{
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 },
 "nbformat": 4,
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 "cells": [
  {
   "source": [
    "# Nigerian Music scraped from Spotify - an analysis"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Requirement already satisfied: seaborn in /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages (0.11.1)\n",
      "Requirement already satisfied: scipy>=1.0 in /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages (from seaborn) (1.4.1)\n",
      "Requirement already satisfied: numpy>=1.15 in /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages (from seaborn) (1.19.2)\n",
      "Requirement already satisfied: pandas>=0.23 in /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages (from seaborn) (1.1.2)\n",
      "Requirement already satisfied: matplotlib>=2.2 in /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages (from seaborn) (3.1.0)\n",
      "Requirement already satisfied: python-dateutil>=2.7.3 in /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages (from pandas>=0.23->seaborn) (2.8.0)\n",
      "Requirement already satisfied: pytz>=2017.2 in /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages (from pandas>=0.23->seaborn) (2019.1)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (1.1.0)\n",
      "Requirement already satisfied: cycler>=0.10 in /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (0.10.0)\n",
      "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (2.4.0)\n",
      "Requirement already satisfied: six>=1.5 in /Users/jenlooper/Library/Python/3.7/lib/python/site-packages (from python-dateutil>=2.7.3->pandas>=0.23->seaborn) (1.12.0)\n",
      "Requirement already satisfied: setuptools in /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages (from kiwisolver>=1.0.1->matplotlib>=2.2->seaborn) (45.1.0)\n",
      "\u001b[33mWARNING: You are using pip version 20.2.3; however, version 21.1.2 is available.\n",
      "You should consider upgrading via the '/Library/Frameworks/Python.framework/Versions/3.7/bin/python3.7 -m pip install --upgrade pip' command.\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "!pip install seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                       name                         album  \\\n",
       "0                    Sparky            Mandy & The Jungle   \n",
       "1                shuga rush  EVERYTHING YOU HEARD IS TRUE   \n",
       "2                     LITT!                         LITT!   \n",
       "3  Confident / Feeling Cool               Enjoy Your Life   \n",
       "4                wanted you                         rare.   \n",
       "\n",
       "                artist artist_top_genre  release_date  length  popularity  \\\n",
       "0        Cruel Santino  alternative r&b          2019  144000          48   \n",
       "1  Odunsi (The Engine)          afropop          2020   89488          30   \n",
       "2                 AYLØ        indie r&b          2018  207758          40   \n",
       "3           Lady Donli     nigerian pop          2019  175135          14   \n",
       "4  Odunsi (The Engine)          afropop          2018  152049          25   \n",
       "\n",
       "   danceability  acousticness  energy  instrumentalness  liveness  loudness  \\\n",
       "0         0.666        0.8510   0.420          0.534000    0.1100    -6.699   \n",
       "1         0.710        0.0822   0.683          0.000169    0.1010    -5.640   \n",
       "2         0.836        0.2720   0.564          0.000537    0.1100    -7.127   \n",
       "3         0.894        0.7980   0.611          0.000187    0.0964    -4.961   \n",
       "4         0.702        0.1160   0.833          0.910000    0.3480    -6.044   \n",
       "\n",
       "   speechiness    tempo  time_signature  \n",
       "0       0.0829  133.015               5  \n",
       "1       0.3600  129.993               3  \n",
       "2       0.0424  130.005               4  \n",
       "3       0.1130  111.087               4  \n",
