122959           2013.0   305    305    mm  \n",
       "122960           2013.0   305    305    mm  \n",
       "122961           2013.0   305    305    mm  \n",
       "121181           2013.0    45   2410    mm  \n",
       "112306           2013.0   NaN    NaN   NaN  \n",
       "127035           2013.0   508    660    mm  \n",
       "\n",
       "[69201 rows x 8 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols = ['id','artist','title','medium','year','acquisitionYear','height','width','units']\n",
    "csv_df = pd.read_csv(csv_path, index_col='id',usecols=cols)\n",
    "csv_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "csv_df.to_pickle('C:\\\\Users\\\\waee\\\\Downloads\\\\test.bin')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we simply save the data obtained using Pickle, a serialization tool.\n",
    "Pandas has it already included, so no explicit import is actually needed.\n",
    "\n",
    "## Json Processing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pandas has real way of processing Json directly, so it must be transformed into a format that Pandas can use first.\n",
    "Thankfully, such a task is relatively easy to accomplish in Python."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "#First we define an array with the names of the columns we want to retrieve from the Json files\n",
    "cols_retrieve = ['id','all_artists','title','medium','acquisitionYear','height','width']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import json\n",
    "def retrieveDataFromFile(path, cols):\n",
    "    with open(path) as artFile:\n",
    "        data = json.load(artFile)\n",
    "    record = []\n",
    "    for field in cols:\n",
    "        try:\n",
    "            record.append(data[field])\n",
    "        except:\n",
    "            record.append(np.nan)\n",
    "    return tuple(record)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This function, as the name implies, retrieves data from the specified file. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "jsonTest = \"C:\\\\Users\\\\waee\\\\Downloads\\\\collection-master\\\\collection-master\\\\artworks\\\\a\\\\000\\\\a00001-1035.json\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1035,\n",
       " 'Robert Blake',\n",
       " 'A Figure Bowing before a Seated Old Man with his Arm Outstretched in Benediction. Verso: Indecipherable Sketch',\n",
       " 'Watercolour, ink, chalk and graphite on paper. Verso: graphite on paper',\n",
       " 1922,\n",
       " '419',\n",
       " '394')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "retrieveDataFromFile(jsonTest,cols_retrieve)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "artwork_root ='C:\\\\Users\\waee\\\\Downloads\\\\collection-master\\\\collection-master\\\\artworks' "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we'll walk through the file structure to retrieve all of the json files. WARNING: This might take a long time.\n",
    "If you don't want to wait, place a break after the if so that only the first file of each directory will be examined."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>all_artists</th>\n",
       "      <th>title</th>\n",
       "      <th>medium</th>\n",
       "      <th>acquisitionYear</th>\n",
       "      <th>height</th>\n",
       "      <th>width</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1035</th>\n",
       "      <td>Robert Blake</td>\n",
       "      <td>A Figure Bowing before a Seated Old Man with h...</td>\n",
       "      <td>Watercolour, ink, chalk and graphite on paper....</td>\n",
       "      <td>1922</td>\n",
       "      <td>419</td>\n",
       "      <td>394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20230</th>\n",
       "      <td>Sir Edward Coley Burne-Jones, Bt</td>\n",
       "      <td>Study of Heads for a Pietà</td>\n",
       "      <td>Graphite and chalk on paper</td>\n",
       "      <td>1927</td>\n",
       "      <td>154</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6725</th>\n",
       "      <td>Arthur Boyd Houghton</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Graphite on paper</td>\n",
       "      <td>1922</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7330</th>\n",
       "      <td>George Jones</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Ink on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7430</th>\n",
       "      <td>George Jones</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Ink on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7530</th>\n",
       "      <td>George Jones</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Ink on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7630</th>\n",
       "      <td>George Jones</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Watercolour on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7730</th>\n",
       "      <td>George Jones</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Ink and graphite on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9492</th>\n",
       "      <td>Sir John Everett Millais, Bt</td>\n",
       "      <td>The Sower</td>\n",
       "      <td>Wood engraving on paper</td>\n",
       "      <td>1924</td>\n",
       "      <td>108</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14407</th>\n",
       "      <td>Reuben Townroe</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Watercolour on paper</td>\n",
       "      <td>1905</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14700</th>\n",
       "      <td>Joseph Mallord William Turner</td>\n",
       "      <td>Peat Bog, Scotland</td>\n",
       "      <td>Etching and engraving on paper</td>\n",
       "      <td>1925</td>\n",
       "      <td>258</td>\n",
       "      <td>178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12191</th>\n",
       "      <td>Helen Beatrix Potter</td>\n",
       "      <td>The Mice at Work: Threading the Needle</td>\n",
       "      <td>Ink, watercolour and gouache on paper</td>\n",
       "      <td>1946</td>\n",
       "      <td>92</td>\n",
       "      <td>111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69330</th>\n",
       "      <td>George Jones</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Watercolour on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69430</th>\n",
       "      <td>George Jones</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Ink on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69530</th>\n",
       "      <td>George Jones</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Watercolour, ink and graphite on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69630</th>\n",
       "      <td>George Jones</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Ink and graphite on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69730</th>\n",
       "      <td>George Jones</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Watercolour and graphite on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69830</th>\n",
       "      <td>George Jones</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Watercolour and graphite on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98171</th>\n",
       "      <td>Alex Katz</td>\n",
       "      <td>Pansies</td>\n",
       "      <td>Oil paint on hardboard</td>\n",
       "      <td>2008</td>\n",
       "      <td>404</td>\n",
       "      <td>309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98537</th>\n",
       "      <td>Joseph Beuys</td>\n",
       "      <td>Weird Sister</td>\n",
       "      <td>Graphite and oil paint on acetate</td>\n",
       "      <td>2008</td>\n",
       "      <td>474</td>\n",
       "      <td>391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97256</th>\n",
       "      <td>Robert Mapplethorpe</td>\n",
       "      <td>Cock and Devil</td>\n",
       "      <td>Photograph, gelatine silver print on paper</td>\n",
       "      <td>2009</td>\n",
       "      <td>472</td>\n",
       "      <td>371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97551</th>\n",
       "      <td>Andy Warhol</td>\n",
       "      <td>Male Nude</td>\n",
       "      <td>4 photographs, gelatine silver print on paper ...</td>\n",
       "      <td>2009</td>\n",
       "      <td>540</td>\n",
       "      <td>695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99037</th>\n",
       "      <td>Andy Warhol</td>\n",
       "      <td>H.C. Andersen 1987</td>\n",
       "      <td>Screenprint on paper</td>\n",
       "      <td>2009</td>\n",
       "      <td>599</td>\n",
       "      <td>820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98345</th>\n",
       "      <td>Damien Hirst</td>\n",
       "      <td>Trinity - Pharmacology, Physiology, Pathology</td>\n",
       "      <td>Glass, fibreboard, wood, steel and plastic</td>\n",
       "      <td>2009</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99125</th>\n",
       "      <td>Joseph Beuys</td>\n",
       "      <td>Untitled</td>\n",
       "      <td>Photograph, gelatine silver print on canvas</td>\n",
       "      <td>2009</td>\n",
       "      <td>2275</td>\n",
       "      <td>2330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99132</th>\n",
       "      <td>Joseph Beuys</td>\n",
       "      <td>Felt Action</td>\n",
       "      <td>Oil paint and felt on paper</td>\n",
       "      <td>2009</td>\n",
       "      <td>434</td>\n",
       "      <td>647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105706</th>\n",
       "      <td>Joseph Beuys</td>\n",
       "      <td>Discussion, Documenta 6 Kassel</td>\n",
       "      <td>Print on paper</td>\n",
       "      <td>2009</td>\n",
       "      <td>435</td>\n",
       "      <td>609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105826</th>\n",
       "      <td>Joseph Beuys</td>\n",
       "      <td>‘Die zeit der politischen Parteien ist vorbei’</td>\n",
       "      <td>Print on paper</td>\n",
       "      <td>2009</td>\n",
       "      <td>162</td>\n",
       "      <td>273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105944</th>\n",
       "      <td>Joseph Beuys</td>\n",
       "      <td>Jahre Capital - Kunstkompass Galerie Denise René</td>\n",
       "      <td>Print on paper</td>\n",
       "      <td>2009</td>\n",
       "      <td>315</td>\n",
       "      <td>679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106055</th>\n",
       "      <td>Joseph Beuys</td>\n",
       "      <td>Joseph Beuys: A Private Collection. Stadthaus ...</td>\n",
       "      <td>Print on paper</td>\n",
       "      <td>2009</td>\n",
       "      <td>565</td>\n",
       "      <td>808</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24928</th>\n",
       "      <td>Lady Wharncliffe (née Lady Caroline Mary Eliza...</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Graphite on paper</td>\n",
       "      <td>1997</td>\n",
       "      <td>157</td>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25315</th>\n",
       "      <td>British (?) School</td>\n",
       "      <td>[title not known] Verso: [title not known]</td>\n",
       "      <td>Ink and watercolour on paper. Verso: graphite ...</td>\n",
       "      <td>1997</td>\n",
       "      <td>149</td>\n",
       "      <td>160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25456</th>\n",
       "      <td>after John Flaxman</td>\n",
       "      <td>The Fiery Serpents</td>\n",
       "      <td>Etching on paper</td>\n",
       "      <td>1997</td>\n",
       "      <td>192</td>\n",
       "      <td>131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25801</th>\n",
       "      <td>after John Flaxman</td>\n",
       "      <td>Ulysses Giving Wine to Polyphemus</td>\n",
       "      <td>Engraving and etching on paper</td>\n",
       "      <td>1997</td>\n",
       "      <td>247</td>\n",
       "      <td>170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25254</th>\n",
       "      <td>Abraham Cooper</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Etching on paper</td>\n",
       "      <td>1997</td>\n",
       "      <td>76</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25746</th>\n",
       "      <td>François Louis Thomas Francia</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Etching and watercolour on paper</td>\n",
       "      <td>1997</td>\n",
       "      <td>255</td>\n",
       "      <td>183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25392</th>\n",
       "      <td>John Sell Cotman</td>\n",
       "      <td>Tan-y-Bwlch, Merionethshire, North Wales</td>\n",
       "      <td>Etching on paper</td>\n",
       "      <td>1997</td>\n",
       "      <td>171</td>\n",
       "      <td>113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25713</th>\n",
       "      <td>British (?) School</td>\n",
       "      <td>Edward Young D.C.L.</td>\n",
       "      <td>Etching on paper</td>\n",
       "      <td>1997</td>\n",
       "      <td>66</td>\n",
       "      <td>106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25933</th>\n",
       "      <td>British (?) School</td>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Woodcut on paper</td>\n",
       "      <td>1997</td>\n",
       "      <td>191</td>\n",
       "      <td>250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80033</th>\n",
       "      <td>Sir Anthony Caro</td>\n",
       "      <td>#73 Untitled</td>\n",
       "      <td>Relief, pencil, chalk, acrylic and paper</td>\n",
       "      <td>2004</td>\n",
       "      <td>630</td>\n",
       "      <td>478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80857</th>\n",
       "      <td>Richard Parkes Bonington</td>\n",
       "      <td>French Coast with Fishermen</td>\n",
       "      <td>Oil paint on canvas</td>\n",
       "      <td>2004</td>\n",
       "      <td>967</td>\n",
       "      <td>643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84316</th>\n",
       "      <td>Markus Schinwald</td>\n",
       "      <td>Dictio pii</td>\n",
       "      <td>Film, 35 mm, shown as video, projection, colou...</td>\n",
       "      <td>2005</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88228</th>\n",
       "      <td>Shoji Hamada</td>\n",
       "      <td>Yunomi</td>\n",
       "      <td>Reduced stoneware</td>\n",
       "      <td>2005</td>\n",
       "      <td>75</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88060</th>\n",
       "      <td>Michelangelo Pistoletto</td>\n",
       "      <td>Venus of the Rags</td>\n",
       "      <td>Marble and textiles</td>\n",
       "      <td>2006</td>\n",
       "      <td>3400</td>\n",
       "      <td>2120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81819</th>\n",
       "      <td>Keith Coventry</td>\n",
       "      <td>Heygate Estate</td>\n",
       "      <td>Oil paint on canvas, wood and glass</td>\n",
       "      <td>2006</td>\n",
       "      <td>712</td>\n",
       "      <td>966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26747</th>\n",
       "      <td>Yves Tanguy</td>\n",
       "      <td>Untitled</td>\n",
       "      <td>Watercolour on paper</td>\n",
       "      <td>2007</td>\n",
       "      <td>235</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94662</th>\n",
       "      <td>Linder</td>\n",
       "      <td>Untitled</td>\n",
       "      <td>Printed papers on paper</td>\n",
       "      <td>2007</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66602</th>\n",
       "      <td>Andy Warhol</td>\n",
       "      <td>Brooke Hayward</td>\n",
       "      <td>Acrylic paint and silkscreen on 4 canvases</td>\n",
       "      <td>2008</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99423</th>\n",
       "      <td>William Roberts</td>\n",
       "      <td>The Interruption</td>\n",
       "      <td>Graphite on paper</td>\n",
       "      <td>2008</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100499</th>\n",
       "      <td>David Batchelor</td>\n",
       "      <td>Spectrum of Brick Lane 2</td>\n",
       "      <td>Lightboxes, steel shelving, acrylic sheet, flu...</td>\n",
       "      <td>2008</td>\n",
       "      <td>900</td>\n",
       "      <td>5200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101563</th>\n",
       "      <td>Nedko Solakov</td>\n",
       "      <td>A Life (Black and White)</td>\n",
       "      <td>Performance, 2 people</td>\n",
       "      <td>2009</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96968</th>\n",
       "      <td>William Blake</td>\n",
       "      <td>The Book of Thel pl. 6</td>\n",
       "      <td>Etching with paint, watercolour and ink on paper</td>\n",
       "      <td>2010</td>\n",
       "      <td>186</td>\n",
       "      <td>260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108923</th>\n",
       "      <td>Keith Arnatt</td>\n",
       "      <td>Gardeners</td>\n",
       "      <td>Photograph, gelatin silver print on paper</td>\n",
       "      <td>2010</td>\n",
       "      <td>304</td>\n",
       "      <td>404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90120</th>\n",
       "      <td>Prunella Clough</td>\n",
       "      <td>Stack</td>\n",
       "      <td>Oil paint on canvas</td>\n",
       "      <td>2010</td>\n",
       "      <td>1880</td>\n",
       "      <td>1510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111919</th>\n",
       "      <td>Dominique Gonzalez-Foerster</td>\n",
       "      <td>Noreturn</td>\n",
       "      <td>Video, high definition, colour and sound</td>\n",
       "      <td>2011</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118532</th>\n",
       "      <td>Trevor Bell</td>\n",
       "      <td>Place</td>\n",
       "      <td>Acrylic paint on paper</td>\n",
       "      <td>2012</td>\n",
       "      <td>980</td>\n",
       "      <td>750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117815</th>\n",
       "      <td>Jiro Takamatsu</td>\n",
       "      <td>Shadow</td>\n",
       "      <td>Graphite on paper</td>\n",
       "      <td>2012</td>\n",
       "      <td>181</td>\n",
       "      <td>260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117484</th>\n",
       "      <td>Shelagh Cluett</td>\n",
       "      <td>Flux III</td>\n",
       "      <td>Steel, bitumen, latex, clay and cotton string</td>\n",
       "      <td>2012</td>\n",
       "      <td>950</td>\n",
       "      <td>2430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89762</th>\n",
       "      <td>Robert Mangold</td>\n",
       "      <td>Red Wall</td>\n",
       "      <td>Oil paint on fibreboard</td>\n",
       "      <td>2013</td>\n",
       "      <td>2450</td>\n",
       "      <td>2450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123531</th>\n",
       "      <td>Birdhead (Ji Weiyu, born 1980; Song Tao, born ...</td>\n",
       "      <td>Welcome to Birdhead World Again</td>\n",
       "      <td>6 photographs, cellulose print, black and whit...</td>\n",
       "      <td>2013</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>738 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              all_artists  \\\n",
       "id                                                          \n",
       "1035                                         Robert Blake   \n",
       "20230                    Sir Edward Coley Burne-Jones, Bt   \n",
       "6725                                 Arthur Boyd Houghton   \n",
       "7330                                         George Jones   \n",
       "7430                                         George Jones   \n",
       "7530                                         George Jones   \n",
       "7630                                         George Jones   \n",
       "7730                                         George Jones   \n",
       "9492                         Sir John Everett Millais, Bt   \n",
       "14407                                      Reuben Townroe   \n",
       "14700                       Joseph Mallord William Turner   \n",
       "12191                                Helen Beatrix Potter   \n",
       "69330                                        George Jones   \n",
       "69430                                        George Jones   \n",
       "69530                                        George Jones   \n",
       "69630                                        George Jones   \n",
       "69730                                        George Jones   \n",
       "69830                                        George Jones   \n",
       "98171                                           Alex Katz   \n",
       "98537                                        Joseph Beuys   \n",
       "97256                                 Robert Mapplethorpe   \n",
