From 928ca98cfbfd7ab193b3730eea1a2daa07b7a5b4 Mon Sep 17 00:00:00 2001 From: CharlotteStiller <76783661+CharlotteStiller@users.noreply.github.com> Date: Wed, 13 Oct 2021 16:49:03 +0200 Subject: [PATCH] Add files via upload --- Solutions.ipynb | 1813 +++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 1813 insertions(+) create mode 100644 Solutions.ipynb diff --git a/Solutions.ipynb b/Solutions.ipynb new file mode 100644 index 0000000..3454287 --- /dev/null +++ b/Solutions.ipynb @@ -0,0 +1,1813 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## LAB SPOTIFY" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 3 playlists and 1 question: Is this the best party music or music to fall sleep? \n", + "(Playlist maker: My brother) " + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "scrolled": true, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'tracks': {'href': 'https://api.spotify.com/v1/search?query=artist%3A+Queen&type=track&offset=0&limit=2',\n", + " 'items': [{'album': {'album_type': 'album',\n", + " 'artists': [{'external_urls': {'spotify': 'https://open.spotify.com/artist/1dfeR4HaWDbWqFHLkxsg1d'},\n", + " 'href': 'https://api.spotify.com/v1/artists/1dfeR4HaWDbWqFHLkxsg1d',\n", + " 'id': '1dfeR4HaWDbWqFHLkxsg1d',\n", + " 'name': 'Queen',\n", + " 'type': 'artist',\n", + " 'uri': 'spotify:artist:1dfeR4HaWDbWqFHLkxsg1d'}],\n", + " 'available_markets': ['CA', 'US'],\n", + " 'external_urls': {'spotify': 'https://open.spotify.com/album/6X9k3hSsvQck2OfKYdBbXr'},\n", + " 'href': 'https://api.spotify.com/v1/albums/6X9k3hSsvQck2OfKYdBbXr',\n", + " 'id': '6X9k3hSsvQck2OfKYdBbXr',\n", + " 'images': [{'height': 640,\n", + " 'url': 'https://i.scdn.co/image/ab67616d0000b273ce4f1737bc8a646c8c4bd25a',\n", + " 'width': 640},\n", + " {'height': 300,\n", + " 'url': 'https://i.scdn.co/image/ab67616d00001e02ce4f1737bc8a646c8c4bd25a',\n", + " 'width': 300},\n", + " {'height': 64,\n", + " 'url': 'https://i.scdn.co/image/ab67616d00004851ce4f1737bc8a646c8c4bd25a',\n", + " 'width': 64}],\n", + " 'name': 'A Night At The Opera (Deluxe Remastered Version)',\n", + " 'release_date': '1975-11-21',\n", + " 'release_date_precision': 'day',\n", + " 'total_tracks': 18,\n", + " 'type': 'album',\n", + " 'uri': 'spotify:album:6X9k3hSsvQck2OfKYdBbXr'},\n", + " 'artists': [{'external_urls': {'spotify': 'https://open.spotify.com/artist/1dfeR4HaWDbWqFHLkxsg1d'},\n", + " 'href': 'https://api.spotify.com/v1/artists/1dfeR4HaWDbWqFHLkxsg1d',\n", + " 'id': '1dfeR4HaWDbWqFHLkxsg1d',\n", + " 'name': 'Queen',\n", + " 'type': 'artist',\n", + " 'uri': 'spotify:artist:1dfeR4HaWDbWqFHLkxsg1d'}],\n", + " 'available_markets': ['CA', 'US'],\n", + " 'disc_number': 1,\n", + " 'duration_ms': 354320,\n", + " 'explicit': False,\n", + " 'external_ids': {'isrc': 'GBUM71029604'},\n", + " 'external_urls': {'spotify': 'https://open.spotify.com/track/7tFiyTwD0nx5a1eklYtX2J'},\n", + " 'href': 'https://api.spotify.com/v1/tracks/7tFiyTwD0nx5a1eklYtX2J',\n", + " 'id': '7tFiyTwD0nx5a1eklYtX2J',\n", + " 'is_local': False,\n", + " 'name': 'Bohemian Rhapsody - Remastered 2011',\n", + " 'popularity': 74,\n", + " 'preview_url': None,\n", + " 'track_number': 11,\n", + " 'type': 'track',\n", + " 'uri': 'spotify:track:7tFiyTwD0nx5a1eklYtX2J'},\n", + " {'album': {'album_type': 'album',\n", + " 'artists': [{'external_urls': {'spotify': 'https://open.spotify.com/artist/1dfeR4HaWDbWqFHLkxsg1d'},\n", + " 'href': 'https://api.spotify.com/v1/artists/1dfeR4HaWDbWqFHLkxsg1d',\n", + " 'id': '1dfeR4HaWDbWqFHLkxsg1d',\n", + " 'name': 'Queen',\n", + " 'type': 'artist',\n", + " 'uri': 'spotify:artist:1dfeR4HaWDbWqFHLkxsg1d'}],\n", + " 'available_markets': ['CA', 