       "4       0.0447  105.115               4  "
      ],
      "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>album</th>\n      <th>artist</th>\n      <th>artist_top_genre</th>\n      <th>release_date</th>\n      <th>length</th>\n      <th>popularity</th>\n      <th>danceability</th>\n      <th>acousticness</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>time_signature</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Sparky</td>\n      <td>Mandy &amp; The Jungle</td>\n      <td>Cruel Santino</td>\n      <td>alternative r&amp;b</td>\n      <td>2019</td>\n      <td>144000</td>\n      <td>48</td>\n      <td>0.666</td>\n      <td>0.8510</td>\n      <td>0.420</td>\n      <td>0.534000</td>\n      <td>0.1100</td>\n      <td>-6.699</td>\n      <td>0.0829</td>\n      <td>133.015</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>shuga rush</td>\n      <td>EVERYTHING YOU HEARD IS TRUE</td>\n      <td>Odunsi (The Engine)</td>\n      <td>afropop</td>\n      <td>2020</td>\n      <td>89488</td>\n      <td>30</td>\n      <td>0.710</td>\n      <td>0.0822</td>\n      <td>0.683</td>\n      <td>0.000169</td>\n      <td>0.1010</td>\n      <td>-5.640</td>\n      <td>0.3600</td>\n      <td>129.993</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>LITT!</td>\n      <td>LITT!</td>\n      <td>AYLØ</td>\n      <td>indie r&amp;b</td>\n      <td>2018</td>\n      <td>207758</td>\n      <td>40</td>\n      <td>0.836</td>\n      <td>0.2720</td>\n      <td>0.564</td>\n      <td>0.000537</td>\n      <td>0.1100</td>\n      <td>-7.127</td>\n      <td>0.0424</td>\n      <td>130.005</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Confident / Feeling Cool</td>\n      <td>Enjoy Your Life</td>\n      <td>Lady Donli</td>\n      <td>nigerian pop</td>\n      <td>2019</td>\n      <td>175135</td>\n      <td>14</td>\n      <td>0.894</td>\n      <td>0.7980</td>\n      <td>0.611</td>\n      <td>0.000187</td>\n      <td>0.0964</td>\n      <td>-4.961</td>\n      <td>0.1130</td>\n      <td>111.087</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>wanted you</td>\n      <td>rare.</td>\n      <td>Odunsi (The Engine)</td>\n      <td>afropop</td>\n      <td>2018</td>\n      <td>152049</td>\n      <td>25</td>\n      <td>0.702</td>\n      <td>0.1160</td>\n      <td>0.833</td>\n      <td>0.910000</td>\n      <td>0.3480</td>\n      <td>-6.044</td>\n      <td>0.0447</td>\n      <td>105.115</td>\n      <td>4</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "metadata": {},
     "execution_count": 21
    }
   ],
   "source": [
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "df = pd.read_csv(\"../../data/nigerian-songs.csv\")\n",
    "df.head()"
   ]
  },
  {
   "source": [
    "Get information about the dataframe"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "source": [
    "df.info()"
   ],
   "cell_type": "code",
   "metadata": {},
   "execution_count": 22,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\nRangeIndex: 530 entries, 0 to 529\nData columns (total 16 columns):\n #   Column            Non-Null Count  Dtype  \n---  ------            --------------  -----  \n 0   name              530 non-null    object \n 1   album             530 non-null    object \n 2   artist            530 non-null    object \n 3   artist_top_genre  530 non-null    object \n 4   release_date      530 non-null    int64  \n 5   length            530 non-null    int64  \n 6   popularity        530 non-null    int64  \n 7   danceability      530 non-null    float64\n 8   acousticness      530 non-null    float64\n 9   energy            530 non-null    float64\n 10  instrumentalness  530 non-null    float64\n 11  liveness          530 non-null    float64\n 12  loudness          530 non-null    float64\n 13  speechiness       530 non-null    float64\n 14  tempo             530 non-null    float64\n 15  time_signature    530 non-null    int64  \ndtypes: float64(8), int64(4), object(4)\nmemory usage: 66.4+ KB\n"
     ]
    }
   ]
  },
  {
   "source": [
    "Double-check for null values."