       "97551                                         Andy Warhol   \n",
       "99037                                         Andy Warhol   \n",
       "98345                                        Damien Hirst   \n",
       "99125                                        Joseph Beuys   \n",
       "99132                                        Joseph Beuys   \n",
       "105706                                       Joseph Beuys   \n",
       "105826                                       Joseph Beuys   \n",
       "105944                                       Joseph Beuys   \n",
       "106055                                       Joseph Beuys   \n",
       "...                                                   ...   \n",
       "24928   Lady Wharncliffe (née Lady Caroline Mary Eliza...   \n",
       "25315                                  British (?) School   \n",
       "25456                                  after John Flaxman   \n",
       "25801                                  after John Flaxman   \n",
       "25254                                      Abraham Cooper   \n",
       "25746                       François Louis Thomas Francia   \n",
       "25392                                    John Sell Cotman   \n",
       "25713                                  British (?) School   \n",
       "25933                                  British (?) School   \n",
       "80033                                    Sir Anthony Caro   \n",
       "80857                            Richard Parkes Bonington   \n",
       "84316                                    Markus Schinwald   \n",
       "88228                                        Shoji Hamada   \n",
       "88060                             Michelangelo Pistoletto   \n",
       "81819                                      Keith Coventry   \n",
       "26747                                         Yves Tanguy   \n",
       "94662                                              Linder   \n",
       "66602                                         Andy Warhol   \n",
       "99423                                     William Roberts   \n",
       "100499                                    David Batchelor   \n",
       "101563                                      Nedko Solakov   \n",
       "96968                                       William Blake   \n",
       "108923                                       Keith Arnatt   \n",
       "90120                                     Prunella Clough   \n",
       "111919                        Dominique Gonzalez-Foerster   \n",
       "118532                                        Trevor Bell   \n",
       "117815                                     Jiro Takamatsu   \n",
       "117484                                     Shelagh Cluett   \n",
       "89762                                      Robert Mangold   \n",
       "123531  Birdhead (Ji Weiyu, born 1980; Song Tao, born ...   \n",
       "\n",
       "                                                    title  \\\n",
       "id                                                          \n",
       "1035    A Figure Bowing before a Seated Old Man with h...   \n",
       "20230                          Study of Heads for a Pietà   \n",
       "6725                                    [title not known]   \n",
       "7330                                    [title not known]   \n",
       "7430                                    [title not known]   \n",
       "7530                                    [title not known]   \n",
       "7630                                    [title not known]   \n",
       "7730                                    [title not known]   \n",
       "9492                                            The Sower   \n",
       "14407                                   [title not known]   \n",
       "14700                                  Peat Bog, Scotland   \n",
       "12191              The Mice at Work: Threading the Needle   \n",
       "69330                                   [title not known]   \n",
       "69430                                   [title not known]   \n",
       "69530                                   [title not known]   \n",
       "69630                                   [title not known]   \n",
       "69730                                   [title not known]   \n",
       "69830                                   [title not known]   \n",
       "98171                                             Pansies   \n",
       "98537                                        Weird Sister   \n",
       "97256                                      Cock and Devil   \n",
       "97551                                           Male Nude   \n",
       "99037                                  H.C. Andersen 1987   \n",
       "98345       Trinity - Pharmacology, Physiology, Pathology   \n",
       "99125                                            Untitled   \n",
       "99132                                         Felt Action   \n",
       "105706                     Discussion, Documenta 6 Kassel   \n",
       "105826     ‘Die zeit der politischen Parteien ist vorbei’   \n",
       "105944   Jahre Capital - Kunstkompass Galerie Denise René   \n",
       "106055  Joseph Beuys: A Private Collection. Stadthaus ...   \n",
       "...                                                   ...   \n",
       "24928                                   [title not known]   \n",
       "25315          [title not known] Verso: [title not known]   \n",
       "25456                                  The Fiery Serpents   \n",
       "25801                   Ulysses Giving Wine to Polyphemus   \n",
       "25254                                   [title not known]   \n",
       "25746                                   [title not known]   \n",
       "25392            Tan-y-Bwlch, Merionethshire, North Wales   \n",
       "25713                                 Edward Young D.C.L.   \n",
       "25933                                   [title not known]   \n",
       "80033                                        #73 Untitled   \n",
       "80857                         French Coast with Fishermen   \n",
       "84316                                          Dictio pii   \n",
       "88228                                              Yunomi   \n",
       "88060                                   Venus of the Rags   \n",
       "81819                                      Heygate Estate   \n",
       "26747                                            Untitled   \n",
       "94662                                            Untitled   \n",
       "66602                                      Brooke Hayward   \n",
       "99423                                    The Interruption   \n",
       "100499                           Spectrum of Brick Lane 2   \n",
       "101563                           A Life (Black and White)   \n",
       "96968                              The Book of Thel pl. 6   \n",
       "108923                                          Gardeners   \n",
       "90120                                               Stack   \n",
       "111919                                           Noreturn   \n",
       "118532                                              Place   \n",
       "117815                                             Shadow   \n",
       "117484                                           Flux III   \n",
       "89762                                            Red Wall   \n",
       "123531                    Welcome to Birdhead World Again   \n",
       "\n",
       "                                                   medium  acquisitionYear  \\\n",
       "id                                                                           \n",
       "1035    Watercolour, ink, chalk and graphite on paper....             1922   \n",
       "20230                         Graphite and chalk on paper             1927   \n",
       "6725                                    Graphite on paper             1922   \n",
       "7330                                         Ink on paper             1888   \n",
       "7430                                         Ink on paper             1888   \n",
       "7530                                         Ink on paper             1888   \n",
       "7630                                 Watercolour on paper             1888   \n",
       "7730                            Ink and graphite on paper             1888   \n",
       "9492                              Wood engraving on paper             1924   \n",
       "14407                                Watercolour on paper             1905   \n",
       "14700                      Etching and engraving on paper             1925   \n",
       "12191               Ink, watercolour and gouache on paper             1946   \n",
       "69330                                Watercolour on paper             1888   \n",
       "69430                                        Ink on paper             1888   \n",
       "69530              Watercolour, ink and graphite on paper             1888   \n",
       "69630                           Ink and graphite on paper             1888   \n",
       "69730                   Watercolour and graphite on paper             1888   \n",
       "69830                   Watercolour and graphite on paper             1888   \n",
       "98171                              Oil paint on hardboard             2008   \n",
       "98537                   Graphite and oil paint on acetate             2008   \n",
       "97256          Photograph, gelatine silver print on paper             2009   \n",
       "97551   4 photographs, gelatine silver print on paper ...             2009   \n",
       "99037                                Screenprint on paper             2009   \n",
       "98345          Glass, fibreboard, wood, steel and plastic             2009   \n",
       "99125         Photograph, gelatine silver print on canvas             2009   \n",
       "99132                         Oil paint and felt on paper             2009   \n",
       "105706                                     Print on paper             2009   \n",
       "105826                                     Print on paper             2009   \n",
       "105944                                     Print on paper             2009   \n",
       "106055                                     Print on paper             2009   \n",
       "...                                                   ...              ...   \n",
       "24928                                   Graphite on paper             1997   \n",
       "25315   Ink and watercolour on paper. Verso: graphite ...             1997   \n",
       "25456                                    Etching on paper             1997   \n",
       "25801                      Engraving and etching on paper             1997   \n",
       "25254                                    Etching on paper             1997   \n",
       "25746                    Etching and watercolour on paper             1997   \n",
       "25392                                    Etching on paper             1997   \n",
       "25713                                    Etching on paper             1997   \n",
       "25933                                    Woodcut on paper             1997   \n",
       "80033            Relief, pencil, chalk, acrylic and paper             2004   \n",
       "80857                                 Oil paint on canvas             2004   \n",
       "84316   Film, 35 mm, shown as video, projection, colou...             2005   \n",
       "88228                                   Reduced stoneware             2005   \n",
       "88060                                 Marble and textiles             2006   \n",
       "81819                 Oil paint on canvas, wood and glass             2006   \n",
       "26747                                Watercolour on paper             2007   \n",
       "94662                             Printed papers on paper             2007   \n",
       "66602          Acrylic paint and silkscreen on 4 canvases             2008   \n",
       "99423                                   Graphite on paper             2008   \n",
       "100499  Lightboxes, steel shelving, acrylic sheet, flu...             2008   \n",
       "101563                              Performance, 2 people             2009   \n",
       "96968    Etching with paint, watercolour and ink on paper             2010   \n",
       "108923          Photograph, gelatin silver print on paper             2010   \n",
       "90120                                 Oil paint on canvas             2010   \n",
       "111919           Video, high definition, colour and sound             2011   \n",
       "118532                             Acrylic paint on paper             2012   \n",
       "117815                                  Graphite on paper             2012   \n",
       "117484      Steel, bitumen, latex, clay and cotton string             2012   \n",
       "89762                             Oil paint on fibreboard             2013   \n",
       "123531  6 photographs, cellulose print, black and whit...             2013   \n",
       "\n",
       "       height width  \n",
       "id                   \n",
       "1035      419   394  \n",
       "20230     154   136  \n",
       "6725                 \n",
       "7330                 \n",
       "7430                 \n",
       "7530                 \n",
       "7630                 \n",
       "7730                 \n",
       "9492      108   140  \n",
       "14407                \n",
       "14700     258   178  \n",
       "12191      92   111  \n",
       "69330                \n",
       "69430                \n",
       "69530                \n",
       "69630                \n",
       "69730                \n",
       "69830                \n",
       "98171     404   309  \n",
       "98537     474   391  \n",
       "97256     472   371  \n",
       "97551     540   695  \n",
       "99037     599   820  \n",
       "98345                \n",
       "99125    2275  2330  \n",
       "99132     434   647  \n",
       "105706    435   609  \n",
       "105826    162   273  \n",
       "105944    315   679  \n",
       "106055    565   808  \n",
       "...       ...   ...  \n",
       "24928     157   210  \n",
       "25315     149   160  \n",
       "25456     192   131  \n",
       "25801     247   170  \n",
       "25254      76    35  \n",
       "25746     255   183  \n",
       "25392     171   113  \n",
       "25713      66   106  \n",
       "25933     191   250  \n",
       "80033     630   478  \n",
       "80857     967   643  \n",
       "84316                \n",
       "88228      75    90  \n",
       "88060    3400  2120  \n",
       "81819     712   966  \n",
       "26747     235    80  \n",
       "94662                \n",
       "66602                \n",
       "99423                \n",
       "100499    900  5200  \n",
       "101563               \n",
       "96968     186   260  \n",
       "108923    304   404  \n",
       "90120    1880  1510  \n",
       "111919               \n",
       "118532    980   750  \n",
       "117815    181   260  \n",
       "117484    950  2430  \n",
       "89762    2450  2450  \n",
       "123531               \n",
       "\n",
       "[738 rows x 6 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import sys\n",
    "artworks = []\n",
    "for root,dirs,files in os.walk(artwork_root):\n",
    "    for f in files:\n",
    "        if f.endswith('json'):\n",
    "            try:\n",
    "                record = retrieveDataFromFile(os.path.join(root,f), cols_retrieve)\n",
    "                artworks.append(record)\n",
    "            except:\n",
    "                pass #some files don't have an acquisition date, so this is needed in order to prevent the program from crashing\n",
    "                \n",
    "        break; #uncomment this to only load first file\n",
    "df = pd.DataFrame.from_records(artworks,columns=cols_retrieve, index='id')\n",
    "df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id\n",
       "1035      False\n",
       "20230     False\n",
       "6725      False\n",
       "7330      False\n",
       "7430      False\n",
       "7530      False\n",
       "7630      False\n",
       "7730      False\n",
       "9492      False\n",
       "14407     False\n",
       "14700     False\n",
       "12191     False\n",
       "69330     False\n",
       "69430     False\n",
       "69530     False\n",
       "69630     False\n",
       "69730     False\n",
       "69830     False\n",
       "98171     False\n",
       "98537     False\n",
       "97256     False\n",
       "97551     False\n",
       "99037     False\n",
       "98345     False\n",
       "99125     False\n",
       "99132     False\n",
       "105706    False\n",
       "105826    False\n",
       "105944    False\n",
       "106055    False\n",
       "          ...  \n",
       "24928     False\n",
       "25315     False\n",
       "25456     False\n",
       "25801     False\n",
       "25254     False\n",
       "25746     False\n",
       "25392     False\n",
       "25713     False\n",
       "25933     False\n",
       "80033     False\n",
       "80857     False\n",
       "84316     False\n",
       "88228     False\n",
       "88060     False\n",
       "81819     False\n",
       "26747     False\n",
       "94662     False\n",
       "66602     False\n",
       "99423     False\n",
       "100499    False\n",
       "101563    False\n",
       "96968     False\n",
       "108923    False\n",
       "90120     False\n",
       "111919    False\n",
       "118532    False\n",
       "117815    False\n",
       "117484    False\n",
       "89762     False\n",
       "123531    False\n",
       "Name: all_artists, Length: 738, dtype: bool"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "artworks_by_Francis = df['all_artists'] == 'Francis Bacon' #Simple query to get all art pieces made by the given artist\n",
    "artworks_by_Francis #This Pandas method counts all truthy values, so 1s, true and any value considered truthy will be counted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Jiro Takamatsu 1\n"
     ]
    }
   ],
   "source": [
    "artworks_by_Francis = df['all_artists'].value_counts()\n",
    "print('Jiro Takamatsu',artworks_by_Francis['Jiro Takamatsu'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## loc\n",
    "\n",
    "This method allows you filter data using row and column indexers. The row indexers are the id values previously set, and the column indexers are the column names."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "all_artists                                             Robert Blake\n",
       "title              A Figure Bowing before a Seated Old Man with h...\n",
       "medium             Watercolour, ink, chalk and graphite on paper....\n",
       "acquisitionYear                                                 1922\n",
       "height                                                           419\n",
       "width                                                            394\n",
       "Name: 1035, dtype: object"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[1035,:]#Specific id. Colon in the column index is used to retrieve all columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>all_artists</th>\n",
       "      <th>title</th>\n",
       "      <th>medium</th>\n",
       "      <th>acquisitionYear</th>\n",
       "      <th>height</th>\n",
       "      <th>width</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>117815</th>\n",
       "      <td>Jiro Takamatsu</td>\n",
       "      <td>Shadow</td>\n",
       "      <td>Graphite on paper</td>\n",
       "      <td>2012</td>\n",
       "      <td>181</td>\n",
       "      <td>260</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           all_artists   title             medium  acquisitionYear height  \\\n",
       "id                                                                          \n",
       "117815  Jiro Takamatsu  Shadow  Graphite on paper             2012    181   \n",
       "\n",
       "       width  \n",
       "id            \n",
       "117815   260  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df['all_artists']=='Jiro Takamatsu',:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Queries may also be placed in the row field, yielding results similar to those of a SQL SELECT.\n",
    "\n",
    "## iloc\n",
    "\n",
    "iloc functions in a similar way to loc, but only allows the use of numbers as parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id\n",