'US'],\n", + " 'external_urls': {'spotify': 'https://open.spotify.com/album/6wPXUmYJ9mOWrKlLzZ5cCa'},\n", + " 'href': 'https://api.spotify.com/v1/albums/6wPXUmYJ9mOWrKlLzZ5cCa',\n", + " 'id': '6wPXUmYJ9mOWrKlLzZ5cCa',\n", + " 'images': [{'height': 640,\n", + " 'url': 'https://i.scdn.co/image/ab67616d0000b27307744e2ed983efa3e6620a47',\n", + " 'width': 640},\n", + " {'height': 300,\n", + " 'url': 'https://i.scdn.co/image/ab67616d00001e0207744e2ed983efa3e6620a47',\n", + " 'width': 300},\n", + " {'height': 64,\n", + " 'url': 'https://i.scdn.co/image/ab67616d0000485107744e2ed983efa3e6620a47',\n", + " 'width': 64}],\n", + " 'name': 'The Game (Deluxe Remastered Version)',\n", + " 'release_date': '1980-06-27',\n", + " 'release_date_precision': 'day',\n", + " 'total_tracks': 15,\n", + " 'type': 'album',\n", + " 'uri': 'spotify:album:6wPXUmYJ9mOWrKlLzZ5cCa'},\n", + " 'artists': [{'external_urls': {'spotify': 'https://open.spotify.com/artist/1dfeR4HaWDbWqFHLkxsg1d'},\n", + " 'href': 'https://api.spotify.com/v1/artists/1dfeR4HaWDbWqFHLkxsg1d',\n", + " 'id': '1dfeR4HaWDbWqFHLkxsg1d',\n", + " 'name': 'Queen',\n", + " 'type': 'artist',\n", + " 'uri': 'spotify:artist:1dfeR4HaWDbWqFHLkxsg1d'}],\n", + " 'available_markets': ['CA', 'US'],\n", + " 'disc_number': 1,\n", + " 'duration_ms': 214653,\n", + " 'explicit': False,\n", + " 'external_ids': {'isrc': 'GBUM71029605'},\n", + " 'external_urls': {'spotify': 'https://open.spotify.com/track/57JVGBtBLCfHw2muk5416J'},\n", + " 'href': 'https://api.spotify.com/v1/tracks/57JVGBtBLCfHw2muk5416J',\n", + " 'id': '57JVGBtBLCfHw2muk5416J',\n", + " 'is_local': False,\n", + " 'name': 'Another One Bites The Dust - Remastered 2011',\n", + " 'popularity': 74,\n", + " 'preview_url': None,\n", + " 'track_number': 3,\n", + " 'type': 'track',\n", + " 'uri': 'spotify:track:57JVGBtBLCfHw2muk5416J'}],\n", + " 'limit': 2,\n", + " 'next': 'https://api.spotify.com/v1/search?query=artist%3A+Queen&type=track&offset=2&limit=2',\n", + " 'offset': 0,\n", + " 'previous': None,\n", + " 'total': 10000}}" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import spotipy\n", + "from spotipy.oauth2 import SpotifyClientCredentials\n", + "\n", + "#Initialize SpotiPy with user credentias\n", + "sp = spotipy.Spotify(auth_manager=SpotifyClientCredentials(client_id='Learned that it is better to not upload the id',\n", + " client_secret='Learned that it is better to not upload the key'))\n", + "\n", + "results = sp.search(q='artist: Queen', limit=2)\n", + "results" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "playlist_id='3UERdXjRtUA8vNRQTtnY8M' #insert your playlist id\n", + "results = sp.playlist(playlist_id)\n", + "\n", + "# create a list of song ids\n", + "ids=[]\n", + "\n", + "for item in results['tracks']['items']:\n", + " track = item['track']['id']\n", + " ids.append(track)\n", + " \n", + "song_meta={'id':[],'album':[], 'name':[], \n", + " 'artist':[],'explicit':[],'popularity':[]}\n", + "\n", + "for song_id in ids:\n", + " # get song's meta data\n", + " meta = sp.track(song_id)\n", + " \n", + " # song id\n", + " song_meta['id'].append(song_id)\n", + "\n", + " # album name\n", + " album=meta['album']['name']\n", + " song_meta['album']+=[album]\n", + "\n", + " # song name\n", + " song=meta['name']\n", + " song_meta['name']+=[song]\n", + " \n", + " # artists name\n", + " s = ', '\n", + " artist=s.join([singer_name['name'] for singer_name in meta['artists']])\n", + " song_meta['artist']+=[artist]\n", + " \n", + " # explicit: lyrics could be considered offensive or unsuitable for children\n", + " explicit=meta['explicit']\n", + " song_meta['explicit'].append(explicit)\n", + " \n", + " # song popularity\n", + " popularity=meta['popularity']\n", + " song_meta['popularity'].append(popularity)\n", + "\n", + "song_meta_df=pd.DataFrame.from_dict(song_meta)\n", + "\n", + "# check the song feature\n", + "features = sp.audio_features(song_meta['id'])\n", + "# change dictionary to dataframe\n", + "features_df=pd.DataFrame.from_dict(features)\n", + "\n", + "# convert milliseconds to mins\n", + "# duration_ms: The duration of the track in milliseconds.