   ],
   "cell_type": "code",
   "metadata": {},
   "execution_count": 23,
   "outputs": [
    {
     "output_type": "error",
     "ename": "SyntaxError",
     "evalue": "invalid syntax (<ipython-input-23-33dd3e912c4b>, line 1)",
     "traceback": [
      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-23-33dd3e912c4b>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m    Double-check for null values.\u001b[0m\n\u001b[0m                   ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "name                0\n",
       "album               0\n",
       "artist              0\n",
       "artist_top_genre    0\n",
       "release_date        0\n",
       "length              0\n",
       "popularity          0\n",
       "danceability        0\n",
       "acousticness        0\n",
       "energy              0\n",
       "instrumentalness    0\n",
       "liveness            0\n",
       "loudness            0\n",
       "speechiness         0\n",
       "tempo               0\n",
       "time_signature      0\n",
       "dtype: int64"
      ]
     },
     "metadata": {},
     "execution_count": 19
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "source": [
    "Look at the general values of the data. Note that popularity can be '0' - and there are many rows with that value"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "       release_date         length  popularity  danceability  acousticness  \\\n",
       "count    530.000000     530.000000  530.000000    530.000000    530.000000   \n",
       "mean    2015.390566  222298.169811   17.507547      0.741619      0.265412   \n",
       "std        3.131688   39696.822259   18.992212      0.117522      0.208342   \n",
       "min     1998.000000   89488.000000    0.000000      0.255000      0.000665   \n",
       "25%     2014.000000  199305.000000    0.000000      0.681000      0.089525   \n",
       "50%     2016.000000  218509.000000   13.000000      0.761000      0.220500   \n",
       "75%     2017.000000  242098.500000   31.000000      0.829500      0.403000   \n",
       "max     2020.000000  511738.000000   73.000000      0.966000      0.954000   \n",
       "\n",
       "           energy  instrumentalness    liveness    loudness  speechiness  \\\n",
       "count  530.000000        530.000000  530.000000  530.000000   530.000000   \n",
       "mean     0.760623          0.016305    0.147308   -4.953011     0.130748   \n",
       "std      0.148533          0.090321    0.123588    2.464186     0.092939   \n",
       "min      0.111000          0.000000    0.028300  -19.362000     0.027800   \n",
       "25%      0.669000          0.000000    0.075650   -6.298750     0.059100   \n",
       "50%      0.784500          0.000004    0.103500   -4.558500     0.097950   \n",
       "75%      0.875750          0.000234    0.164000   -3.331000     0.177000   \n",
       "max      0.995000          0.910000    0.811000    0.582000     0.514000   \n",
       "\n",
       "            tempo  time_signature  \n",
       "count  530.000000      530.000000  \n",
       "mean   116.487864        3.986792  \n",
       "std     23.518601        0.333701  \n",
       "min     61.695000        3.000000  \n",
       "25%    102.961250        4.000000  \n",
       "50%    112.714500        4.000000  \n",
       "75%    125.039250        4.000000  \n",
       "max    206.007000        5.000000  "
      ],
      "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>release_date</th>\n      <th>length</th>\n      <th>popularity</th>\n      <th>danceability</th>\n      <th>acousticness</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>time_signature</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>530.000000</td>\n      <td>530.000000</td>\n      <td>530.000000</td>\n      <td>530.000000</td>\n      <td>530.000000</td>\n      <td>530.000000</td>\n      <td>530.000000</td>\n      <td>530.000000</td>\n      <td>530.000000</td>\n      <td>530.000000</td>\n      <td>530.000000</td>\n      <td>530.000000</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>2015.390566</td>\n      <td>222298.169811</td>\n      <td>17.507547</td>\n      <td>0.741619</td>\n      <td>0.265412</td>\n      <td>0.760623</td>\n      <td>0.016305</td>\n      <td>0.147308</td>\n      <td>-4.953011</td>\n      <td>0.130748</td>\n      <td>116.487864</td>\n      <td>3.986792</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>3.131688</td>\n      <td>39696.822259</td>\n      <td>18.992212</td>\n      <td>0.117522</td>\n      <td>0.208342</td>\n      <td>0.148533</td>\n      <td>0.090321</td>\n      <td>0.123588</td>\n      <td>2.464186</td>\n      <td>0.092939</td>\n      <td>23.518601</td>\n      <td>0.333701</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>1998.000000</td>\n      <td>89488.000000</td>\n      <td>0.000000</td>\n      <td>0.255000</td>\n      <td>0.000665</td>\n      <td>0.111000</td>\n      <td>0.000000</td>\n      <td>0.028300</td>\n      <td>-19.362000</td>\n      <td>0.027800</td>\n      <td>61.695000</td>\n      <td>3.000000</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>2014.000000</td>\n      <td>199305.000000</td>\n      <td>0.000000</td>\n      <td>0.681000</td>\n      <td>0.089525</td>\n      <td>0.669000</td>\n      <td>0.000000</td>\n      <td>0.075650</td>\n      <td>-6.298750</td>\n      <td>0.059100</td>\n      <td>102.961250</td>\n      <td>4.000000</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>2016.000000</td>\n      <td>218509.000000</td>\n      <td>13.000000</td>\n      <td>0.761000</td>\n      <td>0.220500</td>\n      <td>0.784500</td>\n      <td>0.000004</td>\n      <td>0.103500</td>\n      <td>-4.558500</td>\n      <td>0.097950</td>\n      <td>112.714500</td>\n      <td>4.000000</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>2017.000000</td>\n      <td>242098.500000</td>\n      <td>31.000000</td>\n      <td>0.829500</td>\n      <td>0.403000</td>\n      <td>0.875750</td>\n      <td>0.000234</td>\n      <td>0.164000</td>\n      <td>-3.331000</td>\n      <td>0.177000</td>\n      <td>125.039250</td>\n      <td>4.000000</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>2020.000000</td>\n      <td>511738.000000</td>\n      <td>73.000000</td>\n      <td>0.966000</td>\n      <td>0.954000</td>\n      <td>0.995000</td>\n      <td>0.910000</td>\n      <td>0.811000</td>\n      <td>0.582000</td>\n      <td>0.514000</td>\n      <td>206.007000</td>\n      <td>5.000000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "metadata": {},
     "execution_count": 5
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "source": [
    "Let's examine the genres. Quite a few are listed as 'Missing' which means they aren't categorized in the dataset with a genre "
   ],
   "cell_type": "code",
   "metadata": {},
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Top genres')"
      ]
     },
     "metadata": {},
     "execution_count": 6
    },
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "top = df['artist_top_genre'].value_counts()\n",
    "plt.figure(figsize=(10,7))\n",
    "sns.barplot(x=top[:5].index,y=top[:5].values)\n",
    "plt.xticks(rotation=45)\n",
    "plt.title('Top genres',color = 'blue')"
   ]
  },
  {
   "source": [
    "Remove 'Missing' genres, as it's not classified in Spotify\n"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Top genres')"
      ]
     },
     "metadata": {},
     "execution_count": 7
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 720x504 with 1 Axes>",
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "df = df[df['artist_top_genre'] != 'Missing']\n",
    "top = df['artist_top_genre'].value_counts()\n",
    "plt.figure(figsize=(10,7))\n",
    "sns.barplot(x=top.index,y=top.values)\n",
    "plt.xticks(rotation=45)\n",
    "plt.title('Top genres',color = 'blue')"
   ]
  },
  {
   "source": [
    "The top three genres comprise the greatest part of the dataset, so let's focus on those"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Top genres')"
      ]
     },
     "metadata": {},
     "execution_count": 8
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 720x504 with 1 Axes>",
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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "df = df[(df['artist_top_genre'] == 'afro dancehall') | (df['artist_top_genre'] == 'afropop') | (df['artist_top_genre'] == 'nigerian pop')]\n",
    "df = df[(df['popularity'] > 0)]\n",
    "top = df['artist_top_genre'].value_counts()\n",
    "plt.figure(figsize=(10,7))\n",
    "sns.barplot(x=top.index,y=top.values)\n",
    "plt.xticks(rotation=45)\n",
    "plt.title('Top genres',color = 'blue')"
   ]
  },
  {
   "source": [
    "The data is not strongly correlated except between energy and loudness, which makes sense. Popularity has a correspondence to release data, which also makes sense, as more recent songs are probably more popular. Length and energy seem to have a correlation - perhaps shorter songs are more energetic?"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "corrmat = df.corr()\n",
    "f, ax = plt.subplots(figsize=(12, 9))\n",
    "sns.heatmap(corrmat, vmax=.8, square=True);"
   ]
  },
  {
   "source": [
    "Are the genres significantly different in the perception of their danceability, based on their popularity? Examine our top three genres data distribution for popularity and danceability along a given x and y axis "
   ],
   "cell_type": "code",
   "metadata": {},
   "execution_count": null,
   "outputs": []
  },
  {
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     },
     "metadata": {}
    }
   ],
   "source": [
    "sns.set_theme(style=\"ticks\")\n",
    "\n",
    "# Show the joint distribution using kernel density estimation\n",
    "g = sns.jointplot(\n",
    "    data=df,\n",
    "    x=\"popularity\", y=\"danceability\", hue=\"artist_top_genre\",\n",
    "    kind=\"kde\",\n",
    ")"
   ]
  },
  {
   "source": [
    "In general, the three genres align in terms of their popularity and danceability.  A scatterplot of the same axes shows a similar pattern of convergence. Try a scatterplot to check the distribution of data per genre"
   ],
   "cell_type": "code",
   "metadata": {},
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:316: UserWarning: The `size` parameter has been renamed to `height`; please update your code.\n  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7fc69984fa20>"
      ]
     },
     "metadata": {},
     "execution_count": 13
    },
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "sns.FacetGrid(df, hue=\"artist_top_genre\", size=5) \\\n",
    "   .map(plt.scatter, \"popularity\", \"danceability\") \\\n",
    "   .add_legend()"
   ]
  }
 ]
}