       "34390                                    Graphite on paper\n",
       "34490                                    Graphite on paper\n",
       "34590                                                 None\n",
       "34689                                                 None\n",
       "34789                                 Pen and ink on paper\n",
       "34889                                                 None\n",
       "34989                                    Graphite on paper\n",
       "35089                                    Graphite on paper\n",
       "35189                                                 None\n",
       "35289                                    Graphite on paper\n",
       "35389                                    Graphite on paper\n",
       "35489                    Graphite and watercolour on paper\n",
       "35589                                    Graphite on paper\n",
       "35689                                    Graphite on paper\n",
       "35787                                 Pen and ink on paper\n",
       "35887                                    Graphite on paper\n",
       "35987                                 Pen and ink on paper\n",
       "36087                                   Engraving on paper\n",
       "36187                                    Graphite on paper\n",
       "36281                                                 None\n",
       "36379                                                 None\n",
       "36479                                                 None\n",
       "36579                                                 None\n",
       "36679                                    Graphite on paper\n",
       "36779                                    Graphite on paper\n",
       "36879                                    Graphite on paper\n",
       "36979                                    Graphite on paper\n",
       "37079                                    Graphite on paper\n",
       "37179                                    Graphite on paper\n",
       "37278                                    Graphite on paper\n",
       "                               ...                        \n",
       "51337                                    Graphite on paper\n",
       "51437                                    Graphite on paper\n",
       "51537                                    Graphite on paper\n",
       "51637                                    Graphite on paper\n",
       "51737                                    Graphite on paper\n",
       "51837                                    Graphite on paper\n",
       "51937                     Gouache and watercolour on paper\n",
       "52037                     Gouache and watercolour on paper\n",
       "52137    Watercolour, gouache and pen and watercolour o...\n",
       "52237                    Pen and ink and graphite on paper\n",
       "52337                                    Graphite on paper\n",
       "52437                                    Graphite on paper\n",
       "52537                                 Watercolour on paper\n",
       "52637                       Chalk and watercolour on paper\n",
       "52737                                 Watercolour on paper\n",
       "52837                                 Watercolour on paper\n",
       "52937                                    Graphite on paper\n",
       "53037                                    Graphite on paper\n",
       "53137                                    Graphite on paper\n",
       "53237                                                 None\n",
       "53337                                    Graphite on paper\n",
       "53437                                    Graphite on paper\n",
       "53537                                    Graphite on paper\n",
       "53637                                    Graphite on paper\n",
       "53737                                    Graphite on paper\n",
       "53837                                    Graphite on paper\n",
       "53937                                    Graphite on paper\n",
       "54037                                    Graphite on paper\n",
       "54137                                    Graphite on paper\n",
       "54236                                    Graphite on paper\n",
       "Name: medium, Length: 200, dtype: object"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[100:300,2] #The first parameter in this case uses the given range."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## max and idxmax\n",
    "\n",
    "max returns the maximum value of the given column, idxmax returns the identifier that belongs to such a record.\n",
    "Care should be practiced however, as data may not be entirely clean and could cause errors, such as with the following query."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "reduction operation 'argmax' not allowed for this dtype",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-29-0bf84df646b0>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'width'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0midxmax\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python37\\site-packages\\pandas\\core\\series.py\u001b[0m in \u001b[0;36midxmax\u001b[1;34m(self, axis, skipna, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1949\u001b[0m         \"\"\"\n\u001b[0;32m   1950\u001b[0m         \u001b[0mskipna\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnv\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalidate_argmax_with_skipna\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mskipna\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1951\u001b[1;33m         \u001b[0mi\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnanops\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnanargmax\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcom\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalues_from_object\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mskipna\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mskipna\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1952\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mi\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1953\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnan\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python37\\site-packages\\pandas\\core\\nanops.py\u001b[0m in \u001b[0;36m_f\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m     71\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0many\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcheck\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mobj\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mobj_iter\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     72\u001b[0m                 \u001b[0mmsg\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'reduction operation {name!r} not allowed for this dtype'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 73\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreplace\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'nan'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m''\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     74\u001b[0m             \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     75\u001b[0m                 \u001b[1;32mwith\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0merrstate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minvalid\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'ignore'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mTypeError\u001b[0m: reduction operation 'argmax' not allowed for this dtype"
     ]
    }
   ],
   "source": [
    "df['width'].idxmax()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This happens due to the fact that there's strings mixed up with numbers.\n",
    "A relatively simple way to fix this is using the coerce method.\n",
    "Here, you attempt to perform a transformation and, if an error happens, a neutral value of the target type will be inserted, as a substitute of the previous value.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id\n",
       "1035       394.0\n",
       "20230      136.0\n",
       "6725         NaN\n",
       "7330         NaN\n",
       "7430         NaN\n",
       "7530         NaN\n",
       "7630         NaN\n",
       "7730         NaN\n",
       "9492       140.0\n",
       "14407        NaN\n",
       "14700      178.0\n",
       "12191      111.0\n",
       "69330        NaN\n",
       "69430        NaN\n",
       "69530        NaN\n",
       "69630        NaN\n",
       "69730        NaN\n",
       "69830        NaN\n",
       "98171      309.0\n",
       "98537      391.0\n",
       "97256      371.0\n",
       "97551      695.0\n",
       "99037      820.0\n",
       "98345        NaN\n",
       "99125     2330.0\n",
       "99132      647.0\n",
       "105706     609.0\n",
       "105826     273.0\n",
       "105944     679.0\n",
       "106055     808.0\n",
       "           ...  \n",
       "24928      210.0\n",
       "25315      160.0\n",
       "25456      131.0\n",
       "25801      170.0\n",
       "25254       35.0\n",
       "25746      183.0\n",
       "25392      113.0\n",
       "25713      106.0\n",
       "25933      250.0\n",
       "80033      478.0\n",
       "80857      643.0\n",
       "84316        NaN\n",
       "88228       90.0\n",
       "88060     2120.0\n",
       "81819      966.0\n",
       "26747       80.0\n",
       "94662        NaN\n",
       "66602        NaN\n",
       "99423        NaN\n",
       "100499    5200.0\n",
       "101563       NaN\n",
       "96968      260.0\n",
       "108923     404.0\n",
       "90120     1510.0\n",
       "111919       NaN\n",
       "118532     750.0\n",
       "117815     260.0\n",
       "117484    2430.0\n",
       "89762     2450.0\n",
       "123531       NaN\n",
       "Name: width, Length: 738, dtype: float64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.to_numeric(df['width'], errors='coerce')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This corrects the values, but does not actually assign them.\n",
    "For that, we'll need to bring back the loc method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id\n",
       "1035         394\n",
       "20230        136\n",
       "6725      potato\n",
       "7330      potato\n",
       "7430      potato\n",
       "7530      potato\n",
       "7630      potato\n",
       "7730      potato\n",
       "9492         140\n",
       "14407     potato\n",
       "14700        178\n",
       "12191        111\n",
       "69330     potato\n",
       "69430     potato\n",
       "69530     potato\n",
       "69630     potato\n",
       "69730     potato\n",
       "69830     potato\n",
       "98171        309\n",
       "98537        391\n",
       "97256        371\n",
       "97551        695\n",
       "99037        820\n",
       "98345     potato\n",
       "99125       2330\n",
       "99132        647\n",
       "105706       609\n",
       "105826       273\n",
       "105944       679\n",
       "106055       808\n",
       "           ...  \n",
       "24928        210\n",
       "25315        160\n",
       "25456        131\n",
       "25801        170\n",
       "25254         35\n",
       "25746        183\n",
       "25392        113\n",
       "25713        106\n",
       "25933        250\n",
       "80033        478\n",
       "80857        643\n",
       "84316     potato\n",
       "88228         90\n",
       "88060       2120\n",
       "81819        966\n",
       "26747         80\n",
       "94662     potato\n",
       "66602     potato\n",
       "99423     potato\n",
       "100499      5200\n",
       "101563    potato\n",
       "96968        260\n",
       "108923       404\n",
       "90120       1510\n",
       "111919    potato\n",
       "118532       750\n",
       "117815       260\n",
       "117484      2430\n",
       "89762       2450\n",
       "123531    potato\n",
       "Name: width, Length: 738, dtype: object"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test = df.loc[:,'width'] = pd.to_numeric(df['width'],errors='coerse')\n",
    "test=test.fillna(\"potato\")\n",
    "test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, the values are now assigned and it's safe to use max and idxmax."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5200.0"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['width'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100499"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['width'].idxmax()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "group = df.groupby('all_artists')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "def changeNaN(series):\n",
    "    return series.fillna(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Transform\n",
    "\n",
    "This operation applies the given function to the provided data series.\n",
    "First parameter is the function while the second parameter indicates whether the function is applied per row or column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "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>title</th>\n",
       "      <th>medium</th>\n",
       "      <th>acquisitionYear</th>\n",
       "      <th>height</th>\n",
       "      <th>width</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1035</th>\n",
       "      <td>A Figure Bowing before a Seated Old Man with h...</td>\n",
       "      <td>Watercolour, ink, chalk and graphite on paper....</td>\n",
       "      <td>1922</td>\n",
       "      <td>419</td>\n",
       "      <td>394.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20230</th>\n",
       "      <td>Study of Heads for a Pietà</td>\n",
       "      <td>Graphite and chalk on paper</td>\n",
       "      <td>1927</td>\n",
       "      <td>154</td>\n",
       "      <td>136.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6725</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Graphite on paper</td>\n",
       "      <td>1922</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7330</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Ink on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7430</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Ink on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7530</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Ink on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7630</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Watercolour on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7730</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Ink and graphite on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9492</th>\n",
       "      <td>The Sower</td>\n",
       "      <td>Wood engraving on paper</td>\n",
       "      <td>1924</td>\n",
       "      <td>108</td>\n",
       "      <td>140.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14407</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Watercolour on paper</td>\n",
       "      <td>1905</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14700</th>\n",
       "      <td>Peat Bog, Scotland</td>\n",
       "      <td>Etching and engraving on paper</td>\n",
       "      <td>1925</td>\n",
       "      <td>258</td>\n",
       "      <td>178.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12191</th>\n",
       "      <td>The Mice at Work: Threading the Needle</td>\n",
       "      <td>Ink, watercolour and gouache on paper</td>\n",
       "      <td>1946</td>\n",
       "      <td>92</td>\n",
       "      <td>111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69330</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Watercolour on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69430</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Ink on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69530</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Watercolour, ink and graphite on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69630</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Ink and graphite on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69730</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Watercolour and graphite on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69830</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Watercolour and graphite on paper</td>\n",
       "      <td>1888</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98171</th>\n",
       "      <td>Pansies</td>\n",
       "      <td>Oil paint on hardboard</td>\n",
       "      <td>2008</td>\n",
       "      <td>404</td>\n",
       "      <td>309.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98537</th>\n",
       "      <td>Weird Sister</td>\n",
       "      <td>Graphite and oil paint on acetate</td>\n",
       "      <td>2008</td>\n",
       "      <td>474</td>\n",
       "      <td>391.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97256</th>\n",
       "      <td>Cock and Devil</td>\n",
       "      <td>Photograph, gelatine silver print on paper</td>\n",
       "      <td>2009</td>\n",
       "      <td>472</td>\n",
       "      <td>371.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97551</th>\n",
       "      <td>Male Nude</td>\n",
       "      <td>4 photographs, gelatine silver print on paper ...</td>\n",
       "      <td>2009</td>\n",
       "      <td>540</td>\n",
       "      <td>695.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99037</th>\n",
       "      <td>H.C. Andersen 1987</td>\n",
       "      <td>Screenprint on paper</td>\n",
       "      <td>2009</td>\n",
       "      <td>599</td>\n",
       "      <td>820.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98345</th>\n",
       "      <td>Trinity - Pharmacology, Physiology, Pathology</td>\n",
       "      <td>Glass, fibreboard, wood, steel and plastic</td>\n",
       "      <td>2009</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99125</th>\n",
       "      <td>Untitled</td>\n",
       "      <td>Photograph, gelatine silver print on canvas</td>\n",
       "      <td>2009</td>\n",
       "      <td>2275</td>\n",
       "      <td>2330.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99132</th>\n",
       "      <td>Felt Action</td>\n",
       "      <td>Oil paint and felt on paper</td>\n",
       "      <td>2009</td>\n",
       "      <td>434</td>\n",
       "      <td>647.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105706</th>\n",
       "      <td>Discussion, Documenta 6 Kassel</td>\n",
       "      <td>Print on paper</td>\n",
       "      <td>2009</td>\n",
       "      <td>435</td>\n",
       "      <td>609.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105826</th>\n",
       "      <td>‘Die zeit der politischen Parteien ist vorbei’</td>\n",
       "      <td>Print on paper</td>\n",
       "      <td>2009</td>\n",
       "      <td>162</td>\n",
       "      <td>273.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105944</th>\n",
       "      <td>Jahre Capital - Kunstkompass Galerie Denise René</td>\n",
       "      <td>Print on paper</td>\n",
       "      <td>2009</td>\n",
       "      <td>315</td>\n",
       "      <td>679.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106055</th>\n",
       "      <td>Joseph Beuys: A Private Collection. Stadthaus ...</td>\n",
       "      <td>Print on paper</td>\n",
       "      <td>2009</td>\n",
       "      <td>565</td>\n",
       "      <td>808.0</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>24928</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Graphite on paper</td>\n",
       "      <td>1997</td>\n",
       "      <td>157</td>\n",
       "      <td>210.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25315</th>\n",
       "      <td>[title not known] Verso: [title not known]</td>\n",
       "      <td>Ink and watercolour on paper. Verso: graphite ...</td>\n",
       "      <td>1997</td>\n",
       "      <td>149</td>\n",
       "      <td>160.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25456</th>\n",
       "      <td>The Fiery Serpents</td>\n",
       "      <td>Etching on paper</td>\n",
       "      <td>1997</td>\n",
       "      <td>192</td>\n",
       "      <td>131.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25801</th>\n",
       "      <td>Ulysses Giving Wine to Polyphemus</td>\n",
       "      <td>Engraving and etching on paper</td>\n",
       "      <td>1997</td>\n",
       "      <td>247</td>\n",
       "      <td>170.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25254</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Etching on paper</td>\n",
       "      <td>1997</td>\n",