\n", + "# 1 minute = 60 seconds = 60 × 1000 milliseconds = 60,000 ms\n", + "features_df['duration_ms']=features_df['duration_ms']/60000\n", + "\n", + "# combine two dataframe\n", + "playlist_kai_september_2021=song_meta_df.merge(features_df)" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(25, 23)" + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "playlist_kai_september_2021.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [], + "source": [ + "playlist_id='7yd0uFcl7Goe6QctOUSunM' #insert your playlist id\n", + "results = sp.playlist(playlist_id)\n", + "\n", + "# create a list of song ids\n", + "ids=[]\n", + "\n", + "for item in results['tracks']['items']:\n", + " track = item['track']['id']\n", + " ids.append(track)\n", + " \n", + "song_meta={'id':[],'album':[], 'name':[], \n", + " 'artist':[],'explicit':[],'popularity':[]}\n", + "\n", + "for song_id in ids:\n", + " # get song's meta data\n", + " meta = sp.track(song_id)\n", + " \n", + " # song id\n", + " song_meta['id'].append(song_id)\n", + "\n", + " # album name\n", + " album=meta['album']['name']\n", + " song_meta['album']+=[album]\n", + "\n", + " # song name\n", + " song=meta['name']\n", + " song_meta['name']+=[song]\n", + " \n", + " # artists name\n", + " s = ', '\n", + " artist=s.join([singer_name['name'] for singer_name in meta['artists']])\n", + " song_meta['artist']+=[artist]\n", + " \n", + " # explicit: lyrics could be considered offensive or unsuitable for children\n", + " explicit=meta['explicit']\n", + " song_meta['explicit'].append(explicit)\n", + " \n", + " # song popularity\n", + " popularity=meta['popularity']\n", + " song_meta['popularity'].append(popularity)\n", + "\n", + "song_meta_df=pd.DataFrame.from_dict(song_meta)\n", + "\n", + "# check the song feature\n", + "features = sp.audio_features(song_meta['id'])\n", + "# change dictionary to dataframe\n", + "features_df=pd.DataFrame.from_dict(features)\n", + "\n", + "# convert milliseconds to mins\n", + "# duration_ms: The duration of the track in milliseconds.\n", + "# 1 minute = 60 seconds = 60 × 1000 milliseconds = 60,000 ms\n", + "features_df['duration_ms']=features_df['duration_ms']/60000\n", + "\n", + "# combine two dataframe\n", + "playlist_kai_november_2020=song_meta_df.merge(features_df)" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(53, 23)" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "playlist_kai_november_2020.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "playlist_id='4uGpGn66fyq3Ecc5VNo4Kv' #insert your playlist id\n", + "results = sp.playlist(playlist_id)\n", + "\n", + "# create a list of song ids\n", + "ids=[]\n", + "\n", + "for item in results['tracks']['items']:\n", + " track = item['track']['id']\n", + " ids.append(track)\n", + " \n", + "song_meta={'id':[],'album':[], 'name':[], \n", + " 'artist':[],'explicit':[],'popularity':[]}\n", + "\n", + "for song_id in ids:\n", + " # get song's meta data\n", + " meta = sp.track(song_id)\n", + " \n", + " # song id\n", + " song_meta['id'].append(song_id)\n", + "\n", + " # album name\n", + " album=meta['album']['name']\n", + " song_meta['album']+=[album]\n", + "\n", + " # song name\n", + " song=meta['name']\n", + " song_meta['name']+=[song]\n", + " \n", + " # artists