Data Cleaning - Genre Addition .ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "artist_by_genre = pd.read_csv('archive/data_w_genres.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .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>artists</th>\n",
       "      <th>acousticness</th>\n",
       "      <th>danceability</th>\n",
       "      <th>duration_ms</th>\n",
       "      <th>energy</th>\n",
       "      <th>instrumentalness</th>\n",
       "      <th>liveness</th>\n",
       "      <th>loudness</th>\n",
       "      <th>speechiness</th>\n",
       "      <th>tempo</th>\n",
       "      <th>valence</th>\n",
       "      <th>popularity</th>\n",
       "      <th>key</th>\n",
       "      <th>mode</th>\n",
       "      <th>count</th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>\"Cats\" 1981 Original London Cast</td>\n",
       "      <td>0.575083</td>\n",
       "      <td>0.442750</td>\n",
       "      <td>247260.000000</td>\n",
       "      <td>0.386336</td>\n",
       "      <td>0.022717</td>\n",
       "      <td>0.287708</td>\n",
       "      <td>-14.205417</td>\n",
       "      <td>0.180675</td>\n",
       "      <td>115.983500</td>\n",
       "      <td>0.334433</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>['show tunes']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>\"Cats\" 1983 Broadway Cast</td>\n",
       "      <td>0.862538</td>\n",
       "      <td>0.441731</td>\n",
       "      <td>287280.000000</td>\n",
       "      <td>0.406808</td>\n",
       "      <td>0.081158</td>\n",
       "      <td>0.315215</td>\n",
       "      <td>-10.690000</td>\n",
       "      <td>0.176212</td>\n",
       "      <td>103.044154</td>\n",
       "      <td>0.268865</td>\n",
       "      <td>33.076923</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>26</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>\"Fiddler On The Roof” Motion Picture Chorus</td>\n",
       "      <td>0.856571</td>\n",
       "      <td>0.348286</td>\n",
       "      <td>328920.000000</td>\n",
       "      <td>0.286571</td>\n",
       "      <td>0.024593</td>\n",
       "      <td>0.325786</td>\n",
       "      <td>-15.230714</td>\n",
       "      <td>0.118514</td>\n",
       "      <td>77.375857</td>\n",
       "      <td>0.354857</td>\n",
       "      <td>34.285714</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>\"Fiddler On The Roof” Motion Picture Orchestra</td>\n",
       "      <td>0.884926</td>\n",
       "      <td>0.425074</td>\n",
       "      <td>262890.962963</td>\n",
       "      <td>0.245770</td>\n",
       "      <td>0.073587</td>\n",
       "      <td>0.275481</td>\n",
       "      <td>-15.639370</td>\n",
       "      <td>0.123200</td>\n",
       "      <td>88.667630</td>\n",
       "      <td>0.372030</td>\n",
       "      <td>34.444444</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>\"Joseph And The Amazing Technicolor Dreamcoat\"...</td>\n",
       "      <td>0.605444</td>\n",
       "      <td>0.437333</td>\n",
       "      <td>232428.111111</td>\n",
       "      <td>0.429333</td>\n",
       "      <td>0.037534</td>\n",
       "      <td>0.216111</td>\n",
       "      <td>-11.447222</td>\n",
       "      <td>0.086000</td>\n",
       "      <td>120.329667</td>\n",
       "      <td>0.458667</td>\n",
       "      <td>42.555556</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27616</th>\n",
       "      <td>鳳飛飛</td>\n",
       "      <td>0.884000</td>\n",
       "      <td>0.358000</td>\n",
       "      <td>259387.000000</td>\n",
       "      <td>0.208000</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>0.150000</td>\n",
       "      <td>-9.524000</td>\n",
       "      <td>0.033900</td>\n",
       "      <td>131.261000</td>\n",
       "      <td>0.278000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>['c-pop', 'classic mandopop', 'vintage chinese...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27617</th>\n",
       "      <td>黃品源</td>\n",
       "      <td>0.541000</td>\n",
       "      <td>0.578000</td>\n",
       "      <td>293840.000000</td>\n",
       "      <td>0.334000</td>\n",
       "      <td>0.000006</td>\n",
       "      <td>0.067500</td>\n",
       "      <td>-11.974000</td>\n",
       "      <td>0.026700</td>\n",
       "      <td>135.934000</td>\n",
       "      <td>0.243000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>['c-pop', 'classic cantopop', 'classic mandopop']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27618</th>\n",
       "      <td>黃國隆</td>\n",
       "      <td>0.785455</td>\n",
       "      <td>0.570818</td>\n",
       "      <td>174582.727273</td>\n",
       "      <td>0.148400</td>\n",