       "      <td>76</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25746</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Etching and watercolour on paper</td>\n",
       "      <td>1997</td>\n",
       "      <td>255</td>\n",
       "      <td>183.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25392</th>\n",
       "      <td>Tan-y-Bwlch, Merionethshire, North Wales</td>\n",
       "      <td>Etching on paper</td>\n",
       "      <td>1997</td>\n",
       "      <td>171</td>\n",
       "      <td>113.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25713</th>\n",
       "      <td>Edward Young D.C.L.</td>\n",
       "      <td>Etching on paper</td>\n",
       "      <td>1997</td>\n",
       "      <td>66</td>\n",
       "      <td>106.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25933</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>Woodcut on paper</td>\n",
       "      <td>1997</td>\n",
       "      <td>191</td>\n",
       "      <td>250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80033</th>\n",
       "      <td>#73 Untitled</td>\n",
       "      <td>Relief, pencil, chalk, acrylic and paper</td>\n",
       "      <td>2004</td>\n",
       "      <td>630</td>\n",
       "      <td>478.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80857</th>\n",
       "      <td>French Coast with Fishermen</td>\n",
       "      <td>Oil paint on canvas</td>\n",
       "      <td>2004</td>\n",
       "      <td>967</td>\n",
       "      <td>643.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84316</th>\n",
       "      <td>Dictio pii</td>\n",
       "      <td>Film, 35 mm, shown as video, projection, colou...</td>\n",
       "      <td>2005</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88228</th>\n",
       "      <td>Yunomi</td>\n",
       "      <td>Reduced stoneware</td>\n",
       "      <td>2005</td>\n",
       "      <td>75</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88060</th>\n",
       "      <td>Venus of the Rags</td>\n",
       "      <td>Marble and textiles</td>\n",
       "      <td>2006</td>\n",
       "      <td>3400</td>\n",
       "      <td>2120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81819</th>\n",
       "      <td>Heygate Estate</td>\n",
       "      <td>Oil paint on canvas, wood and glass</td>\n",
       "      <td>2006</td>\n",
       "      <td>712</td>\n",
       "      <td>966.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26747</th>\n",
       "      <td>Untitled</td>\n",
       "      <td>Watercolour on paper</td>\n",
       "      <td>2007</td>\n",
       "      <td>235</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94662</th>\n",
       "      <td>Untitled</td>\n",
       "      <td>Printed papers on paper</td>\n",
       "      <td>2007</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66602</th>\n",
       "      <td>Brooke Hayward</td>\n",
       "      <td>Acrylic paint and silkscreen on 4 canvases</td>\n",
       "      <td>2008</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99423</th>\n",
       "      <td>The Interruption</td>\n",
       "      <td>Graphite on paper</td>\n",
       "      <td>2008</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100499</th>\n",
       "      <td>Spectrum of Brick Lane 2</td>\n",
       "      <td>Lightboxes, steel shelving, acrylic sheet, flu...</td>\n",
       "      <td>2008</td>\n",
       "      <td>900</td>\n",
       "      <td>5200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101563</th>\n",
       "      <td>A Life (Black and White)</td>\n",
       "      <td>Performance, 2 people</td>\n",
       "      <td>2009</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96968</th>\n",
       "      <td>The Book of Thel pl. 6</td>\n",
       "      <td>Etching with paint, watercolour and ink on paper</td>\n",
       "      <td>2010</td>\n",
       "      <td>186</td>\n",
       "      <td>260.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108923</th>\n",
       "      <td>Gardeners</td>\n",
       "      <td>Photograph, gelatin silver print on paper</td>\n",
       "      <td>2010</td>\n",
       "      <td>304</td>\n",
       "      <td>404.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90120</th>\n",
       "      <td>Stack</td>\n",
       "      <td>Oil paint on canvas</td>\n",
       "      <td>2010</td>\n",
       "      <td>1880</td>\n",
       "      <td>1510.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111919</th>\n",
       "      <td>Noreturn</td>\n",
       "      <td>Video, high definition, colour and sound</td>\n",
       "      <td>2011</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118532</th>\n",
       "      <td>Place</td>\n",
       "      <td>Acrylic paint on paper</td>\n",
       "      <td>2012</td>\n",
       "      <td>980</td>\n",
       "      <td>750.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117815</th>\n",
       "      <td>Shadow</td>\n",
       "      <td>Graphite on paper</td>\n",
       "      <td>2012</td>\n",
       "      <td>181</td>\n",
       "      <td>260.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117484</th>\n",
       "      <td>Flux III</td>\n",
       "      <td>Steel, bitumen, latex, clay and cotton string</td>\n",
       "      <td>2012</td>\n",
       "      <td>950</td>\n",
       "      <td>2430.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89762</th>\n",
       "      <td>Red Wall</td>\n",
       "      <td>Oil paint on fibreboard</td>\n",
       "      <td>2013</td>\n",
       "      <td>2450</td>\n",
       "      <td>2450.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123531</th>\n",
       "      <td>Welcome to Birdhead World Again</td>\n",
       "      <td>6 photographs, cellulose print, black and whit...</td>\n",
       "      <td>2013</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>738 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    title  \\\n",
       "id                                                          \n",
       "1035    A Figure Bowing before a Seated Old Man with h...   \n",
       "20230                          Study of Heads for a Pietà   \n",
       "6725                                    [title not known]   \n",
       "7330                                    [title not known]   \n",
       "7430                                    [title not known]   \n",
       "7530                                    [title not known]   \n",
       "7630                                    [title not known]   \n",
       "7730                                    [title not known]   \n",
       "9492                                            The Sower   \n",
       "14407                                   [title not known]   \n",
       "14700                                  Peat Bog, Scotland   \n",
       "12191              The Mice at Work: Threading the Needle   \n",
       "69330                                   [title not known]   \n",
       "69430                                   [title not known]   \n",
       "69530                                   [title not known]   \n",
       "69630                                   [title not known]   \n",
       "69730                                   [title not known]   \n",
       "69830                                   [title not known]   \n",
       "98171                                             Pansies   \n",
       "98537                                        Weird Sister   \n",
       "97256                                      Cock and Devil   \n",
       "97551                                           Male Nude   \n",
       "99037                                  H.C. Andersen 1987   \n",
       "98345       Trinity - Pharmacology, Physiology, Pathology   \n",
       "99125                                            Untitled   \n",
       "99132                                         Felt Action   \n",
       "105706                     Discussion, Documenta 6 Kassel   \n",
       "105826     ‘Die zeit der politischen Parteien ist vorbei’   \n",
       "105944   Jahre Capital - Kunstkompass Galerie Denise René   \n",
       "106055  Joseph Beuys: A Private Collection. Stadthaus ...   \n",
       "...                                                   ...   \n",
       "24928                                   [title not known]   \n",
       "25315          [title not known] Verso: [title not known]   \n",
       "25456                                  The Fiery Serpents   \n",
       "25801                   Ulysses Giving Wine to Polyphemus   \n",
       "25254                                   [title not known]   \n",
       "25746                                   [title not known]   \n",
       "25392            Tan-y-Bwlch, Merionethshire, North Wales   \n",
       "25713                                 Edward Young D.C.L.   \n",
       "25933                                   [title not known]   \n",
       "80033                                        #73 Untitled   \n",
       "80857                         French Coast with Fishermen   \n",
       "84316                                          Dictio pii   \n",
       "88228                                              Yunomi   \n",
       "88060                                   Venus of the Rags   \n",
       "81819                                      Heygate Estate   \n",
       "26747                                            Untitled   \n",
       "94662                                            Untitled   \n",
       "66602                                      Brooke Hayward   \n",
       "99423                                    The Interruption   \n",
       "100499                           Spectrum of Brick Lane 2   \n",
       "101563                           A Life (Black and White)   \n",
       "96968                              The Book of Thel pl. 6   \n",
       "108923                                          Gardeners   \n",
       "90120                                               Stack   \n",
       "111919                                           Noreturn   \n",
       "118532                                              Place   \n",
       "117815                                             Shadow   \n",
       "117484                                           Flux III   \n",
       "89762                                            Red Wall   \n",
       "123531                    Welcome to Birdhead World Again   \n",
       "\n",
       "                                                   medium  acquisitionYear  \\\n",
       "id                                                                           \n",
       "1035    Watercolour, ink, chalk and graphite on paper....             1922   \n",
       "20230                         Graphite and chalk on paper             1927   \n",
       "6725                                    Graphite on paper             1922   \n",
       "7330                                         Ink on paper             1888   \n",
       "7430                                         Ink on paper             1888   \n",
       "7530                                         Ink on paper             1888   \n",
       "7630                                 Watercolour on paper             1888   \n",
       "7730                            Ink and graphite on paper             1888   \n",
       "9492                              Wood engraving on paper             1924   \n",
       "14407                                Watercolour on paper             1905   \n",
       "14700                      Etching and engraving on paper             1925   \n",
       "12191               Ink, watercolour and gouache on paper             1946   \n",
       "69330                                Watercolour on paper             1888   \n",
       "69430                                        Ink on paper             1888   \n",
       "69530              Watercolour, ink and graphite on paper             1888   \n",
       "69630                           Ink and graphite on paper             1888   \n",
       "69730                   Watercolour and graphite on paper             1888   \n",
       "69830                   Watercolour and graphite on paper             1888   \n",
       "98171                              Oil paint on hardboard             2008   \n",
       "98537                   Graphite and oil paint on acetate             2008   \n",
       "97256          Photograph, gelatine silver print on paper             2009   \n",
       "97551   4 photographs, gelatine silver print on paper ...             2009   \n",
       "99037                                Screenprint on paper             2009   \n",
       "98345          Glass, fibreboard, wood, steel and plastic             2009   \n",
       "99125         Photograph, gelatine silver print on canvas             2009   \n",
       "99132                         Oil paint and felt on paper             2009   \n",
       "105706                                     Print on paper             2009   \n",
       "105826                                     Print on paper             2009   \n",
       "105944                                     Print on paper             2009   \n",
       "106055                                     Print on paper             2009   \n",
       "...                                                   ...              ...   \n",
       "24928                                   Graphite on paper             1997   \n",
       "25315   Ink and watercolour on paper. Verso: graphite ...             1997   \n",
       "25456                                    Etching on paper             1997   \n",
       "25801                      Engraving and etching on paper             1997   \n",
       "25254                                    Etching on paper             1997   \n",
       "25746                    Etching and watercolour on paper             1997   \n",
       "25392                                    Etching on paper             1997   \n",
       "25713                                    Etching on paper             1997   \n",
       "25933                                    Woodcut on paper             1997   \n",
       "80033            Relief, pencil, chalk, acrylic and paper             2004   \n",
       "80857                                 Oil paint on canvas             2004   \n",
       "84316   Film, 35 mm, shown as video, projection, colou...             2005   \n",
       "88228                                   Reduced stoneware             2005   \n",
       "88060                                 Marble and textiles             2006   \n",
       "81819                 Oil paint on canvas, wood and glass             2006   \n",
       "26747                                Watercolour on paper             2007   \n",
       "94662                             Printed papers on paper             2007   \n",
       "66602          Acrylic paint and silkscreen on 4 canvases             2008   \n",
       "99423                                   Graphite on paper             2008   \n",
       "100499  Lightboxes, steel shelving, acrylic sheet, flu...             2008   \n",
       "101563                              Performance, 2 people             2009   \n",
       "96968    Etching with paint, watercolour and ink on paper             2010   \n",
       "108923          Photograph, gelatin silver print on paper             2010   \n",
       "90120                                 Oil paint on canvas             2010   \n",
       "111919           Video, high definition, colour and sound             2011   \n",
       "118532                             Acrylic paint on paper             2012   \n",
       "117815                                  Graphite on paper             2012   \n",
       "117484      Steel, bitumen, latex, clay and cotton string             2012   \n",
       "89762                             Oil paint on fibreboard             2013   \n",
       "123531  6 photographs, cellulose print, black and whit...             2013   \n",
       "\n",
       "       height   width  \n",
       "id                     \n",
       "1035      419   394.0  \n",
       "20230     154   136.0  \n",
       "6725              0.0  \n",
       "7330              0.0  \n",
       "7430              0.0  \n",
       "7530              0.0  \n",
       "7630              0.0  \n",
       "7730              0.0  \n",
       "9492      108   140.0  \n",
       "14407             0.0  \n",
       "14700     258   178.0  \n",
       "12191      92   111.0  \n",
       "69330             0.0  \n",
       "69430             0.0  \n",
       "69530             0.0  \n",
       "69630             0.0  \n",
       "69730             0.0  \n",
       "69830             0.0  \n",
       "98171     404   309.0  \n",
       "98537     474   391.0  \n",
       "97256     472   371.0  \n",
       "97551     540   695.0  \n",
       "99037     599   820.0  \n",
       "98345             0.0  \n",
       "99125    2275  2330.0  \n",
       "99132     434   647.0  \n",
       "105706    435   609.0  \n",
       "105826    162   273.0  \n",
       "105944    315   679.0  \n",
       "106055    565   808.0  \n",
       "...       ...     ...  \n",
       "24928     157   210.0  \n",
       "25315     149   160.0  \n",
       "25456     192   131.0  \n",
       "25801     247   170.0  \n",
       "25254      76    35.0  \n",
       "25746     255   183.0  \n",
       "25392     171   113.0  \n",
       "25713      66   106.0  \n",
       "25933     191   250.0  \n",
       "80033     630   478.0  \n",
       "80857     967   643.0  \n",
       "84316             0.0  \n",
       "88228      75    90.0  \n",
       "88060    3400  2120.0  \n",
       "81819     712   966.0  \n",
       "26747     235    80.0  \n",
       "94662             0.0  \n",
       "66602             0.0  \n",
       "99423             0.0  \n",
       "100499    900  5200.0  \n",
       "101563            0.0  \n",
       "96968     186   260.0  \n",
       "108923    304   404.0  \n",
       "90120    1880  1510.0  \n",
       "111919            0.0  \n",
       "118532    980   750.0  \n",
       "117815    181   260.0  \n",
       "117484    950  2430.0  \n",
       "89762    2450  2450.0  \n",
       "123531            0.0  \n",
       "\n",
       "[738 rows x 5 columns]"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "group.transform(changeNaN)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When grouping, data is separated into two large groups: the grouped column first, and the rest of the selected data second.\n",
    "The names used for each group are irrelevant, you can choose whichever, but as usual it's best to choose meaningful names."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Abraham Cooper\n",
      "id\n",
      "25254    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Achilles Droungas\n",
      "id\n",
      "4007    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Adrian Stokes\n",
      "id\n",
      "6    2001\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Akram Zaatari\n",
      "id\n",
      "101045    2008\n",
      "101145    2008\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Alan Davie\n",
      "id\n",
      "20183    1991\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Albert Goodwin\n",
      "id\n",
      "5506    1901\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Albert Houthuesen\n",
      "id\n",
      "6865    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Alex Katz\n",
      "id\n",
      "98171    2008\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Alexander Cozens\n",
      "id\n",
      "22546    1996\n",
      "22508    1996\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Allen David\n",
      "id\n",
      "3632    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Ambrose McEvoy\n",
      "id\n",
      "9081    1926\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Andrew Wilson\n",
      "id\n",
      "23997    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Andy Warhol\n",
      "id\n",
      "97551    2009\n",
      "99037    2009\n",
      "66602    2008\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Anthony Gross\n",
      "id\n",
      "5698    1946\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Art & Language (Michael Baldwin, born 1945; Mel Ramsden, born 1944)\n",
      "id\n",
      "602    1983\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Arthur Boyd Houghton\n",
      "id\n",
      "6725    1922\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Barnett Freedman\n",
      "id\n",