name\n", + " s = ', '\n", + " artist=s.join([singer_name['name'] for singer_name in meta['artists']])\n", + " song_meta['artist']+=[artist]\n", + " \n", + " # explicit: lyrics could be considered offensive or unsuitable for children\n", + " explicit=meta['explicit']\n", + " song_meta['explicit'].append(explicit)\n", + " \n", + " # song popularity\n", + " popularity=meta['popularity']\n", + " song_meta['popularity'].append(popularity)\n", + "\n", + "song_meta_df=pd.DataFrame.from_dict(song_meta)\n", + "\n", + "# check the song feature\n", + "features = sp.audio_features(song_meta['id'])\n", + "# change dictionary to dataframe\n", + "features_df=pd.DataFrame.from_dict(features)\n", + "\n", + "# convert milliseconds to mins\n", + "# duration_ms: The duration of the track in milliseconds.\n", + "# 1 minute = 60 seconds = 60 × 1000 milliseconds = 60,000 ms\n", + "features_df['duration_ms']=features_df['duration_ms']/60000\n", + "\n", + "# combine two dataframe\n", + "playlist_kai_januar_2020=song_meta_df.merge(features_df)" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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idalbumnameartistexplicitpopularitydanceabilityenergykeyloudness...instrumentalnesslivenessvalencetempotypeuritrack_hrefanalysis_urlduration_mstime_signature
01YLUxdSfbsXYktpkp1aUvdPelicans WeThe FlyCosmo SheldrakeFalse00.8650.69410-6.358...0.0008420.11000.6610103.988audio_featuresspotify:track:1YLUxdSfbsXYktpkp1aUvdhttps://api.spotify.com/v1/tracks/1YLUxdSfbsXY...https://api.spotify.com/v1/audio-analysis/1YLU...3.5656334
157HwKH3pHLeelTkckr94qfBeware of the ManiacsHorny HippiesThe DodosFalse460.4490.54111-10.299...0.0000000.17000.2760125.156audio_featuresspotify:track:57HwKH3pHLeelTkckr94qfhttps://api.spotify.com/v1/tracks/57HwKH3pHLee...https://api.spotify.com/v1/audio-analysis/57Hw...2.9849334
24Dy9SM605DwtyqEHGUj1ZDHusbandsYou, Me, CellphonesHusbandsFalse00.5120.5500-8.264...0.0008390.10600.480099.905audio_featuresspotify:track:4Dy9SM605DwtyqEHGUj1ZDhttps://api.spotify.com/v1/tracks/4Dy9SM605Dwt...https://api.spotify.com/v1/audio-analysis/4Dy9...3.6432174
3290xSzR8Ee9fm82poMg4odQuiet FerocityUsed to Be in LoveThe Jungle GiantsFalse620.8300.63111-5.238...0.0359000.05390.8770128.013audio_featuresspotify:track:290xSzR8Ee9fm82poMg4odhttps://api.spotify.com/v1/tracks/290xSzR8Ee9f...https://api.spotify.com/v1/audio-analysis/290x...3.7131174
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76UaocmOO1bO7YwfHv9KqcyThe Way We Were: The Best Of Gladys Knight & T...Midnight Train to GeorgiaGladys Knight & The PipsFalse600.5790.47710-8.539...0.0000000.09740.537089.724audio_featuresspotify:track:6UaocmOO1bO7YwfHv9Kqcyhttps://api.spotify.com/v1/tracks/6UaocmOO1bO7...https://api.spotify.com/v1/audio-analysis/6Uao...4.6682174
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18 rows × 23 columns

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+ " name artist explicit \\\n", + "0 The Fly Cosmo Sheldrake False \n", + "1 Horny Hippies The Dodos False \n", + "2 You, Me, Cellphones Husbands False \n", + "3 Used to Be in Love The Jungle Giants False \n", + "4 Heart Oberhofer False \n", + "5 The Hustle Unlimited Lambchop False \n", + "6 I Get A Kick Out Of You Frank Sinatra False \n", + "7 Midnight Train to Georgia Gladys Knight & The Pips False \n", + "8 Camberwell #1 Dads False \n", + "9 Miffed Tom Rosenthal False \n", + "10 Common World Yes I'm Very Tired Now False \n", + "11 Hearts CHILDREN False \n", + "12 Disco Benny Sings False \n", + "13 Cupa Cupa - Little People Remix Parra for Cuva, Little People False \n", + "14 Surrender (Kosi Edit) - mixed Portable, L_cio False \n", + "15 Bloodflow - Edit Grandbrothers False \n", + "16 Every Soul Twiddle False \n", + "17 Rip It Up Orange Juice False \n", + "\n", + " popularity danceability energy key loudness ... instrumentalness \\\n", + "0 0 0.865 0.694 10 -6.358 ... 