       "      <td>0.000083</td>\n",
       "      <td>0.142191</td>\n",
       "      <td>-21.610091</td>\n",
       "      <td>0.054355</td>\n",
       "      <td>119.586273</td>\n",
       "      <td>0.741273</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27619</th>\n",
       "      <td>黃蜀娟</td>\n",
       "      <td>0.925143</td>\n",
       "      <td>0.322262</td>\n",
       "      <td>212989.857143</td>\n",
       "      <td>0.141490</td>\n",
       "      <td>0.000189</td>\n",
       "      <td>0.196757</td>\n",
       "      <td>-19.256714</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>111.685381</td>\n",
       "      <td>0.267033</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>42</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27620</th>\n",
       "      <td>黑豹</td>\n",
       "      <td>0.381000</td>\n",
       "      <td>0.353000</td>\n",
       "      <td>316160.000000</td>\n",
       "      <td>0.686000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.056800</td>\n",
       "      <td>-9.103000</td>\n",
       "      <td>0.039500</td>\n",
       "      <td>200.341000</td>\n",
       "      <td>0.352000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>['chinese indie', 'chinese indie rock']</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>27621 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 artists  acousticness  \\\n",
       "0                       \"Cats\" 1981 Original London Cast      0.575083   \n",
       "1                              \"Cats\" 1983 Broadway Cast      0.862538   \n",
       "2            \"Fiddler On The Roof” Motion Picture Chorus      0.856571   \n",
       "3         \"Fiddler On The Roof” Motion Picture Orchestra      0.884926   \n",
       "4      \"Joseph And The Amazing Technicolor Dreamcoat\"...      0.605444   \n",
       "...                                                  ...           ...   \n",
       "27616                                                鳳飛飛      0.884000   \n",
       "27617                                                黃品源      0.541000   \n",
       "27618                                                黃國隆      0.785455   \n",
       "27619                                                黃蜀娟      0.925143   \n",
       "27620                                                 黑豹      0.381000   \n",
       "\n",
       "       danceability    duration_ms    energy  instrumentalness  liveness  \\\n",
       "0          0.442750  247260.000000  0.386336          0.022717  0.287708   \n",
       "1          0.441731  287280.000000  0.406808          0.081158  0.315215   \n",
       "2          0.348286  328920.000000  0.286571          0.024593  0.325786   \n",
       "3          0.425074  262890.962963  0.245770          0.073587  0.275481   \n",
       "4          0.437333  232428.111111  0.429333          0.037534  0.216111   \n",
       "...             ...            ...       ...               ...       ...   \n",
       "27616      0.358000  259387.000000  0.208000          0.000002  0.150000   \n",
       "27617      0.578000  293840.000000  0.334000          0.000006  0.067500   \n",
       "27618      0.570818  174582.727273  0.148400          0.000083  0.142191   \n",
       "27619      0.322262  212989.857143  0.141490          0.000189  0.196757   \n",
       "27620      0.353000  316160.000000  0.686000          0.000000  0.056800   \n",
       "\n",
       "        loudness  speechiness       tempo   valence  popularity  key  mode  \\\n",
       "0     -14.205417     0.180675  115.983500  0.334433   38.000000    5     1   \n",
       "1     -10.690000     0.176212  103.044154  0.268865   33.076923    5     1   \n",
       "2     -15.230714     0.118514   77.375857  0.354857   34.285714    0     1   \n",
       "3     -15.639370     0.123200   88.667630  0.372030   34.444444    0     1   \n",
       "4     -11.447222     0.086000  120.329667  0.458667   42.555556   11     1   \n",
       "...          ...          ...         ...       ...         ...  ...   ...   \n",
       "27616  -9.524000     0.033900  131.261000  0.278000   35.000000   10     1   \n",
       "27617 -11.974000     0.026700  135.934000  0.243000   47.000000    9     0   \n",
       "27618 -21.610091     0.054355  119.586273  0.741273   20.000000    5     1   \n",
       "27619 -19.256714     0.055571  111.685381  0.267033   23.000000   10     1   \n",
       "27620  -9.103000     0.039500  200.341000  0.352000   34.000000   11     1   \n",
       "\n",
       "       count                                             genres  \n",
       "0         12                                     ['show tunes']  \n",