      "67357    1976\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Barry Flanagan\n",
      "id\n",
      "4430    1985\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Ben Nicholson OM\n",
      "id\n",
      "10672    1976\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Benjamin West\n",
      "id\n",
      "16107    1974\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Berenice Abbott\n",
      "id\n",
      "107049    2010\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Bernard Cohen\n",
      "id\n",
      "2375    1965\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Bhupen Khakhar\n",
      "id\n",
      "21821    1996\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Birdhead (Ji Weiyu, born 1980; Song Tao, born 1979)\n",
      "id\n",
      "123531    2013\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Bob Law\n",
      "id\n",
      "81049    2004\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Brice Marden\n",
      "id\n",
      "20824    1993\n",
      "Name: acquisitionYear, dtype: int64\n",
      "British (?) School\n",
      "id\n",
      "24877    1997\n",
      "23354    1997\n",
      "25315    1997\n",
      "25713    1997\n",
      "25933    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "British School 16th century\n",
      "id\n",
      "1497    1961\n",
      "Name: acquisitionYear, dtype: int64\n",
      "British School 19th century\n",
      "id\n",
      "24125    1997\n",
      "24119    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Cecil Collins\n",
      "id\n",
      "2481    1979\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Charles Brooking\n",
      "id\n",
      "1572    1924\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Charles Cundall\n",
      "id\n",
      "2968    1933\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Charles Martin\n",
      "id\n",
      "24834    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Chris Ofili\n",
      "id\n",
      "27236    2000\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Christopher Le Brun PRA\n",
      "id\n",
      "19498    1991\n",
      "17336    1989\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Cindy Sherman\n",
      "id\n",
      "66660    2001\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Colin Self\n",
      "id\n",
      "21164    1994\n",
      "13305    1979\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Cornelius Johnson\n",
      "id\n",
      "7174    1910\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Craigie Horsfield\n",
      "id\n",
      "21398    1995\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Dame Barbara Hepworth\n",
      "id\n",
      "6034    1964\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Dame Elisabeth Frink\n",
      "id\n",
      "4565    1975\n",
      "4659    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Damien Hirst\n",
      "id\n",
      "98345    2009\n",
      "26837    1999\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Daniel Maclise\n",
      "id\n",
      "23189    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Dante Gabriel Rossetti\n",
      "id\n",
      "12770    1892\n",
      "Name: acquisitionYear, dtype: int64\n",
      "David Batchelor\n",
      "id\n",
      "100499    2008\n",
      "Name: acquisitionYear, dtype: int64\n",
      "David Bomberg, Richard Michelmore\n",
      "id\n",
      "1263    1983\n",
      "Name: acquisitionYear, dtype: int64\n",
      "David Muirhead\n",
      "id\n",
      "10382    1917\n",
      "Name: acquisitionYear, dtype: int64\n",
      "David Roberts\n",
      "id\n",
      "12646    1847\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Dee Villers\n",
      "id\n",
      "15748    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Diego Rivera\n",
      "id\n",
      "12613    1958\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Dieter Roth\n",
      "id\n",
      "12852    1979\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Dominique Gonzalez-Foerster\n",
      "id\n",
      "111919    2011\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Don McCullin\n",
      "id\n",
      "118161    2012\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Donald Judd\n",
      "id\n",
      "20223    1991\n",
      "Name: acquisitionYear, dtype: int64\n",
      "E.Q. Nicholson\n",
      "id\n",
      "18875    1989\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Ed Baynard\n",
      "id\n",
      "78819    2004\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Edward Bower\n",
      "id\n",
      "1373    1962\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Edward Lear\n",
      "id\n",
      "8475    1910\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Elizabeth Rigby (Lady Eastlake)\n",
      "id\n",
      "24597    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Ellsworth Kelly\n",
      "id\n",
      "66887    2013\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Eric Gill\n",
      "id\n",
      "5269    1979\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Evelyn Cheston\n",
      "id\n",
      "2188    1924\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Fernand Léger\n",
      "id\n",
      "20849    1994\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Frances Richards\n",
      "id\n",
      "12527    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Francis Barlow\n",
      "id\n",
      "729    1971\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Frank Auerbach\n",
      "id\n",
      "642      1976\n",
      "20658    1993\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Frank Huddlestone Potter\n",
      "id\n",
      "12172    1907\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Frank Roth\n",
      "id\n",
      "12872    1963\n",
      "Name: acquisitionYear, dtype: int64\n",
      "François Louis Thomas Francia\n",
      "id\n",
      "25746    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Fred Williams\n",
      "id\n",
      "21532    1996\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Frederick Lee Bridell\n",
      "id\n",
      "1486    1886\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Garrick Palmer\n",
      "id\n",
      "11037    1978\n",
      "Name: acquisitionYear, dtype: int64\n",
      "George Cattermole\n",
      "id\n",
      "2018    1879\n",
      "Name: acquisitionYear, dtype: int64\n",
      "George Chinnery\n",
      "id\n",
      "24367    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "George Jones\n",
      "id\n",
      "7330     1888\n",
      "7430     1888\n",
      "7530     1888\n",
      "7630     1888\n",
      "7730     1888\n",
      "69330    1888\n",
      "69430    1888\n",
      "69530    1888\n",
      "69630    1888\n",
      "69730    1888\n",
      "69830    1888\n",
      "7736     1869\n",
      "Name: acquisitionYear, dtype: int64\n",
      "George Price Boyce\n",
      "id\n",
      "1379    1939\n",
      "Name: acquisitionYear, dtype: int64\n",
      "George Romney\n",
      "id\n",
      "12738    1919\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Gerald Cooper\n",
      "id\n",
      "2781    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Gerd Winner\n",
      "id\n",
      "16277    1975\n",
      "67951    1980\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Gerhard Richter\n",
      "id\n",
      "20452    1992\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Gertrude Hermes\n",
      "id\n",
      "6122    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Gilbert Stuart\n",
      "id\n",
      "13973    1849\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Gordon House\n",
      "id\n",
      "6788     1975\n",
      "67394    1980\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Graham Sutherland OM\n",
      "id\n",
      "14056    1985\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Guerrilla Girls\n",
      "id\n",
      "81145    2004\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Günter Brus\n",
      "id\n",
      "1634    1983\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Hans Hartung\n",
      "id\n",
      "5861    1987\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Harry Kramer\n",
      "id\n",
      "8227    1971\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Helen Beatrix Potter\n",
      "id\n",
      "12191    1946\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Helen Frankenthaler\n",
      "id\n",
      "80967    2004\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Henri Gaudier-Brzeska\n",
      "id\n",
      "21603    1996\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Henry Edridge\n",
      "id\n",
      "4082    1927\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Henry Moore OM, CH\n",
      "id\n",
      "9664     1945\n",
      "9712     1975\n",
      "9810     1975\n",
      "9969     1982\n",
      "10067    1982\n",
      "10152    1986\n",
      "10221    1976\n",
      "10270    1978\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Henry Robert Morland\n",
      "id\n",
      "10301    1894\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Henry Tonks\n",
      "id\n",
      "14362    1931\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Henry William Bunbury\n",
      "id\n",
      "22342    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Howard Hodgkin\n",
      "id\n",
      "6550    1976\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Ivan Meštrovic\n",
      "id\n",
      "9460    1921\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Ivor Abrahams\n",
      "id\n",
      "320    1975\n",
      "328    1986\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Jack Bush\n",
      "id\n",
      "1864    1967\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Jacques Lipchitz\n",
      "id\n",
      "8904    1982\n",
      "Name: acquisitionYear, dtype: int64\n",
      "James Boswell\n",
      "id\n",
      "27012    2000\n",
      "Name: acquisitionYear, dtype: int64\n",
      "James Latham\n",
      "id\n",
      "8394    1947\n",
      "Name: acquisitionYear, dtype: int64\n",
      "James Smetham\n",
      "id\n",
      "13472    1898\n",
      "13477    1912\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Jasper Johns\n",
      "id\n",
      "26024    2005\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Jean Fautrier\n",
      "id\n",
      "22127    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Jean-Michel Atlan\n",
      "id\n",
      "618    1959\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Jenny Holzer\n",
      "id\n",
      "19062    1983\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Jiro Takamatsu\n",
      "id\n",
      "117815    2012\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Joan Miró\n",
      "id\n",
      "9582    1983\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Joe Tilson\n",
      "id\n",
      "14285    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Johannes Dörflinger\n",
      "id\n",
      "3983    1987\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John Constable\n",
      "id\n",
      "2630     1984\n",
      "22438    1996\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John Constable, David Lucas\n",
      "id\n",
      "2661    1985\n",
      "2761    1985\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John Flaxman\n",
      "id\n",
      "24292    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John Frederick Lewis\n",
      "id\n",
      "8675    1907\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John Hoppner\n",
      "id\n",
      "6705    1873\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John O'Connor\n",
      "id\n",
      "10905    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John Piper\n",
      "id\n",
      "11944    1983\n",
      "11997    1976\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John Robertson Reid\n",
      "id\n",
      "12347    1879\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John Scarlett Davis\n",
      "id\n",
      "24993    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John Sell Cotman\n",
      "id\n",
      "25392    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John Singer Sargent\n",
      "id\n",
      "13143    1949\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John Singleton Copley\n",
      "id\n",
      "2786    1830\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John Skeaping\n",
      "id\n",
      "13451    1945\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John Varley\n",
      "id\n",
      "23926    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John Walker\n",
      "id\n",
      "15859    1979\n",
      "15878    1981\n",
      "15885    1988\n",
      "80771    2004\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John Ward\n",
      "id\n",
      "26112    1998\n",
      "Name: acquisitionYear, dtype: int64\n",
      "John `Warwick' Smith\n",
      "id\n",
      "23566    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Josef Herman\n",
      "id\n",
      "6119    1981\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Joseph Beuys\n",
      "id\n",
      "98537     2008\n",
      "99125     2009\n",
      "99132     2009\n",
      "105706    2009\n",
      "105826    2009\n",
      "105944    2009\n",
      "106055    2009\n",
      "957       1982\n",
      "959       1977\n",
      "22187     1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Joseph Highmore\n",
      "id\n",
      "6247    1986\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Joseph Mallord William Turner\n",
      "id\n",
      "14700    1925\n",
      "27417    1856\n",
      "27516    1856\n",
      "27616    1856\n",
      "27716    1856\n",
      "27815    1856\n",
      "27915    1856\n",
      "28016    1856\n",
      "28115    1856\n",
      "28213    1856\n",
      "28312    1856\n",
      "28411    1856\n",
      "28511    1856\n",
      "28609    1856\n",
      "28707    1856\n",
      "28807    1856\n",
      "28906    1856\n",
      "29006    1856\n",
      "29105    1856\n",
      "29205    1856\n",
      "29304    1856\n",
      "29403    1856\n",
      "29503    1856\n",
      "29603    1856\n",
      "29703    1856\n",
      "29803    1856\n",
      "29903    1856\n",
      "30003    1856\n",
      "30103    1856\n",
      "30203    1856\n",
      "         ... \n",
      "62710    1856\n",
      "62806    1856\n",
      "62890    1856\n",
      "62988    1856\n",
      "63088    1856\n",
      "63188    1856\n",
      "63287    1856\n",
      "63385    1856\n",
      "63771    1856\n",
      "63868    1856\n",
      "63964    1856\n",
      "64061    1856\n",
      "64157    1856\n",
      "64250    1856\n",
      "64349    1856\n",
      "64447    1856\n",
      "64547    1856\n",
      "64647    1856\n",
      "64746    1856\n",
      "64846    1856\n",
      "64898    1856\n",
      "64998    1856\n",
      "65098    1856\n",
      "66780    1856\n",
      "14759    1856\n",
      "14837    1856\n",
      "14875    1856\n",
      "14900    1856\n",
      "14958    1856\n",
      "20267    1991\n",
      "Name: acquisitionYear, Length: 387, dtype: int64\n",
      "Joseph Mallord William Turner, Thomas Girtin\n",
      "id\n",
      "63585    1856\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Joseph Van Aken\n",
      "id\n",
      "15689    1930\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Joshua Cristall\n",
      "id\n",
      "24641    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Julia Emily Gordon\n",
      "id\n",
      "22946    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Julio González\n",
      "id\n",
      "5446    1972\n",
      "5457    1972\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Karl Weschke\n",
      "id\n",
      "21193    1994\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Keith Arnatt\n",
      "id\n",
      "108923    2010\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Keith Coventry\n",
      "id\n",
      "81819    2006\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Keith Vaughan\n",
      "id\n",
      "15716    1955\n",
      "15721    1983\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Kenneth Martin\n",
      "id\n",
      "9340    1972\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Lady Susan Elizabeth Percy\n",
      "id\n",
      "23360    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Lady Wharncliffe (née Lady Caroline Mary Elizabeth Creighton)\n",
      "id\n",
      "24928    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Larry Rivers\n",
      "id\n",
      "12635    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Leon Kossoff\n",
      "id\n",
      "27190    1999\n",
      "95350    2008\n",
      "Name: acquisitionYear, dtype: int64\n",
      "León Ferrari\n",
      "id\n",
      "96224    2009\n",
      "96997    2009\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Linder\n",
      "id\n",
      "94662    2007\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Lionel Wendt\n",
      "id\n",
      "125434    2013\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Lord William Pitt Lennox\n",
      "id\n",
      "23157    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Lucian Freud\n",
      "id\n",
      "20590    1992\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Lucien Pissarro\n",
      "id\n",
      "12090    1924\n",
      "12110    1982\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Markus Raetz\n",
      "id\n",
      "12283    1987\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Markus Schinwald\n",
      "id\n",
      "84316    2005\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Martin Kippenberger\n",
      "id\n",
      "83192    2005\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Menashe Kadishman\n",
      "id\n",
      "7788    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Michael Rothenstein\n",
      "id\n",
      "12894    1977\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Michelangelo Pistoletto\n",
      "id\n",
      "88060    2006\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Minoru Hirata\n",
      "id\n",
      "120480    2012\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Naum Gabo\n",
      "id\n",
      "4796    1967\n",
      "4869    1977\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Nedko Solakov\n",
      "id\n",
      "101563    2009\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Neville Gabie\n",
      "id\n",
      "27381    2001\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Nicholas Monro\n",
      "id\n",
      "9630    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Norman Stevens\n",
      "id\n",
      "13877    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Oskar Kokoschka\n",
      "id\n",
      "67795    1984\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Patrick Caulfield\n",
      "id\n",
      "2046     1975\n",
      "2075     1979\n",
      "88850    2006\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Patrick Heron\n",
      "id\n",
      "6161     1975\n",
      "26548    1999\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Per Inge Bjørlo\n",
      "id\n",
      "79840    2004\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Peter Blake\n",
      "id\n",
      "71536    2002\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Peter Phillips\n",
      "id\n",
      "11552    1977\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Phil Collins\n",
      "id\n",
      "76399    2003\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Philip Guston\n",
      "id\n",
      "21709    1996\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Philip James De Loutherbourg\n",
      "id\n",
      "63485    1856\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Philip Wilson Steer\n",
      "id\n",
      "13781    1922\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Prince Hoare\n",
      "id\n",
      "24430    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Prunella Clough\n",
      "id\n",
      "90120    2010\n",
      "Name: acquisitionYear, dtype: int64\n",
      "R.B. Kitaj\n",
      "id\n",
      "8059    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Raoul Dufy\n",
      "id\n",
      "17286    1988\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Reuben Townroe\n",
      "id\n",
      "14407    1905\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Rev. John Thomson of Duddingston\n",
      "id\n",
      "14162    1864\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Richard Deacon\n",
      "id\n",
      "22026    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Richard Garbe\n",
      "id\n",