0.000842 \n", + "1 46 0.449 0.541 11 -10.299 ... 0.000000 \n", + "2 0 0.512 0.550 0 -8.264 ... 0.000839 \n", + "3 62 0.830 0.631 11 -5.238 ... 0.035900 \n", + "4 21 0.403 0.732 9 -7.386 ... 0.379000 \n", + "5 39 0.601 0.478 6 -14.561 ... 0.867000 \n", + "6 0 0.393 0.385 5 -10.985 ... 0.000000 \n", + "7 60 0.579 0.477 10 -8.539 ... 0.000000 \n", + "8 0 0.809 0.434 5 -10.688 ... 0.470000 \n", + "9 41 0.783 0.579 5 -11.799 ... 0.147000 \n", + "10 27 0.756 0.672 0 -6.847 ... 0.387000 \n", + "11 4 0.715 0.464 2 -7.807 ... 0.000588 \n", + "12 0 0.823 0.551 6 -11.649 ... 0.412000 \n", + "13 0 0.694 0.648 10 -7.954 ... 0.850000 \n", + "14 0 0.714 0.759 7 -12.869 ... 0.248000 \n", + "15 48 0.488 0.663 3 -12.098 ... 0.908000 \n", + "16 37 0.563 0.872 11 -6.548 ... 0.001080 \n", + "17 55 0.881 0.546 7 -9.357 ... 0.000149 \n", + "\n", + " liveness valence tempo type \\\n", + "0 0.1100 0.6610 103.988 audio_features \n", + "1 0.1700 0.2760 125.156 audio_features \n", + "2 0.1060 0.4800 99.905 audio_features \n", + "3 0.0539 0.8770 128.013 audio_features \n", + "4 0.1140 0.1950 162.576 audio_features \n", + "5 0.3260 0.4860 111.028 audio_features \n", + "6 0.5450 0.7770 177.956 audio_features \n", + "7 0.0974 0.5370 89.724 audio_features \n", + "8 0.0827 0.7880 120.034 audio_features \n", + "9 0.1200 0.3700 155.790 audio_features \n", + "10 0.0859 0.6420 97.987 audio_features \n", + "11 0.2210 0.4110 108.995 audio_features \n", + "12 0.0920 0.9620 100.987 audio_features \n", + "13 0.0628 0.0913 115.005 audio_features \n", + "14 0.0998 0.8490 119.994 audio_features \n", + "15 0.1180 0.2460 97.021 audio_features \n", + "16 0.1030 0.8860 124.200 audio_features \n", + "17 0.0497 0.8520 102.814 audio_features \n", + "\n", + " uri \\\n", + "0 spotify:track:1YLUxdSfbsXYktpkp1aUvd \n", + "1 spotify:track:57HwKH3pHLeelTkckr94qf \n", + "2 spotify:track:4Dy9SM605DwtyqEHGUj1ZD \n", + "3 spotify:track:290xSzR8Ee9fm82poMg4od \n", + "4 spotify:track:5ySZ6gVWw9XQf1Dxg4gj2M \n", + "5 spotify:track:5x2iDSe6UhPogU7tdOsI9L \n", + "6 spotify:track:7bzfyzaZjqai1wTEJsxTOF \n", + "7 spotify:track:6UaocmOO1bO7YwfHv9Kqcy \n", + "8 spotify:track:6rJGYKNLvDeXl021XUT8SK \n", + "9 spotify:track:6w6bztcdjdwRtHkrVBexGE \n", + "10 spotify:track:67dDXJ2BkhEdCaM4cvTOw6 \n", + "11 spotify:track:42IE9djoOoTpW5BGxKlPA1 \n", + "12 spotify:track:4S61nFbE4MU8I0SeiI2Ebw \n", + "13 spotify:track:4nZNT7iFMpKBz90niaVh6O \n", + "14 spotify:track:6SeMUbVazXNQ1ofAaZIMOj \n", + "15 spotify:track:3TxH9hjKCNlHTUQsPiUaLK \n", + "16 spotify:track:73rarLN1ixtnfgjtAZpOIN \n", + "17 spotify:track:1eamsmwcYYhJwTgMFdQ6YN \n", + "\n", + " track_href \\\n", + "0 https://api.spotify.com/v1/tracks/1YLUxdSfbsXY... \n", + "1 https://api.spotify.com/v1/tracks/57HwKH3pHLee... \n", + "2 https://api.spotify.com/v1/tracks/4Dy9SM605Dwt... \n", + "3 https://api.spotify.com/v1/tracks/290xSzR8Ee9f... \n", + "4 https://api.spotify.com/v1/tracks/5ySZ6gVWw9XQ... \n", + "5 https://api.spotify.com/v1/tracks/5x2iDSe6UhPo... 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https://api.spotify.com/v1/audio-analysis/290x... 3.713117 \n", + "4 https://api.spotify.com/v1/audio-analysis/5ySZ... 4.186217 \n", + "5 https://api.spotify.com/v1/audio-analysis/5x2i... 5.479717 \n", + "6 https://api.spotify.com/v1/audio-analysis/7bzf... 3.234883 \n", + "7 https://api.spotify.com/v1/audio-analysis/6Uao... 4.668217 \n", + "8 https://api.spotify.com/v1/audio-analysis/6rJG... 3.832667 \n", + "9 https://api.spotify.com/v1/audio-analysis/6w6b... 3.212317 \n", + "10 https://api.spotify.com/v1/audio-analysis/67dD... 3.645617 \n", + "11 https://api.spotify.com/v1/audio-analysis/42IE... 3.163383 \n", + "12 https://api.spotify.com/v1/audio-analysis/4S61... 