       "1         26                                                 []  \n",
       "2          7                                                 []  \n",
       "3         27                                                 []  \n",
       "4          9                                                 []  \n",
       "...      ...                                                ...  \n",
       "27616      2  ['c-pop', 'classic mandopop', 'vintage chinese...  \n",
       "27617      2  ['c-pop', 'classic cantopop', 'classic mandopop']  \n",
       "27618     11                                                 []  \n",
       "27619     42                                                 []  \n",
       "27620      2            ['chinese indie', 'chinese indie rock']  \n",
       "\n",
       "[27621 rows x 16 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "artist_by_genre"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Majore music genres from here: https://examples.yourdictionary.com/major-types-of-music-from-around-the-world.html\n",
    "\n",
    "Country\n",
    "Electronic dance music (EDM)\n",
    "Hip-hop\n",
    "Indie rock\n",
    "Jazz\n",
    "K-pop (Not)\n",
    "Metal\n",
    "Oldies\n",
    "Pop\n",
    "Rap\n",
    "Rhythm & blues (R&B)\n",
    "Rock\n",
    "Classical"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"['c-pop', 'classic mandopop', 'vintage chinese pop']\""
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "artist_by_genre.at[27616,'genres'].lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "filtered_genre = []\n",
    "\n",
    "for index, row in artist_by_genre.iterrows():\n",
    "    if row['genres'] == '[]':\n",
    "        filtered_genre.append(None)\n",
    "    else:\n",
    "        if 'country' in row['genres'].lower():\n",
    "            filtered_genre.append('Country')\n",
    "        elif 'electronic' in row['genres'].lower():\n",
    "            filtered_genre.append('EDM')\n",
    "        elif 'dance' in row['genres'].lower():\n",
    "            filtered_genre.append('EDM')\n",
    "        elif 'edm' in row['genres'].lower():\n",
    "            filtered_genre.append('EDM')\n",
    "        elif 'hip hop' in row['genres'].lower():\n",
    "            filtered_genre.append('Hip-hop')\n",
    "        elif 'indie' in row['genres'].lower():\n",
    "            filtered_genre.append('Indie')\n",
    "        elif 'jazz' in row['genres'].lower():\n",
    "            filtered_genre.append('Jazz')\n",
    "        elif 'pop' in row['genres'].lower():\n",
    "            filtered_genre.append('Pop')\n",
    "        elif 'metal' in row['genres'].lower():\n",
    "            filtered_genre.append('Metal')\n",
    "        elif 'old' in row['genres'].lower():\n",
    "            filtered_genre.append('Oldies')\n",
    "        elif 'rap' in row['genres'].lower():\n",
    "            filtered_genre.append('Rap')\n",
    "        elif 'rhythm and blues' in row['genres'].lower():\n",
    "            filtered_genre.append('R&B')\n",
    "        elif 'rock' in row['genres'].lower():\n",
    "            filtered_genre.append('Rock')\n",
    "        elif 'classical' in row['genres'].lower():\n",
    "            filtered_genre.append('Classical')   \n",
    "        else:\n",
    "            filtered_genre.append(None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "artist_by_genre['filtered_genre'] = filtered_genre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "artist_by_valid_genre = artist_by_genre.dropna(subset=['filtered_genre'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "artist_by_valid_genre.to_csv('archive/artists_w_filtered_genres.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NUMBER OF DISTINCT FILTERED GENRES:  12\n"
     ]
    }
   ],
   "source": [
    "print('NUMBER OF DISTINCT FILTERED GENRES: ', len(set(artist_by_valid_genre['filtered_genre'].tolist())))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "list_genres = artist_by_valid_genre['filtered_genre'].tolist()\n",
    "distinct_genres = set(list_genres)\n",
    "genre_artist_count_dict = dict()\n",
    "\n",
    "for genre in distinct_genres:\n",
    "    genre_artist_count_dict[genre] = list_genres.count(genre)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "genre_artist_count_dict_sorted = dict(sorted(genre_artist_count_dict.items(), reverse=True, key=lambda item: item[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,10))\n",
    "plt.bar(list(genre_artist_count_dict_sorted.keys()), list(genre_artist_count_dict_sorted.values()))\n",
    "plt.xticks(rotation='vertical')\n",
    "plt.ylabel('Artist count')\n",
    "plt.xlabel('Genre')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}