      "4966    1925\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Richard Hamilton\n",
      "id\n",
      "105292    2009\n",
      "117159    2012\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Richard Parkes Bonington\n",
      "id\n",
      "1303     1961\n",
      "80857    2004\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Richard Smith\n",
      "id\n",
      "13554    1975\n",
      "13595    1980\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Richard Wilson\n",
      "id\n",
      "16225    1847\n",
      "24001    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Robert Adams\n",
      "id\n",
      "436    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Robert Austin\n",
      "id\n",
      "651    1926\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Robert Blake\n",
      "id\n",
      "1035    1922\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Robert Braithwaite Martineau\n",
      "id\n",
      "9352    1896\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Robert Mangold\n",
      "id\n",
      "89762    2013\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Robert Mapplethorpe\n",
      "id\n",
      "97256    2009\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Robert Motherwell\n",
      "id\n",
      "80142    2004\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Robyn Denny\n",
      "id\n",
      "3765    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Roland Piché\n",
      "id\n",
      "11877    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Rufino Tamayo\n",
      "id\n",
      "14115    1976\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Samuel Palmer\n",
      "id\n",
      "11044    1917\n",
      "11048    1922\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sarah Lucas\n",
      "id\n",
      "26300    1998\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sarah Morris\n",
      "id\n",
      "69942    2002\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Shelagh Cluett\n",
      "id\n",
      "117484    2012\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Shikanosuke Yagaki\n",
      "id\n",
      "112418    2011\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Shoji Hamada\n",
      "id\n",
      "88228    2005\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sir Anthony Caro\n",
      "id\n",
      "80033    2004\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sir Eduardo Paolozzi\n",
      "id\n",
      "11234    1975\n",
      "11330    1980\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sir Edward Coley Burne-Jones, Bt\n",
      "id\n",
      "20230    1927\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sir James Thornhill\n",
      "id\n",
      "14163    1953\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sir John Everett Millais, Bt\n",
      "id\n",
      "9492    1924\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sir John Lavery\n",
      "id\n",
      "8412    1914\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sir Joshua Reynolds\n",
      "id\n",
      "12387    1837\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sir Muirhead Bone\n",
      "id\n",
      "1264    1908\n",
      "1284    1909\n",
      "1233    1918\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sir Nathaniel Dance-Holland\n",
      "id\n",
      "24186    1996\n",
      "22727    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sir Peter Lely\n",
      "id\n",
      "8589    1876\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sir Roland Penrose\n",
      "id\n",
      "11516    1982\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sir Sidney Nolan\n",
      "id\n",
      "10832    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sir Stanley Spencer\n",
      "id\n",
      "13678    1935\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sir William Boxall\n",
      "id\n",
      "1378    1858\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sir William Orpen\n",
      "id\n",
      "10982    1928\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sir William Quiller Orchardson\n",
      "id\n",
      "10960    1947\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sol LeWitt\n",
      "id\n",
      "8765    1980\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Sophie Calle\n",
      "id\n",
      "26559    1999\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Spencer Gore\n",
      "id\n",
      "5521    1940\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Stan Douglas\n",
      "id\n",
      "116    2001\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Steven Pippin\n",
      "id\n",
      "21818    1996\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Steven Sorman\n",
      "id\n",
      "80590    2004\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Susanna Duncombe (née Susanna Highmore)\n",
      "id\n",
      "6347    1986\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Terry Winters\n",
      "id\n",
      "21363    2002\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Thomas Barker of Bath\n",
      "id\n",
      "724    1890\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Thomas Gainsborough\n",
      "id\n",
      "4914    1910\n",
      "4925    1943\n",
      "4957    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Thomas Girtin\n",
      "id\n",
      "63685    1856\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Thomas Hearne\n",
      "id\n",
      "5932    1967\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Thomas Rowlandson\n",
      "id\n",
      "23477    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Thomas Schütte\n",
      "id\n",
      "83700    2003\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Thomas Sidney Cooper\n",
      "id\n",
      "2784    1900\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Thomas Stothard\n",
      "id\n",
      "23668    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Tom Phillips\n",
      "id\n",
      "11578    1975\n",
      "11747    1982\n",
      "11790    1982\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Tracey Moffatt\n",
      "id\n",
      "26285    1998\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Trevor Bell\n",
      "id\n",
      "118532    2012\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Victor Pasmore\n",
      "id\n",
      "11413    1975\n",
      "Name: acquisitionYear, dtype: int64\n",
      "William Blake\n",
      "id\n",
      "1086     1882\n",
      "1138     1940\n",
      "1139     1941\n",
      "96968    2010\n",
      "Name: acquisitionYear, dtype: int64\n",
      "William Daniell\n",
      "id\n",
      "3096    1979\n",
      "3195    1979\n",
      "3295    1979\n",
      "3395    1979\n",
      "3495    1979\n",
      "3595    1979\n",
      "Name: acquisitionYear, dtype: int64\n",
      "William G. Simmonds\n",
      "id\n",
      "13431    1937\n",
      "Name: acquisitionYear, dtype: int64\n",
      "William Henry Brooke\n",
      "id\n",
      "1569    1981\n",
      "Name: acquisitionYear, dtype: int64\n",
      "William Henry Hunt\n",
      "id\n",
      "24746    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "William Hogarth\n",
      "id\n",
      "6634    1973\n",
      "Name: acquisitionYear, dtype: int64\n",
      "William Roberts\n",
      "id\n",
      "12666    1968\n",
      "99423    2008\n",
      "Name: acquisitionYear, dtype: int64\n",
      "William Tucker\n",
      "id\n",
      "14516    1970\n",
      "Name: acquisitionYear, dtype: int64\n",
      "William Turnbull\n",
      "id\n",
      "19191    1990\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Wolfgang Tillmans\n",
      "id\n",
      "85267    2007\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Name: acquisitionYear, dtype: int64\n",
      "Wyndham Lewis\n",
      "id\n",
      "8701    1956\n",
      "Name: acquisitionYear, dtype: int64\n",
      "Yves Tanguy\n",
      "id\n",
      "26747    2007\n",
      "Name: acquisitionYear, dtype: int64\n",
      "after Edward Dayes\n",
      "id\n",
      "19578    1988\n",
      "Name: acquisitionYear, dtype: int64\n",
      "after John Flaxman\n",
      "id\n",
      "25456    1997\n",
      "25801    1997\n",
      "Name: acquisitionYear, dtype: int64\n",
      "after Joseph Mallord William Turner\n",
      "id\n",
      "15069    1986\n",
      "15169    1986\n",
      "15269    1986\n",
      "15369    1986\n",
      "15469    1986\n",
      "16664    1988\n",
      "16764    1988\n",
      "17177    1988\n",
      "18848    1989\n",
      "19632    1988\n",
      "19728    1988\n",
      "19828    1988\n",
      "19928    1988\n",
      "20028    1988\n",
      "Name: acquisitionYear, dtype: int64\n",
      "after Peter De Wint\n",
      "id\n",
      "17077    1988\n",
      "Name: acquisitionYear, dtype: int64\n",
      "attributed to Benjamin Ralph\n",
      "id\n",
      "23406    1997\n",
      "Name: acquisitionYear, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "for artist, remainder in group:\n",
    "    print(artist)\n",
    "    print(remainder['acquisitionYear'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Aggregate\n",
    "\n",
    "This method receives a parameter that indicates how the series should be aggregated. The operation is performed for every column except the one that was used as the grouping column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "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>title</th>\n",
       "      <th>acquisitionYear</th>\n",
       "      <th>height</th>\n",
       "      <th>width</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>all_artists</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Abraham Cooper</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>1997</td>\n",
       "      <td>76</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Achilles Droungas</th>\n",
       "      <td>A Fig, a Plumb, a Quince, an Apple, a Pear</td>\n",
       "      <td>1975</td>\n",
       "      <td>698</td>\n",
       "      <td>524.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adrian Stokes</th>\n",
       "      <td>Landscape, Blasted Tree</td>\n",
       "      <td>2001</td>\n",
       "      <td>510</td>\n",
       "      <td>685.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Akram Zaatari</th>\n",
       "      <td>A girl and her brother. Studio Shehrazade, Sai...</td>\n",
       "      <td>2008</td>\n",
       "      <td>289</td>\n",
       "      <td>290.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alan Davie</th>\n",
       "      <td>Two Insects, Yellow</td>\n",
       "      <td>1991</td>\n",
       "      <td>176</td>\n",
       "      <td>308.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albert Goodwin</th>\n",
       "      <td>Ali Baba and the Forty Thieves</td>\n",
       "      <td>1901</td>\n",
       "      <td>1420</td>\n",
       "      <td>1075.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albert Houthuesen</th>\n",
       "      <td>5. Muse and Clown</td>\n",
       "      <td>1975</td>\n",
       "      <td>632</td>\n",
       "      <td>491.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alex Katz</th>\n",
       "      <td>Pansies</td>\n",
       "      <td>2008</td>\n",
       "      <td>404</td>\n",
       "      <td>309.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alexander Cozens</th>\n",
       "      <td>Landscape with Castle</td>\n",
       "      <td>1996</td>\n",
       "      <td>142</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Allen David</th>\n",
       "      <td>Red Fountain II</td>\n",
       "      <td>1975</td>\n",
       "      <td>464</td>\n",
       "      <td>610.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ambrose McEvoy</th>\n",
       "      <td>Mrs Claude Johnson</td>\n",
       "      <td>1926</td>\n",
       "      <td>768</td>\n",
       "      <td>1016.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andrew Wilson</th>\n",
       "      <td>Composition: A Town by a Lake</td>\n",
       "      <td>1997</td>\n",
       "      <td>287</td>\n",
       "      <td>213.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andy Warhol</th>\n",
       "      <td>Brooke Hayward</td>\n",
       "      <td>2008</td>\n",
       "      <td></td>\n",
       "      <td>695.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anthony Gross</th>\n",
       "      <td>Gateway into Germany: The Maas in Flood near t...</td>\n",
       "      <td>1946</td>\n",
       "      <td>591</td>\n",
       "      <td>413.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Art &amp; Language (Michael Baldwin, born 1945; Mel Ramsden, born 1944)</th>\n",
       "      <td>Index: The Studio at 3 Wesley Place, in the Da...</td>\n",
       "      <td>1983</td>\n",
       "      <td>1680</td>\n",
       "      <td>797.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arthur Boyd Houghton</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>1922</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Barnett Freedman</th>\n",
       "      <td>Untitled</td>\n",
       "      <td>1976</td>\n",
       "      <td>591</td>\n",
       "      <td>952.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Barry Flanagan</th>\n",
       "      <td>Herring Drifter at Fort Augustus Swing Bridge ...</td>\n",
       "      <td>1985</td>\n",
       "      <td>180</td>\n",
       "      <td>127.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ben Nicholson OM</th>\n",
       "      <td>Foxy and Frankie (2)</td>\n",
       "      <td>1976</td>\n",
       "      <td>149</td>\n",
       "      <td>159.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Benjamin West</th>\n",
       "      <td>The Bard</td>\n",
       "      <td>1974</td>\n",
       "      <td>229</td>\n",
       "      <td>292.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Berenice Abbott</th>\n",
       "      <td>Tri-Boro Barber Shop</td>\n",
       "      <td>2010</td>\n",
       "      <td>200</td>\n",
       "      <td>250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bernard Cohen</th>\n",
       "      <td>In That Moment</td>\n",
       "      <td>1965</td>\n",
       "      <td>2438</td>\n",
       "      <td>2438.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bhupen Khakhar</th>\n",
       "      <td>You Can’t Please All</td>\n",
       "      <td>1996</td>\n",
       "      <td>1756</td>\n",
       "      <td>1756.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Birdhead (Ji Weiyu, born 1980; Song Tao, born 1979)</th>\n",
       "      <td>Welcome to Birdhead World Again</td>\n",
       "      <td>2013</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bob Law</th>\n",
       "      <td>Double Cross</td>\n",
       "      <td>2004</td>\n",
       "      <td>385</td>\n",
       "      <td>285.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brice Marden</th>\n",
       "      <td>[no title]</td>\n",
       "      <td>1993</td>\n",
       "      <td>525</td>\n",
       "      <td>398.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>British (?) School</th>\n",
       "      <td>Edward Young D.C.L.</td>\n",
       "      <td>1997</td>\n",
       "      <td>127</td>\n",
       "      <td>67.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>British School 16th century</th>\n",
       "      <td>A Young Lady Aged 21, Possibly Helena Snakenbo...</td>\n",
       "      <td>1961</td>\n",
       "      <td>483</td>\n",
       "      <td>629.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>British School 19th century</th>\n",
       "      <td>Jane Shore Doing Penance through the Streets o...</td>\n",
       "      <td>1997</td>\n",
       "      <td>289</td>\n",
       "      <td>404.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cecil Collins</th>\n",
       "      <td>The Pilgrim</td>\n",
       "      <td>1979</td>\n",
       "      <td>127</td>\n",
       "      <td>171.0</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>Terry Winters</th>\n",
       "      <td>[no title]</td>\n",
       "      <td>2002</td>\n",
       "      <td>100</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas Barker of Bath</th>\n",
       "      <td>Landscape with Figures and Sheep</td>\n",
       "      <td>1890</td>\n",
       "      <td>1130</td>\n",
       "      <td>813.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas Gainsborough</th>\n",
       "      <td>Figure Study for ‘The Housemaid’</td>\n",
       "      <td>1910</td>\n",
       "      <td>1486</td>\n",
       "      <td>346.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas Girtin</th>\n",
       "      <td>Much Wenlock Priory, Shropshire</td>\n",
       "      <td>1856</td>\n",
       "      <td>215</td>\n",
       "      <td>156.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas Hearne</th>\n",
       "      <td>Appleby</td>\n",
       "      <td>1967</td>\n",
       "      <td>403</td>\n",
       "      <td>302.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas Rowlandson</th>\n",
       "      <td>Under an Arrest</td>\n",
       "      <td>1997</td>\n",
       "      <td>195</td>\n",
       "      <td>123.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas Schütte</th>\n",
       "      <td>[no title]</td>\n",
       "      <td>2003</td>\n",
       "      <td>320</td>\n",
       "      <td>447.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas Sidney Cooper</th>\n",
       "      <td>Landscape and Cattle</td>\n",
       "      <td>1900</td>\n",
       "      <td>406</td>\n",
       "      <td>292.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas Stothard</th>\n",
       "      <td>Sketch for ‘Robinson Crusoe’: Two Men Conversi...</td>\n",
       "      <td>1997</td>\n",
       "      <td>90</td>\n",
       "      <td>116.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tom Phillips</th>\n",
       "      <td>Canto XVIII: [no title]</td>\n",
       "      <td>1975</td>\n",
       "      <td>140</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tracey Moffatt</th>\n",
       "      <td>The Wizard of Oz, 1956</td>\n",
       "      <td>1998</td>\n",
       "      <td>600</td>\n",
       "      <td>800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trevor Bell</th>\n",
       "      <td>Place</td>\n",
       "      <td>2012</td>\n",
       "      <td>980</td>\n",
       "      <td>750.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Victor Pasmore</th>\n",
       "      <td>Linear Development 1</td>\n",
       "      <td>1975</td>\n",
       "      <td>420</td>\n",
       "      <td>420.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Blake</th>\n",
       "      <td>Job, his Wife and his Friends: The Complaint o...</td>\n",
       "      <td>1882</td>\n",
       "      <td>186</td>\n",
       "      <td>260.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Daniell</th>\n",
       "      <td>Bovisand, near Plymouth</td>\n",
       "      <td>1979</td>\n",
       "      <td>241</td>\n",
       "      <td>162.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William G. Simmonds</th>\n",
       "      <td>Old Horse</td>\n",
       "      <td>1937</td>\n",
       "      <td>570</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Henry Brooke</th>\n",
       "      <td>Lanherne Bay near the Nunnery, Cornwall</td>\n",
       "      <td>1981</td>\n",
       "      <td>190</td>\n",
       "      <td>146.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Henry Hunt</th>\n",
       "      <td>[title not known]</td>\n",
       "      <td>1997</td>\n",
       "      <td>91</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Hogarth</th>\n",
       "      <td>The Enraged Musician</td>\n",
       "      <td>1973</td>\n",
       "      <td>405</td>\n",
       "      <td>332.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Roberts</th>\n",
       "      <td>Study for ‘Two Step’</td>\n",
       "      <td>1968</td>\n",
       "      <td></td>\n",
       "      <td>298.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Tucker</th>\n",
       "      <td>Anabasis I</td>\n",
       "      <td>1970</td>\n",
       "      <td>1099</td>\n",
       "      <td>1492.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Turnbull</th>\n",
       "      <td>Head</td>\n",
       "      <td>1990</td>\n",
       "      <td>1016</td>\n",
       "      <td>1270.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wolfgang Tillmans</th>\n",
       "      <td>The Bell</td>\n",
       "      <td>2007</td>\n",
       "      <td>1450</td>\n",
       "      <td>2100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wyndham Lewis</th>\n",
       "      <td>Mrs Schiff</td>\n",