3.063450 \n", + "13 https://api.spotify.com/v1/audio-analysis/4nZN... 4.430550 \n", + "14 https://api.spotify.com/v1/audio-analysis/6SeM... 6.922883 \n", + "15 https://api.spotify.com/v1/audio-analysis/3TxH... 3.667900 \n", + "16 https://api.spotify.com/v1/audio-analysis/73ra... 5.883933 \n", + "17 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idalbumnameartistexplicitpopularitydanceabilityenergykeyloudness...instrumentalnesslivenessvalencetempotypeuritrack_hrefanalysis_urlduration_mstime_signature
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24Dy9SM605DwtyqEHGUj1ZDHusbandsYou, Me, CellphonesHusbandsFalse00.5120.5500-8.264...0.0008390.10600.480099.905audio_featuresspotify:track:4Dy9SM605DwtyqEHGUj1ZDhttps://api.spotify.com/v1/tracks/4Dy9SM605Dwt...https://api.spotify.com/v1/audio-analysis/4Dy9...3.6432174
3290xSzR8Ee9fm82poMg4odQuiet FerocityUsed to Be in LoveThe Jungle GiantsFalse620.8300.63111-5.238...0.0359000.05390.8770128.013audio_featuresspotify:track:290xSzR8Ee9fm82poMg4odhttps://api.spotify.com/v1/tracks/290xSzR8Ee9f...https://api.spotify.com/v1/audio-analysis/290x...3.7131174
45ySZ6gVWw9XQf1Dxg4gj2MTime Capsules IIHeartOberhoferFalse210.4030.7329-7.386...0.3790000.11400.1950162.576audio_featuresspotify:track:5ySZ6gVWw9XQf1Dxg4gj2Mhttps://api.spotify.com/v1/tracks/5ySZ6gVWw9XQ...https://api.spotify.com/v1/audio-analysis/5ySZ...4.1862174
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206otUjBoNrp27EubqsoYGQxSandLosersBalthazarFalse580.8640.3855-11.553...0.0539000.14300.6650113.014audio_featuresspotify:track:6otUjBoNrp27EubqsoYGQxhttps://api.spotify.com/v1/tracks/6otUjBoNrp27...https://api.spotify.com/v1/audio-analysis/6otU...3.4280004
212eVofaQRJvddSUBfcub7GzOceansOceansRY X, Ólafur ArnaldsFalse610.6590.3876-13.172...0.6920000.08390.0779114.989audio_featuresspotify:track:2eVofaQRJvddSUBfcub7Gzhttps://api.spotify.com/v1/tracks/2eVofaQRJvdd...https://api.spotify.com/v1/audio-analysis/2eVo...4.6595504
223PURbsY67tLMyausOABtitKingdoms In ColourFeel Good (feat. Khruangbin)Maribou State, KhruangbinFalse580.5660.7574-8.370...0.8400000.39600.4030102.016audio_featuresspotify:track:3PURbsY67tLMyausOABtithttps://api.spotify.com/v1/tracks/3PURbsY67tLM...https://api.spotify.com/v1/audio-analysis/3PUR...4.4533504
230lK64KWzyyvplNW5dQkmXYVärmdöVärmdöLEOIFalse90.6630.5024-11.988...0.7720000.07110.1180100.008audio_featuresspotify:track:0lK64KWzyyvplNW5dQkmXYhttps://api.spotify.com/v1/tracks/0lK64KWzyyvp...https://api.spotify.com/v1/audio-analysis/0lK6...4.4550674
246buFkhiPTQ03okWeIZvR6EStrange to ExplainWeekend WindWoodsFalse470.5980.6301-10.492...0.3380000.17900.6970108.947audio_featuresspotify:track:6buFkhiPTQ03okWeIZvR6Ehttps://api.spotify.com/v1/tracks/6buFkhiPTQ03...https://api.spotify.com/v1/audio-analysis/6buF...7.2775674
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96 rows × 23 columns

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Khruangbin) Maribou State, Khruangbin False \n", + "23 Värmdö LEOI False \n", + "24 Weekend Wind Woods False \n", + "\n", + " popularity danceability energy key loudness ... instrumentalness \\\n", + "0 0 0.865 0.694 10 -6.358 ... 0.000842 \n", + "1 46 0.449 0.541 11 -10.299 ... 0.000000 \n", + "2 0 0.512 0.550 0 -8.264 ... 0.000839 \n", + "3 62 0.830 0.631 11 -5.238 ... 0.035900 \n", + "4 21 0.403 0.732 9 -7.386 ... 0.379000 \n", + ".. ... ... ... ... ... ... ... \n", + "20 58 0.864 0.385 5 -11.553 ... 0.053900 \n", + "21 61 0.659 0.387 6 -13.172 ... 0.692000 \n", + "22 58 0.566 0.757 4 -8.370 ... 0.840000 \n", + "23 9 0.663 0.502 4 -11.988 ... 0.772000 \n", + "24 47 0.598 0.630 1 -10.492 ... 0.338000 \n", + "\n", + " liveness valence tempo type \\\n", + "0 0.1100 0.6610 103.988 audio_features \n", + "1 0.1700 0.2760 125.156 audio_features \n", + "2 0.1060 0.4800 99.905 audio_features \n", + "3 0.0539 0.8770 128.013 audio_features \n", + "4 0.1140 0.1950 162.576 audio_features \n", + ".. ... ... ... ... \n", + "20 0.1430 0.6650 113.014 audio_features \n", + "21 0.0839 0.0779 114.989 audio_features \n", + "22 0.3960 0.4030 102.016 audio_features \n", + "23 0.0711 0.1180 100.008 audio_features \n", + "24 0.1790 0.6970 108.947 audio_features \n", + "\n", + " uri \\\n", + "0 spotify:track:1YLUxdSfbsXYktpkp1aUvd \n", + "1 spotify:track:57HwKH3pHLeelTkckr94qf \n", + "2 spotify:track:4Dy9SM605DwtyqEHGUj1ZD \n", + "3 spotify:track:290xSzR8Ee9fm82poMg4od \n", + "4 spotify:track:5ySZ6gVWw9XQf1Dxg4gj2M \n", + ".. ... \n", + "20 spotify:track:6otUjBoNrp27EubqsoYGQx \n", + "21 spotify:track:2eVofaQRJvddSUBfcub7Gz \n", + "22 spotify:track:3PURbsY67tLMyausOABtit \n", + "23 spotify:track:0lK64KWzyyvplNW5dQkmXY \n", + "24 spotify:track:6buFkhiPTQ03okWeIZvR6E \n", + "\n", + " track_href \\\n", + "0 https://api.spotify.com/v1/tracks/1YLUxdSfbsXY... \n", + "1 https://api.spotify.com/v1/tracks/57HwKH3pHLee... \n", + "2 https://api.spotify.com/v1/tracks/4Dy9SM605Dwt... \n", + "3 https://api.spotify.com/v1/tracks/290xSzR8Ee9f... \n", + "4 https://api.spotify.com/v1/tracks/5ySZ6gVWw9XQ... \n", + ".. ... \n", + "20 https://api.spotify.com/v1/tracks/6otUjBoNrp27... \n", + "21 https://api.spotify.com/v1/tracks/2eVofaQRJvdd... \n", + "22 https://api.spotify.com/v1/tracks/3PURbsY67tLM... \n", + "23 https://api.spotify.com/v1/tracks/0lK64KWzyyvp... \n", + "24 https://api.spotify.com/v1/tracks/6buFkhiPTQ03... \n", + "\n", + " analysis_url duration_ms \\\n", + "0 https://api.spotify.com/v1/audio-analysis/1YLU... 3.565633 \n", + "1 https://api.spotify.com/v1/audio-analysis/57Hw... 2.984933 \n", + "2 https://api.spotify.com/v1/audio-analysis/4Dy9... 3.643217 \n", + "3 https://api.spotify.com/v1/audio-analysis/290x... 3.713117 \n", + "4 https://api.spotify.com/v1/audio-analysis/5ySZ... 4.186217 \n", + ".. ... ... \n", + "20 https://api.spotify.com/v1/audio-analysis/6otU... 3.428000 \n", + "21 https://api.spotify.com/v1/audio-analysis/2eVo... 4.659550 \n", + "22 https://api.spotify.com/v1/audio-analysis/3PUR... 4.453350 \n", + "23 https://api.spotify.com/v1/audio-analysis/0lK6... 4.455067 \n", + "24 https://api.spotify.com/v1/audio-analysis/6buF... 7.277567 \n", + "\n", + " time_signature \n", + "0 4 \n", + "1 4 \n", + "2 4 \n", + "3 4 \n", + "4 4 \n", + ".. ... \n", + "20 4 \n", + "21 4 \n", + "22 4 \n", + "23 4 \n", + "24 4 \n", + "\n", + "[96 rows x 23 columns]" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "playlists = [playlist_kai_januar_2020, playlist_kai_november_2020, playlist_kai_september_2021]\n", + "playlist_kai_jan20_sep21 = pd.concat(playlists)\n", + "playlist_kai_jan20_sep21" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [], + "source": [ + "music_feature=features_df[['danceability','energy','loudness','speechiness','acousticness','instrumentalness','liveness','valence','tempo','duration_ms']]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Tom Rosenthal is the top artist of these three playlists." + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Tom Rosenthal 3\n", + "Wampire 2\n", + "Calvin Love 2\n", + "OH NO OH MY 2\n", + "This Is The Kit 2\n", + " ..\n", + "Van Morrison 1\n", + "The Spinners 1\n", + "Anderson .Paak 1\n", + "Woods 1\n", + "Editors 1\n", + "Name: artist, Length: 89, dtype: int64" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "playlist_kai_jan20_sep21['artist'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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mean0.6587780.593111-9.4025560.0521440.2757160.2615220.1420670.577017118.9540564.146603