       "      <td>1956</td>\n",
       "      <td>1003</td>\n",
       "      <td>1257.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yves Tanguy</th>\n",
       "      <td>Untitled</td>\n",
       "      <td>2007</td>\n",
       "      <td>235</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>after Edward Dayes</th>\n",
       "      <td>The Peak Cavern, Derbyshire: View from the Int...</td>\n",
       "      <td>1988</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>after John Flaxman</th>\n",
       "      <td>The Fiery Serpents</td>\n",
       "      <td>1997</td>\n",
       "      <td>192</td>\n",
       "      <td>131.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>after Joseph Mallord William Turner</th>\n",
       "      <td>Bass Rock</td>\n",
       "      <td>1986</td>\n",
       "      <td></td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>after Peter De Wint</th>\n",
       "      <td>Bognor</td>\n",
       "      <td>1988</td>\n",
       "      <td>115</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>attributed to Benjamin Ralph</th>\n",
       "      <td>Norwich Castle</td>\n",
       "      <td>1997</td>\n",
       "      <td>187</td>\n",
       "      <td>149.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>256 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                                title  \\\n",
       "all_artists                                                                                             \n",
       "Abraham Cooper                                                                      [title not known]   \n",
       "Achilles Droungas                                          A Fig, a Plumb, a Quince, an Apple, a Pear   \n",
       "Adrian Stokes                                                                 Landscape, Blasted Tree   \n",
       "Akram Zaatari                                       A girl and her brother. Studio Shehrazade, Sai...   \n",
       "Alan Davie                                                                        Two Insects, Yellow   \n",
       "Albert Goodwin                                                         Ali Baba and the Forty Thieves   \n",
       "Albert Houthuesen                                                                   5. Muse and Clown   \n",
       "Alex Katz                                                                                     Pansies   \n",
       "Alexander Cozens                                                                Landscape with Castle   \n",
       "Allen David                                                                           Red Fountain II   \n",
       "Ambrose McEvoy                                                                     Mrs Claude Johnson   \n",
       "Andrew Wilson                                                           Composition: A Town by a Lake   \n",
       "Andy Warhol                                                                            Brooke Hayward   \n",
       "Anthony Gross                                       Gateway into Germany: The Maas in Flood near t...   \n",
       "Art & Language (Michael Baldwin, born 1945; Mel...  Index: The Studio at 3 Wesley Place, in the Da...   \n",
       "Arthur Boyd Houghton                                                                [title not known]   \n",
       "Barnett Freedman                                                                             Untitled   \n",
       "Barry Flanagan                                      Herring Drifter at Fort Augustus Swing Bridge ...   \n",
       "Ben Nicholson OM                                                                 Foxy and Frankie (2)   \n",
       "Benjamin West                                                                                The Bard   \n",
       "Berenice Abbott                                                                  Tri-Boro Barber Shop   \n",
       "Bernard Cohen                                                                          In That Moment   \n",
       "Bhupen Khakhar                                                                   You Can’t Please All   \n",
       "Birdhead (Ji Weiyu, born 1980; Song Tao, born 1...                    Welcome to Birdhead World Again   \n",
       "Bob Law                                                                                  Double Cross   \n",
       "Brice Marden                                                                               [no title]   \n",
       "British (?) School                                                                Edward Young D.C.L.   \n",
       "British School 16th century                         A Young Lady Aged 21, Possibly Helena Snakenbo...   \n",
       "British School 19th century                         Jane Shore Doing Penance through the Streets o...   \n",
       "Cecil Collins                                                                             The Pilgrim   \n",
       "...                                                                                               ...   \n",
       "Terry Winters                                                                              [no title]   \n",
       "Thomas Barker of Bath                                                Landscape with Figures and Sheep   \n",
       "Thomas Gainsborough                                                  Figure Study for ‘The Housemaid’   \n",
       "Thomas Girtin                                                         Much Wenlock Priory, Shropshire   \n",
       "Thomas Hearne                                                                                 Appleby   \n",
       "Thomas Rowlandson                                                                     Under an Arrest   \n",
       "Thomas Schütte                                                                             [no title]   \n",
       "Thomas Sidney Cooper                                                             Landscape and Cattle   \n",
       "Thomas Stothard                                     Sketch for ‘Robinson Crusoe’: Two Men Conversi...   \n",
       "Tom Phillips                                                                  Canto XVIII: [no title]   \n",
       "Tracey Moffatt                                                                 The Wizard of Oz, 1956   \n",
       "Trevor Bell                                                                                     Place   \n",
       "Victor Pasmore                                                                   Linear Development 1   \n",
       "William Blake                                       Job, his Wife and his Friends: The Complaint o...   \n",
       "William Daniell                                                               Bovisand, near Plymouth   \n",
       "William G. Simmonds                                                                         Old Horse   \n",
       "William Henry Brooke                                          Lanherne Bay near the Nunnery, Cornwall   \n",
       "William Henry Hunt                                                                  [title not known]   \n",
       "William Hogarth                                                                  The Enraged Musician   \n",
       "William Roberts                                                                  Study for ‘Two Step’   \n",
       "William Tucker                                                                             Anabasis I   \n",
       "William Turnbull                                                                                 Head   \n",
       "Wolfgang Tillmans                                                                            The Bell   \n",
       "Wyndham Lewis                                                                              Mrs Schiff   \n",
       "Yves Tanguy                                                                                  Untitled   \n",
       "after Edward Dayes                                  The Peak Cavern, Derbyshire: View from the Int...   \n",
       "after John Flaxman                                                                 The Fiery Serpents   \n",
       "after Joseph Mallord William Turner                                                         Bass Rock   \n",
       "after Peter De Wint                                                                            Bognor   \n",
       "attributed to Benjamin Ralph                                                           Norwich Castle   \n",
       "\n",
       "                                                    acquisitionYear height  \\\n",
       "all_artists                                                                  \n",
       "Abraham Cooper                                                 1997     76   \n",
       "Achilles Droungas                                              1975    698   \n",
       "Adrian Stokes                                                  2001    510   \n",
       "Akram Zaatari                                                  2008    289   \n",
       "Alan Davie                                                     1991    176   \n",
       "Albert Goodwin                                                 1901   1420   \n",
       "Albert Houthuesen                                              1975    632   \n",
       "Alex Katz                                                      2008    404   \n",
       "Alexander Cozens                                               1996    142   \n",
       "Allen David                                                    1975    464   \n",
       "Ambrose McEvoy                                                 1926    768   \n",
       "Andrew Wilson                                                  1997    287   \n",
       "Andy Warhol                                                    2008          \n",
       "Anthony Gross                                                  1946    591   \n",
       "Art & Language (Michael Baldwin, born 1945; Mel...             1983   1680   \n",
       "Arthur Boyd Houghton                                           1922          \n",
       "Barnett Freedman                                               1976    591   \n",
       "Barry Flanagan                                                 1985    180   \n",
       "Ben Nicholson OM                                               1976    149   \n",
       "Benjamin West                                                  1974    229   \n",
       "Berenice Abbott                                                2010    200   \n",
       "Bernard Cohen                                                  1965   2438   \n",
       "Bhupen Khakhar                                                 1996   1756   \n",
       "Birdhead (Ji Weiyu, born 1980; Song Tao, born 1...             2013          \n",
       "Bob Law                                                        2004    385   \n",
       "Brice Marden                                                   1993    525   \n",
       "British (?) School                                             1997    127   \n",
       "British School 16th century                                    1961    483   \n",
       "British School 19th century                                    1997    289   \n",
       "Cecil Collins                                                  1979    127   \n",
       "...                                                             ...    ...   \n",
       "Terry Winters                                                  2002    100   \n",
       "Thomas Barker of Bath                                          1890   1130   \n",
       "Thomas Gainsborough                                            1910   1486   \n",
       "Thomas Girtin                                                  1856    215   \n",
       "Thomas Hearne                                                  1967    403   \n",
       "Thomas Rowlandson                                              1997    195   \n",
       "Thomas Schütte                                                 2003    320   \n",
       "Thomas Sidney Cooper                                           1900    406   \n",
       "Thomas Stothard                                                1997     90   \n",
       "Tom Phillips                                                   1975    140   \n",
       "Tracey Moffatt                                                 1998    600   \n",
       "Trevor Bell                                                    2012    980   \n",
       "Victor Pasmore                                                 1975    420   \n",
       "William Blake                                                  1882    186   \n",
       "William Daniell                                                1979    241   \n",
       "William G. Simmonds                                            1937    570   \n",
       "William Henry Brooke                                           1981    190   \n",
       "William Henry Hunt                                             1997     91   \n",
       "William Hogarth                                                1973    405   \n",
       "William Roberts                                                1968          \n",
       "William Tucker                                                 1970   1099   \n",
       "William Turnbull                                               1990   1016   \n",
       "Wolfgang Tillmans                                              2007   1450   \n",
       "Wyndham Lewis                                                  1956   1003   \n",
       "Yves Tanguy                                                    2007    235   \n",
       "after Edward Dayes                                             1988          \n",
       "after John Flaxman                                             1997    192   \n",
       "after Joseph Mallord William Turner                            1986          \n",
       "after Peter De Wint                                            1988    115   \n",
       "attributed to Benjamin Ralph                                   1997    187   \n",
       "\n",
       "                                                     width  \n",
       "all_artists                                                 \n",
       "Abraham Cooper                                        35.0  \n",
       "Achilles Droungas                                    524.0  \n",
       "Adrian Stokes                                        685.0  \n",
       "Akram Zaatari                                        290.0  \n",
       "Alan Davie                                           308.0  \n",
       "Albert Goodwin                                      1075.0  \n",
       "Albert Houthuesen                                    491.0  \n",
       "Alex Katz                                            309.0  \n",
       "Alexander Cozens                                      98.0  \n",
       "Allen David                                          610.0  \n",
       "Ambrose McEvoy                                      1016.0  \n",
       "Andrew Wilson                                        213.0  \n",
       "Andy Warhol                                          695.0  \n",
       "Anthony Gross                                        413.0  \n",
       "Art & Language (Michael Baldwin, born 1945; Mel...   797.0  \n",
       "Arthur Boyd Houghton                                   NaN  \n",
       "Barnett Freedman                                     952.0  \n",
       "Barry Flanagan                                       127.0  \n",
       "Ben Nicholson OM                                     159.0  \n",
       "Benjamin West                                        292.0  \n",
       "Berenice Abbott                                      250.0  \n",
       "Bernard Cohen                                       2438.0  \n",
       "Bhupen Khakhar                                      1756.0  \n",
       "Birdhead (Ji Weiyu, born 1980; Song Tao, born 1...     NaN  \n",
       "Bob Law                                              285.0  \n",
       "Brice Marden                                         398.0  \n",
       "British (?) School                                    67.0  \n",
       "British School 16th century                          629.0  \n",
       "British School 19th century                          404.0  \n",
       "Cecil Collins                                        171.0  \n",
       "...                                                    ...  \n",
       "Terry Winters                                         90.0  \n",
       "Thomas Barker of Bath                                813.0  \n",
       "Thomas Gainsborough                                  346.0  \n",
       "Thomas Girtin                                        156.0  \n",
       "Thomas Hearne                                        302.0  \n",
       "Thomas Rowlandson                                    123.0  \n",
       "Thomas Schütte                                       447.0  \n",
       "Thomas Sidney Cooper                                 292.0  \n",
       "Thomas Stothard                                      116.0  \n",
       "Tom Phillips                                         190.0  \n",
       "Tracey Moffatt                                       800.0  \n",
       "Trevor Bell                                          750.0  \n",
       "Victor Pasmore                                       420.0  \n",
       "William Blake                                        260.0  \n",
       "William Daniell                                      162.0  \n",
       "William G. Simmonds                                  200.0  \n",
       "William Henry Brooke                                 146.0  \n",
       "William Henry Hunt                                    86.0  \n",
       "William Hogarth                                      332.0  \n",
       "William Roberts                                      298.0  \n",
       "William Tucker                                      1492.0  \n",
       "William Turnbull                                    1270.0  \n",
       "Wolfgang Tillmans                                   2100.0  \n",
       "Wyndham Lewis                                       1257.0  \n",
       "Yves Tanguy                                           80.0  \n",
       "after Edward Dayes                                     NaN  \n",
       "after John Flaxman                                   131.0  \n",
       "after Joseph Mallord William Turner                   95.0  \n",
       "after Peter De Wint                                   98.0  \n",
       "attributed to Benjamin Ralph                         149.0  \n",
       "\n",
       "[256 rows x 4 columns]"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "group.agg(np.min)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filtering\n",
    "\n",
    "Series or dataframes can be filtered using the .filter method. It receives a condition as a parameter, which is a function that allows the column or row to be filtered."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "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>acquisitionYear</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1035</th>\n",
       "      <td>1922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20230</th>\n",
       "      <td>1927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6725</th>\n",
       "      <td>1922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7330</th>\n",
       "      <td>1888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7430</th>\n",
       "      <td>1888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7530</th>\n",
       "      <td>1888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7630</th>\n",
       "      <td>1888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7730</th>\n",
       "      <td>1888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9492</th>\n",
       "      <td>1924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14407</th>\n",
       "      <td>1905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14700</th>\n",
       "      <td>1925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12191</th>\n",
       "      <td>1946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69330</th>\n",
       "      <td>1888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69430</th>\n",
       "      <td>1888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69530</th>\n",
       "      <td>1888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69630</th>\n",
       "      <td>1888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69730</th>\n",
       "      <td>1888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69830</th>\n",
       "      <td>1888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98171</th>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98537</th>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97256</th>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97551</th>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99037</th>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98345</th>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99125</th>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99132</th>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105706</th>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105826</th>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105944</th>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106055</th>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24928</th>\n",
       "      <td>1997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25315</th>\n",
       "      <td>1997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25456</th>\n",
       "      <td>1997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25801</th>\n",
       "      <td>1997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25254</th>\n",
       "      <td>1997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25746</th>\n",
       "      <td>1997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25392</th>\n",
       "      <td>1997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25713</th>\n",
       "      <td>1997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25933</th>\n",
       "      <td>1997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80033</th>\n",
       "      <td>2004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80857</th>\n",
       "      <td>2004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84316</th>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88228</th>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88060</th>\n",
       "      <td>2006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81819</th>\n",
       "      <td>2006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26747</th>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94662</th>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66602</th>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99423</th>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100499</th>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101563</th>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96968</th>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108923</th>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90120</th>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111919</th>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118532</th>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117815</th>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117484</th>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89762</th>\n",
       "      <td>2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123531</th>\n",
       "      <td>2013</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>738 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        acquisitionYear\n",
       "id                     \n",
       "1035               1922\n",
       "20230              1927\n",
       "6725               1922\n",
       "7330               1888\n",
       "7430               1888\n",
       "7530               1888\n",
       "7630               1888\n",
       "7730               1888\n",
       "9492               1924\n",
       "14407              1905\n",
       "14700              1925\n",
       "12191              1946\n",
       "69330              1888\n",
       "69430              1888\n",
       "69530              1888\n",
       "69630              1888\n",
       "69730              1888\n",
       "69830              1888\n",
       "98171              2008\n",
       "98537              2008\n",
       "97256              2009\n",
       "97551              2009\n",
       "99037              2009\n",
       "98345              2009\n",
       "99125              2009\n",
       "99132              2009\n",
       "105706             2009\n",
       "105826             2009\n",
       "105944             2009\n",
       "106055             2009\n",
       "...                 ...\n",
       "24928              1997\n",
       "25315              1997\n",
       "25456              1997\n",
       "25801              1997\n",
       "25254              1997\n",
       "25746              1997\n",
       "25392              1997\n",
       "25713              1997\n",
       "25933              1997\n",
       "80033              2004\n",
       "80857              2004\n",
       "84316              2005\n",
       "88228              2005\n",
       "88060              2006\n",
       "81819              2006\n",
       "26747              2007\n",
       "94662              2007\n",
       "66602              2008\n",
       "99423              2008\n",
       "100499             2008\n",
       "101563             2009\n",
       "96968              2010\n",
       "108923             2010\n",
       "90120              2010\n",
       "111919             2011\n",
       "118532             2012\n",
       "117815             2012\n",
       "117484             2012\n",
       "89762              2013\n",
       "123531             2013\n",
       "\n",
       "[738 rows x 1 columns]"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.filter(like='ear',axis=1)#Axis of 1 goes over columns, 0 over rows"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exporting to Excel\n",
    "\n",
    "Pandas allows for easy exporting of a dataframe to Excel files.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_excel('test.xlsx')#All columns dumped\n",
    "df.to_excel('test2.xlsx',index=False)#No index column included\n",
    "df.to_excel('test3.xlsx',columns=['all_artists','title','acquisitionYear'])#Only selected columns, index still included\n",
    "df.to_excel('test4.xlsx',columns=['all_artists','title','acquisitionYear'],index=False)#Only selected columns and index is not included"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Panda also allows you to create different sheets before writing the file.\n",
    "You can select which DataFrames will go into which sheets. Each sheet can have its columns selected independently from each other."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "excel_writer=pd.ExcelWriter('sheets_example.xlsx', engine='xlsxwriter') #This entity handles sheets storage and writing\n",
    "df.to_excel(excel_writer,sheet_name='First',index=False)\n",
    "df.to_excel(excel_writer, sheet_name='Second',columns=['all_artists','title','acquisitionYear'],index=False)\n",
    "excel_writer.save()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before the save command, no sheets have actually been written, they've only been saved to the writer."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Many more operations may be performed, but they belong to the underlying ExcelWriter class which is not part of Pandas, so they won't be covered."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## SQL connectivity\n",
    "\n",
    "Pandas also allows for connectivity with classic SQL databases. In the name of speed, we'll use SQLite."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sqlite3\n",
    "\n",
    "with sqlite3.connect('example_db.db')as conn:\n",
    "    df.to_sql('Test',conn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exporting to JSON"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_json('test.json')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "group = df.groupby('acquisitionYear').size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20c215ff1d0>"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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uK2PqhN60DQu2Oo5HOzclgeBA0c6bSrUCLfpucLi+gUfn5NI7vg2XDetidRyPFx0RzNm94pilq3iUcjkt+m7wzood7NhXzX3pKQQF6n/ypsiwJbKnvIY1Px2wOopSPkUrUCsrq6rluQWbGdMnjtG99XaRTTU+JZ6QwACd4lHKxbTot7Lnvt1EdW0D903qZ3UUr9I2LJjRfeKYvaGQxkad4lHKVbTot6KCkkreXfkTVwzvSq/4KKvjeJ0MWyLFFYfJ3LHf6ihK+Qwt+q3okdl5RIQEcvv4XlZH8Urj+8UTGqRTPEq5khb9VvLd5r0szCvhD2N70qFNqNVxvFJkaBBj+3Zk9oYiGnSKRymX0KLfCuobGnloZi5dYyK45oxkq+N4tQxbEqUHD7Ny2z6royjlE7Tot4KPMneRX1zJPef1JTRIe+U7Y2zfjoQHB+odtZRyES36LlZZU8fT8/MZnhzDxNQEq+N4vfCQQMb168jc7CLqGxqtjqOU19Oi72IvLd5C6cFa7s/oh4j2yneFDFsSZVW1fL9Fp3iUcpZTRV9EporIRhHJFpH3RcSv7+69s6ya15dt46LBnbB1bmd1HJ8xpk8cbUKD9I5aSrlAi4u+iHQCbgXSjDGpQCBwmauCeaPH5+YRIPDHiX2sjuJTwoIDmZASz9yNRdTW6xSPUs5wdnonCAgXkSAgAvDbBdWrd5Qxc30hN43qQWJ0uNVxfE76gETKD9WxvKDU6ihKebUWF31jzG5gBvATUAiUG2O+cVUwb9LYaPjbzFzi24Zy0+juVsfxSWf3jiUqLEhX8SjlJGemd9oD5wPdgCQgUkR+dZzn3SgimSKSuXfv3pYn9WBvLN9G1s4D3H1eXyJCgqyO45NCgwI5t38C3+QUcbi+weo4SnktZ6Z3xgPbjDF7jTF1wGfAGcc+yRjzqjEmzRiTFhfne10mC0oO8sS8fMb3i+eCQZ2sjuPT0m2JVNbUs3STTvEo1VLOFP2fgBEiEiH2tYnjgFzXxPIO9Q2NTPs4i4iQQB65KFWXaLays3rG0i4iWHvxKOUEZ+b0VwKfAGuADY59veqiXF7hlaVbydp5gIcuSKVjlF+vVnWL4MAAJvZP4NucYmrqdIpHqZZwavWOMebPxpi+xphUY8xVxpjDrgrm6XILK3j2202k2xLJsCVZHcdvZNiSqKptYHF+idVRlPJKekVuC9TWN3LHR1lEhwfz4PmpVsfxKyO6x9AhMoSvdRWPUi2iRb8FXli4mdzCCh69yEZMZIjVcfxKUGAAE1MTWJhbQnVtvdVxlPI6WvSbaf2uA7y4eAsXDenEhJR4q+P4pQxbEofqGliYp1M8SjWXFv1mqKlr4I6PsohrE8qfJ/e3Oo7fGt4thrioUGZm6RSPUs2lRb8Znpm/iYKSgzw+xUZ0eLDVcfxWYIAwKTWBRfklHDysUzxKNYcW/SbK3F7Gq99t5YrTuzK6t+9dZOZtMgYmcbi+kQW5xVZHUcqraNFvguraeqZ/nEWnduHcO6mf1XEUMLRrexLahvG1TvEo1Sxa9Jvg8Tl5bN9XzYxLBtImVHvreIKAAGHSgESWbtpL+aE6q+Mo5TW06J/C9wWlvLViB78+M5kR3TtYHUcdJWNgIrUNjXybo1M8SjWVFv2TqKyp44+frKdbbCR3ntvX6jjqGIO7tKNTu3DtxaNUM2jRP4mHZ+VSWH6IGZcMJDwk0Oo46hgiQoYtke82l3KgutbqOEp5BS36J7Aov4QPVu3kxlE9GHpae6vjqBNItyVS32iYt7HI6ihKeQUt+sdRXl3H3Z+up3d8G6ZO6GV1HHUSAzpF0zUmQu+opVQTadE/jr98vZF9B2t5+tJBhAbptI4nOzLF8/2Wfew76DdNXpVqMS36x5ibXcTna3fz+7E9Se0UbXUc1QTptkQaGg1zdYpHqVPSon+UfQcPc9/nG0jt1JZbzulpdRzVRCmJbekeG6m9eJRqAi36DsYY7v8im8qaep66ZBDBgfqfxlscmeJZuW0fJZU1VsdRyqNpZXP4KmsPc7KLmDqhN30SoqyOo5opY2ASjcY+PaeUOjEt+kBxRQ0PfLmRwV3bceOo7lbHUS3QOz6KXh3b6BSPUqfg90XfGMM9n23gcH0DT10ykMAAsTqSaqEMWxKrdpRRVK5TPEqdiN8X/Y9X72JhXgl3ntuX7nFtrI6jnJBuS8QYmL1Bz/aVOhG/Lvq7Dxzib1/ncHq3GK49I9nqOMpJPTu2oW9ClPbiUeok/LboNzYa7vpkPcYYZlwykACd1vEJkwcmseanA+w+cMjqKEp5JL8t+u+t3MGyglLuS0+hS0yE1XGUi2TYEgGYrW0ZlDoup4q+iLQTkU9EJE9EckVkpKuCtaYd+6p4ZHYeo3rHcfnwLlbHUS50WodIBnSK1ikepU7A2TP954C5xpi+wEAg1/lIrauh0TD94yyCAoXHLx6AiE7r+Jp0WyJZu8r5aV+11VGU8jgtLvoi0hYYBbwOYIypNcYccFWw1vKv5dtYtX0/f5ncn8TocKvjqFaQPsA+xTNLV/Eo9TPOnOl3B/YC/xKRtSLymohEuihXqygoqeSJefmM7xfPRUM6WR1HtZIuMREM6tJOp3j8gDGGFxcV8Mz8TVQdrrc6jldwpugHAUOAfxhjBgNVwN3HPklEbhSRTBHJ3Lt3rxOHc059QyPTPsoiMiSQRy5K1WkdH5dhS2Tjngq2lVZZHUW1ojeWb+fJefk8t2Az455awldZezDGWB3LozlT9HcBu4wxKx0/f4L9H4H/YYx51RiTZoxJi4uLc+Jwznll6VaydpXz4AWpdIwKsyyHco9JjimemVl6tu+rFuQW89CsHCb2T+Djm0fSoU0It76/lste/YHcwgqr43msFhd9Y0wRsFNE+jg2jQNyXJLKxXL2VPDst5vIsCWSYUuyOo5yg6R24aSd1l7n9X1Uzp4K/vD+WlKTonnm/wYxLDmGr35/Fg9fmEp+cSXpz3/Hn7/Mpry6zuqoHsfZ1Tt/AN4TkfXAIOAR5yO5Vm19I9M+ziI6PIQHz0+1Oo5yowxbInlFlRSUVFodRblQSUUN17+1iujwYF67Jo3wEPvd7QIDhCtPP43F08dw5emn8c4POzjnqcV88ONPNDbqlM8RThV9Y8w6x9SNzRhzgTFmv6uCucrfF24mt7CCRy8aQPvIEKvjKDc6b0AiIvC1dt70GYdqG/jN25mUH6rjtWvSiG/786nadhEhPHhBKl//4Sx6xEVy92cbuOCl5az9yePKkyV8+orcrJ0HeGnxFi4e0pkJKfFWx1FuFt82jOHJMczaUKgf7vmAxkbDtI/XsX53Oc9dNpj+SSe/nWn/pGg+umkkz/7fIIrKa7jwpe+Z/nEWeyv9+17KPlv0a+oamPZxFh2jQnlgcorVcZRFMgYmUVBykPxineLxdk/Nz2f2hiLuPa9fk0/iRIQLBndi4fQx3DS6O1+u283YGYt5fdk26hoaWzmxZ/LZov/0/E0UlBzk8YttRIcHWx1HWeS81AQCBL25ipf7ZPUuXly0hcuHd+GGs7s1+/VtQoO457x+zL19FENOa8+DM3OY9Nx3fF9Q2gppPZtPFv3M7WX887utXHF6V0b1tm6ZqLJebJtQRvbowMz1un7bW/24rYx7PlvPGT068LfznbvGpkdcG9789TD+eXUaNfUNXPHaSn733mq/6srqc0W/uraeaR9n0bl9OPdO6md1HOUBMmxJbN9XzcY9unbb22wvreKmdzLpEhPBP64cSnCg8yVLRJiQEs/8qaO5Y0JvFuaVMO6pxTy/YDM1dQ0uSO3ZfK7oPz4njx37qnlyykDahAZZHUd5gIn9EwgMEGZqu2WvUl5dx3VvrcIAb1wzjOgI107ThgUHcuu4Xnx7x2jG9u3I0/M3MeGZJczPKfbpd4U+VfSXF5Ty1oodXHdmN0Z072B1HOUh2keGcGbPWJ3i8SJ1DY389r3V7Cyr5pVfDSU5tvXaenVuH8FLVw7lvRtOJywokN+8ncm1/1rF1r0HW+2YVvKZol9ZU8edn6yne2wkd07sc+oXKL+SYUtk1/5DZO0qtzqKOgVjDA98mc33W/bx2EU2TnfTCdyZPWOZfdvZ3J/ejzU79nPus0t5dE4uB32skZvPFP2HZuZSWH6IGZcOJCw40Oo4ysOcm5JAcKAwSztverzXl23j/R93css5Pbh4aGe3Hjs4MIAbzu7OwuljOH9QJ15ZspWxMxbzxdrdPvMu0SeK/qK8Ej7M3MlNo3swpGt7q+MoDxQdEcyoXnHMWl+ol+R7sPk5xTw8O5dJAxKYNsG6d+xxUaHMuGQgn/3uDBKiw7j9w3Vc+soKNu7x/neKXl/0D1TXcten6+kTH8Xt43tZHUd5sHRbInvKa1i7Uy/H90Qb95Rz2wdrsXWK5qlLBhEQYH378yFd2/PF787ksYsGsGVvFZP/vow/fZHNgepaq6O1mNcX/b98tZGyqlqeunQgoUE6raNObEJKPCFBAbqKxwMVV9Rw/ZuZtAsP5p9X/7eJmicICBAuG96VRdPGcPXIZN5buYNzZizmvZU7aPDCd41eXfTnZhfyxbo9/H5sT1I7nbwPh1JRYcGM6R3H7A06xeNJqmvrueGtTCpr6njtmmF0PE4TNU8QHRHMX37Zn1m3nk2v+Cju+zyb819cxuodZVZHaxavLfr7Dh7mvs+zSe3UllvO6Wl1HOUl0m2JFFccZtV27/of1Vc1Nhru+DCL7D3lPH/5YFKS2lod6ZT6JbblwxtH8PzlgymtrOXif6zgjo/WUVJZY3W0JvHKom+M4b7Ps6msqefpSwe55Co95R/G94snLFineDzFk9/kM3djEfdN6se4ft7TCVdE+OXAJBZMG83vxvRgZlYhY2cs4Z9Lt1Jb79mN3LyyWn6VtYe5G4u44xe96R0fZXUc5UUiQ4MY27cjc7ILvXI+1pd8lLmTfyzewhWnd+X6s5rfRM0TRIYGcefEvsybOorh3WJ4eHYu5z23lO82W3c/8FPxuqJfXFHDA19uZEjXdvzm7O5Wx1FeKMOWROnBWlZu3Wd1FL/1w9Z93Pf5Bs7uFctff9nfqSZqnqBbbCRvXDuM169Jo77RcNXrP3LTO5nsLKu2OtrPeFXRN8Zw96frOVzfwIxLBhLoAUu6lPc5p09HIkIC+VqneCyxrbSKm99dTdeYCF64YohPTc+O6xfPvNtH8cdz+7B0Uynjn17Cs99u8qhGbl71X/vjzF0syt/LXRP70j2ujdVxlJcKDwlkXL945mYXUu+nN9KwyoHqWq5/cxUCvHHtMJ+810VYcCC3nNOTBdNGMyElnme/3cz4p5cwN7vII67q9Zqiv2t/NX+bmcOI7jFcMzLZ6jjKy2XYEtlfXcf3W3SKx11q6xv57btr2LX/EK9encZpHVqviZonSGoXzgtXDOH934wgMiSIm99dzdVv/EhBibWN3Lyi6Dc2Gu76dD3GGJ6cMtAjrtRT3m107zjahAYxU3vxuIUxhj99kc2Krft4fMoAhiXHWB3JbUb26MCsW8/iz5NTWLfzABOfXcrDs3KorKmzJI9XFP33Vu5gecE+7ktPoUtMhNVxlA8ICw5kQko8c7OLPH6JnS94delWPszcyR/G9uTCwe5touYJggID+PWZ3Vg0fQwXD+nMa8u2MfapJXy6epfbLxT0+KK/vbSKR2bnMap3HJcP72J1HOVDMmyJVNTUs9wP75PqTvM2FvHY3DzSbYlMHd/b6jiWim0TyuNTbHzxuzNJahfOtI+zuOSVFWTvdl8jN48u+g2Nhj9+kkVQoPD4xQO8flmX8ixn94ojKiyIr3WKp9Vk7y7n9g/WYevcjqcu0anZIwZ2acfnvz2DJ6bY2LGviskvLOPezzewv6r1G7k5XfRFJFBE1orITFcEOtoby7axavt+/vrL/iRGh7t698rPhQQFcG7/BOZvLPaoJXW+oqi8huvfWkVMZAj/vHqo3ufiGAEBwqVpXVgwbQy/PqMbH67ayZgZi3lnxfZWvXDQFWf6twG5LtjP/ygoqeTJb/KZkBLPhYM7uXr3SgH2KZ7Kw/V8t1mneFypurae699axcGael67Jo2OUZ7ZRM0TRIcH88DkFGbfejYpiW15vSZrAAARV0lEQVT505cbyfj7slbrD+VU0ReRzkA68Jpr4tjVNzQy7aMsIkMCeeRCndZRrefMnrG0iwjWVTwu1NhouP2DdeQWVvDCFUPol+j5TdQ8QZ+EKP79m9N58YohlFfXcsnLK7j9g7UUV7i2kVuQk69/FrgTcGkDnJeXbCFrVzkvXjGEuKhQV+5aqf8RHBjAxP4JfJW1h8ztZaT50VLC1vL4vDy+ySnmz5NTOKdvR6vjeBURId2WyDl943hp0RZeXbqV+TnFLj1Gi8/0RSQDKDHGrD7F824UkUwRydy799RNiHL2VPDcgs1k2BJJtyW2NJ5STXb9Wd1oGxbMlJdXMPXDdZS4+MzKn3y46ideWbKVX43oyrVnJFsdx2tFhAQx/dw+zL9jFCN7uPbG8NLSy4JF5FHgKqAeCAPaAp8ZY351otekpaWZzMzME+6ztr6RX76wjNKDtcyfOor2kSEtyqZUc1UdrufFRQW89t02ggOFW8f14tdndiMkyKMXuHmU77eUcvXrPzKyRwf+de0wgnyop47VRGS1MSbNFftq8W/FGHOPMaazMSYZuAxYeLKC3xR/X7iZvKJKHrtogBZ85VZHWuR+M3UUp3fvwKNz8pj43FKWbvLcFrmeZOveg/z23TV0i43kxSuHaMH3YB7zm8naeYCXFm9hytDOjE/xnpspKN+S7GiR+8a1aTQ0Gq5+40dufNszW+R6iv1VtVz35ioCA4Q3rh1G2zDfa6LmS1xS9I0xi40xGS19fU1dA9M+zqJjVCgPTE5xRSSlnDK2739b5H632d4i9+n5mzhUq+v5j1Zb38jN765mz4EaXr1qqLZJ8QIecab/1Df5FJQc5PGLbXqWoDzGsS1yn19wpEVuoUe0yLWa/balG1i5rYwnpth05ZOXsLzor9pexmvLtnHl6V0Z1TvO6jhK/czRLXLbhAZx87truOr1HykoqbQ6mqVeXrKVj1fv4tZxvbhAL6D0GpYW/eraeqZ/nEXn9uHcO6mflVGUOqUjLXL/MjmF9bsOMPHZ73hopnUtcq00N7uQx+fmMXlgElPH97I6jmoGS4v+Y3Py+KmsmhlTBhIZ6ux1Ykq1vqDAAK51tMidMrQzry/fxjkzlvCJBS1yrbJhVzm3f7iOwV3b8eQUm14x72UsK/rLC0p5e8UOfn1GN07v7tqLD5RqbR3ahPLYxfYWuZ3ahzP94yymvPy9W1vkWqGw/BDXv7WKDpGhvHpVmjZR80KWFP3Kmjru/GQ93eMiuXNiHysiKOUSR7fI/amsmskvLOOezzZQ5oYWue5Wdbie69/MpLq2gTeuHaYtUryUJUX/oZm5FJYf4qlLBuqZgvJ6x7bI/ShzJ+fMWMzbK7b7zI3XGxoNt32wjryiCl64YjB9Elzabku5kduL/sK8Yj7M3MnNo3swuGt7dx9eqVZzpEXunNvOpn9SWx74ciOTX1jOj9tap0WuOz02J5dvc4v58+T+jOmjTdS8mVuLfkOj4e5PN9A3IYrb9BN/5aN6x0fx3g2n89KV9ha5l76ygts+WEtRuXc2cnv/x5/453fbuGbkaVyjTdS8nluL/p4DhyirqmXGJQMJDdJpHeW7RIRJAxL5dtpo/jC2J3Oyixj71GL+sXgLh+u956re5QWl/OmLbEb3juNPGXq1vC9wa9E/cKiOP4ztRWqnaHceVinLRIQEMe0Xffh26mjO6BHL43PzmPjsdyzKL7E62ikVlBzkt++upntcJH+/YrA2UfMRLW6t3BLtuvY1e7flEKx/eZSfWpRfwt++zmFbaRXj+3XkTxkpnNYh0upYP1NWVcuFLy2n6nA9n//uTO2pYzGPaK3cEl1iIrTgK792Tp+OzL39bO6a2Jfvt+xjwjNLeeqbfI9q5Ha4voGb31lNYXkNr1yVpgXfx7i1AofqDSmUIjQokN+O6cHCaWM4LzWBvy8sYNxTi5m13vpGbsYY7v0smx+3l/HkFBtDT9MVdr5Gq7BSFkmIDuO5ywbz0U0jiY4I4ZZ/r+HK11ayqdi6Rm4vLd7Cp2t2cfv4Xpw/SJuo+SIt+kpZbHi3GL7+/Zk8eH5/Nu6p4LznvuNvX+dQ4eZGbrM3FPLkvHzOH5TEbeN0SbWv0qKvlAcICgzgqpHJLJo+hkvTuvCv77cxdsZiPsrc6ZZGblk7DzD1w3UMPa09j1+sTdR8mRZ9pTxITGQIj140gK9uOYuuMRHc+cl6LvrH92TtPNBqx9xz4BA3vJ1JXFQor1w1VFuj+Dgt+kp5oAGdo/nk5jN46pKB7Np/iAteWs5dn6xn38HDLj1O1eF6rn8rkxpHE7XYNtpEzddp0VfKQwUECBcP7cyi6aO54axufLpmF2NmLOZfy7e5pJFbQ6Ph1vfXsqm4kheuHELveG2i5g+06Cvl4aLCgrkvPYW5t5/NwM7t+OvXOWT8fRk/bN3n1H4fmZ3LgrwS/jI5hdF6q1K/oUVfKS/Rs2MU71w/nJd/NYTKmnoue/UHfv/vNRSWH2r2vt5buYPXl23j2jOSuWpksuvDKo+lRV8pLyIiTExN5Ns7RnPbuF7Mzylm7IwlvLiooMmN3JZtLuWBLzdyTh9touaPtOgr5YXCQwKZOqE3394xmlG9Y3lyXj7nPrOUhXnFJ31dQUklv31vNT3j2vD85YMJDNClmf6mxUVfRLqIyCIRyRWRjSJymyuDKaVOrUtMBK9clcbb1w0nIEC47s1MrntzFdtLq3723LKqWq57M5PQoEBevzaNqLBgCxIrqzlzpl8PTDPG9ANGALeIiL5XVMoCo3rHMfe2Udw7qS8rt+7jF88s5Ym5eVTX1gP2Jmo3vZNJcUUN/7x6KJ3baxM1fxXU0hcaYwqBQsf3lSKSC3QCclyUTSnVDCFBAdw4qgcXDOrEY3PyeGnxFj5bs5t70/uxOK+EVdv388IVg/U2pX7OJf30RSQZWAqkGmMqTvS8tLQ0k5mZ6fTxlFKnlrm9jD9/tZGNe+z/S94xoTe3ak8dr+TKfvpOF30RaQMsAR42xnx2nMdvBG4E6Nq169AdO3Y4dTylVNM1NBo+ytxJWVUtvxvTQ3vqeCmPKfoiEgzMBOYZY54+1fP1TF8ppZrPI+6cJfZThteB3KYUfKWUUtZzZvXOmcBVwFgRWef4muSiXEoppVqBM6t3lgE6QaiUUl5Er8hVSik/okVfKaX8iBZ9pZTyI1r0lVLKj2jRV0opP+KSNgxNPphIJZDvtgO6XyxQanWIVuTL4/PlsYGOz9v1Mca45H6WLV6y2UL5rrqqzBOJSKaOzzv58thAx+ftRMRlrQx0ekcppfyIFn2llPIj7i76r7r5eO6m4/Nevjw20PF5O5eNz60f5CqllLKWTu8opZQfcaron+jm6CISIyLzRWSz48/2ju0iIs+LSIGIrBeRIY7t5xzVqXOdiNSIyAXOD885rhqf47EnHPvIdTzH8mZ1Lh7f4yKS7fj6P6vGdFSe5o6tr4isEJHDIjL9mH1NFJF8x7jvtmI8x3Lx+N4QkRIRybZiLMfjqvGdaD9Wc+H4wkTkRxHJcuznr6c8uDGmxV9AIjDE8X0UsAlIAZ4A7nZsvxt43PH9JGAO9u6cI4CVx9lnDFAGRDiTzRVfrhofcAawHAh0fK0AxvjQ+NKB+diXAEcCmUBbLxtbR2AY8DAw/aj9BAJbgO5ACJAFpHjh7+6443M8NgoYAmRbPa5W+P0ddz8+ND4B2ji+DwZWAiNOdmynzvSNMYXGmDWO7yuBIzdHPx94y/G0t4AjZ+3nA28bux+AdiKSeMxupwBzjDHVzmRzBReOzwBh2ItGKPZfTrHbBnICLhxfCrDEGFNvjKnCXhgnunEoP9PcsRljSowxq4C6Y3Y1HCgwxmw1xtQCHzj2YSkXjg9jzFLsJ1oew1XjO8l+LOXC8RljzEHHj8GOr5N+UOuyOX2x3xx9MPZ/aeKNMYWOUIXY/5UC+6B2HvWyXfz8F3AZ8L6rcrmKM+MzxqwAFgGFjq95xphc9yRvGid/f1nAeSISISKxwDlAF/ckP7Umju1EmvJ31lJOjs/juWp8x+zHYzg7PhEJFJF1QAkw3xhz0vG5pOiL/ebonwK3G2MqTvbU42z7z79KjrPGAcA8V+RyFWfHJyI9gX5AZ+wFY6yIjHJ90pZxdnzGmG+A2cD32P/BXgHUuzxoCzRjbCfcxXG2ecySNxeMz6O5anye+t/JFbmMMQ3GmEHY68twEUk92fOdLvpivzn6p8B7xpjPHJuLj0zbOP4scWzfxf+eAXYG9hz186XA58aYn70FtYqLxnch8IMx5qDjrdgc7HPilnPV788Y87AxZpAxZgL2QrnZHflPppljO5FT/Z21jIvG57FcNb4T7Mdyrv79GWMOAIs5xdSqs6t3TnRz9K+AaxzfXwN8edT2q8VuBFB+5K2Mw+V40NSOC8f3EzBaRIIcv+jR2OfwLOWq8TneXnZw7NMG2IBv3DKIE2jB2E5kFdBLRLqJSAj26cevXJ23uVw4Po/kqvGdZD+WcuH44kSkneP7cGA8kHfSg5/sU95TfQFnYX+rux5Y5/iaBHQAFmA/21sAxJj/ftL8IvbVEBuAtKP2lQzsBgKcyeTKL1eND/sKkFewF/oc4Gmrx+bi8YU5xpUD/AAM8sKxJWA/q68ADji+b+t4bBL21RVbgPusHlsrjO997J811Tm2X+8r4zvRfnxofDZgrWM/2cADpzq2XpGrlFJ+RK/IVUopP6JFXyml/IgWfaWU8iNa9JVSyo9o0VdKKT+iRV/5HBH5m4iMP8njN4vI1Y7vrxWRpKMee01EUlpwzF84uiCK4+dAsXeMPaMlY1CqteiSTeXXRGQx9q6FTt94WkQ+AL41xrwmIrcD/Y0xv3Fyn0HGGI9oaaF8g57pK0uIyBcistrRA/xGx7aJIrLG0Rt8gWNbBxH5RkTWisgrIrJDRGJFJFmO6v8uItNF5C+O798UkSmO7x8TkRyx9/+f4dj2F8fzpwBpwHuOs/JwEVksImmO510uIhvEfo+Ax4861kERediR8wcRiXc8NBW4R0T6A78H7nI8P15EPhORTLH3Ph/h2D7C8e5grYgsF5Feju03iMgHIjITe8sOpVxGi76yynXGmKHYi+6tjsL5T+BiY8xA4BLH8/4MLDPGDMZ+iXrXph5ARGKw9z3qb4yxAQ8d/bgx5hPsvf+vNPa+QYeOem0S8DgwFhgEDJP/3tgnEnsvpYHAUuA3jv0VAs9ibzj3kDHmSLvi54EnjDFp2PtLvebYnguc5Rjbg8fkGwlcZey9jJRymSCrAyi/dauIXOj4vgtwI7DUGLMN4KiCOQq4yLFtlojsb8YxKoAa4DURmQXMbMZrhwGLjTF7AUTkPUeWL4Dao/a1Gji6ML8IPGaMefOobeOBPvLfm6W1d/RJaQe8LSI9jnP8b4wxzRmrUk2iZ/rK7URkDPZCONJxtrwWe0/+E33AdLzt9fzv39+wn73IPhc+HHsnwwuAuc2JeZLH6sx/Pwxr4KiTJ2NM43HyCjDc8W5ikDGmk+NdxcPY762Q6sh39BiqmpFVqSbToq+sEA3sN8ZUi0hf7G2mQ7F3Iu0G/5maAfv0yZWObecB7R3bi4GOjjn/UCDj2IOIvVd5tDFmNnA79mmaY1Viv13dsVY68sSKSCD2DrBLWjRa+Ba45ahcR3JEY28yCHBtC/etVLNo0VdWmAsEich67HPZPwB7sU/xfCYiWcCHjuf+FRglImuAX2BvU42x33Phb9iL80yO3042CpjpOM4S7B+0HutN4OUjH+Qe2eiYn78H+x3PsoA1xpiWtim+BTjT8WFyDo7PALB/ZvCkiCxv4X6VajZdsqm8iohsx97SudTqLEp5Iz3TV0opP6Jn+kop5Uf0TF8ppfyIFn2llPIjWvSVUsqPaNFXSik/okVfKaX8iBZ9pZTyI/8PPD60bUZx2RMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "group.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20c216a4588>"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x1800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "group[100:200].plot.pie(figsize=(25, 25))#Slice of data reduced to increase visibility"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pandas offers a huge amount of visualization options, all of which are thoroughly demonstrated here: https://pandas.pydata.org/pandas-docs/stable/user_guide/visualization.html"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}