std0.1631940.1262862.5860220.0574520.2854480.3286360.1199170.27125024.2706861.107018
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" + ], + "text/plain": [ + " danceability energy loudness speechiness acousticness \\\n", + "count 18.000000 18.000000 18.000000 18.000000 18.000000 \n", + "mean 0.658778 0.593111 -9.402556 0.052144 0.275716 \n", + "std 0.163194 0.126286 2.586022 0.057452 0.285448 \n", + "min 0.393000 0.385000 -14.561000 0.027200 0.002200 \n", + "25% 0.524750 0.493750 -11.483000 0.036400 0.078600 \n", + "50% 0.704000 0.565000 -8.948000 0.039250 0.133000 \n", + "75% 0.802500 0.669750 -7.491250 0.042750 0.503250 \n", + "max 0.881000 0.872000 -5.238000 0.281000 0.944000 \n", + "\n", + " instrumentalness liveness valence tempo duration_ms \n", + "count 18.000000 18.000000 18.000000 18.000000 18.000000 \n", + "mean 0.261522 0.142067 0.577017 118.954056 4.146603 \n", + "std 0.328636 0.119917 0.271250 24.270686 1.107018 \n", + "min 0.000000 0.049700 0.091300 89.724000 2.984933 \n", + "25% 0.000651 0.087425 0.380250 101.443750 3.317571 \n", + "50% 0.091450 0.104500 0.589500 113.016500 3.690508 \n", + "75% 0.405750 0.119500 0.833750 124.917000 4.608800 \n", + "max 0.908000 0.545000 0.962000 177.956000 6.922883 " + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "music_feature.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\charlotte.stiller\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:1637: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " self._setitem_single_block(indexer, value, name)\n", + "C:\\Users\\charlotte.stiller\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:692: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " iloc._setitem_with_indexer(indexer, value, self.name)\n" + ] + } + ], + "source": [ + "from sklearn.preprocessing import MinMaxScaler\n", + "min_max_scaler = MinMaxScaler()\n", + "music_feature.loc[:]=min_max_scaler.fit_transform(music_feature.loc[:])" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# plot size\n", + "fig=plt.figure(figsize=(12,8))\n", + "\n", + "# convert column names into a list\n", + "categories=list(music_feature.columns)\n", + "# number of categories\n", + "N=len(categories)\n", + "\n", + "# create a list with the average of all features\n", + "value=list(music_feature.mean())\n", + "\n", + "# repeat first value to close the circle\n", + "# the plot is a circle, so we need to \"complete the loop\"\n", + "# and append the start value to the end.\n", + "value+=value[:1]\n", + "# calculate angle for each category\n", + "angles=[n/float(N)*2*3.14159265359 for n in range(N)]\n", + "angles+=angles[:1]\n", + "\n", + "# plot\n", + "plt.polar(angles, value)\n", + "plt.fill(angles,value,alpha=0.3)\n", + "\n", + "# plt.title('Discovery Weekly Songs Audio Features', size=35)\n", + "\n", + "plt.xticks(angles[:-1],categories, size=15)\n", + "plt.yticks(color='grey',size=15)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Very danceable - the next party is just around the corner :-) " + ] + } + ], + "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": "3.8.8" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +}