From 7c79be1a4347a3dccef4bee7239ca2f890c27a56 Mon Sep 17 00:00:00 2001 From: Badr Date: Sat, 12 Oct 2024 13:21:06 -0400 Subject: [PATCH] correcting spotify --- docs/source/examples_business_spotify.rst | 420 +- examples/business/spotify/spotify.ipynb | 8790 +++++++++++---------- 2 files changed, 4644 insertions(+), 4566 deletions(-) diff --git a/docs/source/examples_business_spotify.rst b/docs/source/examples_business_spotify.rst index f3fc9c71e..49c836c0f 100644 --- a/docs/source/examples_business_spotify.rst +++ b/docs/source/examples_business_spotify.rst @@ -3,56 +3,51 @@ Predicting Popularity on Spotify ================================== -This example uses the publicly-available Spotify from Kaggle to predict the popularity of -Polish songs and artists on Spotify. We'll also use a model to group artists -together based on how similar their songs are. +This example uses the publicly-available Spotify from Kaggle to predict the popularity of Polish songs and artists on Spotify. We'll also use a model to group artists together based on how similar their songs are. You can download the Jupyter notebook of this study `here `_. .. note:: We are only using polish artists and a subset of the tracks dataset filtered by a handful of artists. - The "tracks" dataset (tracks.csv) have the following features: -id represents the Id of the track generated by Spotify +Id represents the Id of the track generated by Spotify Numerical: -- **acousticness** (range: [0,1]) -- **danceability** (range: [0,1]) -- **energy** (range: [0,1]) -- **duration_ms** (range: [200000,300000]) -- **instrumentalness** (range: [0,1]) -- **valence** (range: [0,1]) -- **popularity** (range: [0,100]) -- **tempo** (range: [50,150]) -- **liveness** (range: [0,1]) -- **loudness** (range: [-60,0]) -- **speechiness** (range: [0,1]) +- **acousticness** (range: ``[0,1]``) +- **danceability** (range: ``[0,1]``) +- **energy** (range: ``[0,1]``) +- **duration_ms** (range: ``[200000,300000]``) +- **instrumentalness** (range: ``[0,1]``) +- **valence** (range: ``[0,1]``) +- **popularity** (range: ``[0,100]``) +- **tempo** (range: ``[50,150]``) +- **liveness** (range: ``[0,1]``) +- **loudness** (range: ``[-60,0]``) +- **speechiness** (range: ``[0,1]``) Dummy: -- **mode** (0 = Minor, 1 = Major) -- **explicit** (0 = No explicit content and 1 = Explicit content) +- **mode**: (``0 = Minor``, ``1 = Major``) +- **explicit**: (0 = No explicit content and 1 = Explicit content) Categorical: -- **key** - keys on an octave encoded as integers in range [0,11] (C = 0, C# = 1, etc.) -- **timesignature** - predicted time signature -- **artists** - list of contributing artists -- **artists** - list of IDs of contributing artists -- **release_date** - date of release (yyyy-mm-dd) -- **name** - track name +- **key**: keys on an octave encoded as integers in range ``[0,11]`` (``C = 0``, ``C = 1``, etc.) +- **timesignature**: predicted time signature. +- **artists**: list of contributing artists. +- **artists**: list of IDs of contributing artists. +- **release_date**: date of release (yyyy-mm-dd). +- **name**: track name. The "artists" dataset (artists.csv) has the following features: -- **id** - ID of the artist -- **name** - artist name -- **followers** - how many followers the artist has -- **popularity** - popularity of the artists based on their tracks -- **genres** - list of genres covered by the artist's tracks - - +- **id**: ID of the artist. +- **name**: artist name. +- **followers**: how many followers the artist has. +- **popularity**: popularity of the artists based on their tracks. +- **genres**: list of genres covered by the artist's tracks. We will follow the data science cycle (Data Exploration - Data Preparation - Data Modeling - Model Evaluation - Model Deployment) to solve this problem. @@ -83,26 +78,26 @@ You can skip the below cell if you already have an established connection. vp.connect("VerticaDSN") -Create a new schema, "spotify." +Create a new schema, "spotify". .. ipython:: python vp.drop("spotify", method = "schema") vp.create_schema("spotify") - Data Loading ------------- -Load the datasets into the vDataFrame with read_csv() and then view them with display(). +Load the datasets into the ``vDataFrame`` with ``read_csv()`` and then view them with ``display()``. .. code-block:: # load datasets as vDataFrame objects artists = vp.read_csv("artists.csv", schema = "spotify", parse_nrows = 100) tracks = vp.read_csv("tracks.csv" , schema = "spotify", parse_nrows = 100) - display(artists) - display(tracks) + + # Display + artists.head(100) .. ipython:: python :suppress: @@ -112,11 +107,15 @@ Load the datasets into the vDataFrame with read_csv() and then view them with di schema = "spotify", parse_nrows = 100, ) - res = artists + res = artists.head(100) html_file = open("/project/data/VerticaPy/docs/figures/examples_spotify_artists_table.html", "w") html_file.write(res._repr_html_()) html_file.close() +.. code-block:: + + tracks.head(100) + .. raw:: html :file: /project/data/VerticaPy/docs/figures/examples_spotify_artists_table.html @@ -124,7 +123,7 @@ Load the datasets into the vDataFrame with read_csv() and then view them with di :suppress: tracks = vp.read_csv("/project/data/VerticaPy/docs/source/_static/website/examples/data/spotify/tracks.csv",schema = "spotify",parse_nrows = 100) - res = tracks + res = tracks.head(100) html_file = open("/project/data/VerticaPy/docs/figures/examples_spotify_tracks_table.html", "w") html_file.write(res._repr_html_()) html_file.close() @@ -132,7 +131,6 @@ Load the datasets into the vDataFrame with read_csv() and then view them with di .. raw:: html :file: /project/data/VerticaPy/docs/figures/examples_spotify_tracks_table.html - .. warning:: This example uses a sample dataset. For the full analysis, you should consider using the complete dataset. @@ -142,6 +140,7 @@ Since we are only focusing on Polish artists in this subset of data, let us save .. code-block:: polish_artists = artists + # save it to the database polish_artists.to_db('"spotify"."polish_artists"', relation_type = "table") @@ -153,7 +152,6 @@ Since we are only focusing on Polish artists in this subset of data, let us save vp.drop("spotify.polish_artists") polish_artists.to_db('"spotify"."polish_artists"', relation_type = "table") - Data Exploration ----------------- @@ -167,7 +165,7 @@ We can visualize the top 60 most-followed Polish artists with a bar chart. method = "mean", of = "followers", max_cardinality = 50, - width = 800 + width = 800, ) .. ipython:: python @@ -179,7 +177,7 @@ We can visualize the top 60 most-followed Polish artists with a bar chart. method = "mean", of = "followers", max_cardinality = 50, - width = 800 + width = 800, ) fig.write_html("/project/data/VerticaPy/docs/figures/examples_spotify_polish_followers_bar.html") @@ -199,7 +197,7 @@ We can do the same with the most popular tracks. For example, we can graph Monik method = "mean", of = "popularity", max_cardinality = 25, - width = 800 + width = 800, ) .. ipython:: python @@ -212,28 +210,27 @@ We can do the same with the most popular tracks. For example, we can graph Monik method = "mean", of = "popularity", max_cardinality = 25, - width = 800 + width = 800, ) fig.write_html("/project/data/VerticaPy/docs/figures/examples_spotify_brodka_popularity_bar.html") .. raw:: html :file: /project/data/VerticaPy/docs/figures/examples_spotify_brodka_popularity_bar.html -To get an idea of what makes Monika Brodka's songs popular, -let's create a boxplot of the numerical feature distribution of her tracks. +To get an idea of what makes Monika Brodka's songs popular, let's create a boxplot of the numerical feature distribution of her tracks. .. code-block:: ## list of the relevant numerical features numerical_features = [ - 'danceability', - 'energy', - 'speechiness', - 'acousticness', - 'instrumentalness', - 'valence', - 'liveness' - ] + "danceability", + "energy", + "speechiness", + "acousticness", + "instrumentalness", + "valence", + "liveness", + ] # create a boxplot of the above features brodka_tracks.boxplot(columns = numerical_features) @@ -244,14 +241,14 @@ let's create a boxplot of the numerical feature distribution of her tracks. ## list of the relevant numerical features numerical_features = [ - 'danceability', - 'energy', - 'speechiness', - 'acousticness', - 'instrumentalness', - 'valence', - 'liveness' - ] + "danceability", + "energy", + "speechiness", + "acousticness", + "instrumentalness", + "valence", + "liveness", + ] # create a boxplot of the above features fig = brodka_tracks.boxplot(columns = numerical_features) @@ -265,38 +262,38 @@ Timing is a classic factor for success, so let's look at the popularity of Monik .. code-block:: # extract year from the date - brodka_tracks['release_year'] = "year(release_date::date)" + brodka_tracks["release_year"] = "year(release_date::date)" # smooth the popularity using rolling mean brodka_tracks.rolling( - func = 'mean', - columns = 'popularity', + func = "mean", + columns = "popularity", window = (-3, 3), - order_by = 'release_year', - name = 'smoothed_popularity' + order_by = "release_year", + name = "smoothed_popularity", ) # plot the smoothed curve for popularity of her songs - brodka_tracks.plot(ts = 'release_date', columns=['smoothed_popularity']) + brodka_tracks.plot(ts = "release_date", columns=["smoothed_popularity"]) .. ipython:: python :okwarning: :supress: # extract year from the date - brodka_tracks['release_year'] = "year(release_date::date)" + brodka_tracks["release_year"] = "year(release_date::date)" # smooth the popularity using rolling mean brodka_tracks.rolling( - func = 'mean', - columns = 'popularity', + func = "mean", + columns = "popularity", window = (-3, 3), - order_by = 'release_year', - name = 'smoothed_popularity' + order_by = "release_year", + name = "smoothed_popularity", ) # plot the smoothed curve for popularity of her songs - fig = brodka_tracks.plot(ts = 'release_date', columns=['smoothed_popularity']) + fig = brodka_tracks.plot(ts = "release_date", columns = ["smoothed_popularity"]) fig.write_html("/project/data/VerticaPy/docs/figures/examples_spotify_brodka_release_plot.html") .. raw:: html @@ -311,26 +308,26 @@ features change and correlate with each other in Monika's most popular songs. .. code-block:: # extract year from date - tracks['release_year'] = "year(release_date::date)" + tracks["release_year"] = "year(release_date::date)" # get the average of numerical features during the year yearly_aggs = tracks.groupby( - 'release_year', [ - 'AVG(danceability) as danceability', - 'AVG(energy) as energy', - 'AVG(speechiness) AS speechiness', - 'AVG(acousticness) AS acousticness', - 'AVG(instrumentalness) AS instrumentalness', - 'AVG(valence) AS valence', - 'AVG(liveness) AS liveness', + "release_year", [ + "AVG(danceability) as danceability", + "AVG(energy) as energy", + "AVG(speechiness) AS speechiness", + "AVG(acousticness) AS acousticness", + "AVG(instrumentalness) AS instrumentalness", + "AVG(valence) AS valence", + "AVG(liveness) AS liveness", ] ) # plot the cures for numerical features along the different years yearly_aggs.plot( - ts='release_year', - columns=numerical_features + ts = "release_year", + columns = numerical_features, ) .. ipython:: python @@ -339,26 +336,25 @@ features change and correlate with each other in Monika's most popular songs. tracks['release_year'] = "year(release_date::date)" yearly_aggs = tracks.groupby( - 'release_year', [ - 'AVG(danceability) as danceability', - 'AVG(energy) as energy', - 'AVG(speechiness) AS speechiness', - 'AVG(acousticness) AS acousticness', - 'AVG(instrumentalness) AS instrumentalness', - 'AVG(valence) AS valence', - 'AVG(liveness) AS liveness', + "release_year", [ + "AVG(danceability) as danceability", + "AVG(energy) as energy", + "AVG(speechiness) AS speechiness", + "AVG(acousticness) AS acousticness", + "AVG(instrumentalness) AS instrumentalness", + "AVG(valence) AS valence", + "AVG(liveness) AS liveness", ] ) fig = yearly_aggs.plot( - ts='release_year', - columns=numerical_features + ts = "release_year", + columns = numerical_features, ) fig.write_html("/project/data/VerticaPy/docs/figures/examples_spotify_brodka_release_plot.html") .. raw:: html :file: /project/data/VerticaPy/docs/figures/examples_spotify_brodka_release_plot.html - .. code-block:: # correlation of numerical features @@ -440,7 +436,7 @@ Additionally, we manipulate our data a bit to make things easier later on: column = "artists", pattern = ",", method = "count", - name = "nb_singers" + name = "nb_singers", ) polish_tracks["nb_singers"].add(1) @@ -455,7 +451,7 @@ Additionally, we manipulate our data a bit to make things easier later on: column = "artists", pattern = ",", method = "count", - name = "nb_singers" + name = "nb_singers", ) polish_tracks["nb_singers"].add(1) res = polish_tracks @@ -472,23 +468,25 @@ Define a list of predictors and the response, and then save the normalized versi # define predictors and response predictors = [ - 'duration_minute', - # 'release_year', - 'danceability', - 'energy', - 'loudness', - 'speechiness', - 'acousticness', - 'instrumentalness', - 'liveness', - 'valence', - 'artists_followers', - 'artist_popularity', - 'nb_singers' + "duration_minute", + # "release_year", + "danceability", + "energy", + "loudness", + "speechiness", + "acousticness", + "instrumentalness", + "liveness", + "valence", + "artists_followers", + "artist_popularity", + "nb_singers", ] - response = 'popularity' - polish_tracks.normalize(method = "minmax", - columns = predictors) + response = "popularity" + polish_tracks.normalize( + method = "minmax", + columns = predictors, + ) # save the final dataset to the database vp.drop("spotify.polish_tracks_data_final") polish_tracks.to_db('"spotify"."polish_tracks_data_final"', relation_type = "table") @@ -498,50 +496,52 @@ Define a list of predictors and the response, and then save the normalized versi :okwarning: predictors = [ - 'duration_minute', - # 'release_year', - 'danceability', - 'energy', - 'loudness', - 'speechiness', - 'acousticness', - 'instrumentalness', - 'liveness', - 'valence', - 'artists_followers', - 'artist_popularity', - 'nb_singers' + "duration_minute", + # "release_year", + "danceability", + "energy", + "loudness", + "speechiness", + "acousticness", + "instrumentalness", + "liveness", + "valence", + "artists_followers", + "artist_popularity", + "nb_singers", ] - response = 'popularity' - polish_tracks.normalize(method = "minmax", - columns = predictors) + response = "popularity" + polish_tracks.normalize( + method = "minmax", + columns = predictors, + ) vp.drop("spotify.polish_tracks_data_final") polish_tracks.to_db('"spotify"."polish_tracks_data_final"', relation_type = "table") - Machine Learning ----------------- -We can use AutoML to easily get a well-performing model. +We can use ``AutoML`` to easily get a well-performing model. .. ipython:: python # define a random seed so models tested by AutoML produce consistent results vp.set_option("random_state", 2) -AutoML automatically tests several machine learning models and picks the best performing one. +``AutoML`` automatically tests several machine learning models and picks the best performing one. .. ipython:: python :okwarning: from verticapy.machine_learning.vertica.automl import AutoML + # define the model auto_model = AutoML( - 'spotify.automl_spotify_polish', - estimator = 'fast', + "spotify.automl_spotify_polish", + estimator = "fast", preprocess_data = True, stepwise = False, - cv = 2 + cv = 2, ) Train the model. @@ -550,12 +550,11 @@ Train the model. :okwarning: auto_model.fit( - 'spotify.polish_tracks_data_final', + "spotify.polish_tracks_data_final", predictors, response ) - .. code-block:: auto_model.plot() @@ -570,7 +569,7 @@ Train the model. .. raw:: html :file: /project/data/VerticaPy/docs/figures/examples_spotify_automl_plot.html -Extract the best model according to AutoML. From here, we can look at the model type and its hyperparameters. +Extract the best model according to ``AutoML``. From here, we can look at the model type and its hyperparameters. .. ipython:: python @@ -582,14 +581,14 @@ Extract the best model according to AutoML. From here, we can look at the model print(bm_type) print(hyperparams) -Thanks to AutoML, we know best model type and its hyperparameters. Let's create a new model with this information in mind. +Thanks to ``AutoML``, we know best model type and its hyperparameters. Let's create a new model with this information in mind. .. code-block:: from verticapy.machine_learning.vertica import LinearRegression # define the model - rf_model = LinearRegression('spotify.linear_regression_spotify', **hyperparams) + rf_model = LinearRegression("spotify.linear_regression_spotify", **hyperparams) # train the model rf_model.fit(polish_tracks, predictors, response) @@ -597,7 +596,7 @@ Thanks to AutoML, we know best model type and its hyperparameters. Let's create # use the model to predict rf_model.predict( polish_tracks, - name = 'estimated_popularity' + name = "estimated_popularity", ) @@ -606,12 +605,13 @@ Thanks to AutoML, we know best model type and its hyperparameters. Let's create :okwarning: from verticapy.machine_learning.vertica import LinearRegression - if 'C' in hyperparams: - hyperparams.pop('C') - if 'l1_ratio' in hyperparams: - hyperparams.pop('l1_ratio') + + if "C" in hyperparams: + hyperparams.pop("C") + if "l1_ratio" in hyperparams: + hyperparams.pop("l1_ratio") # define the model - rf_model = LinearRegression('spotify.linear_regression_spotify', **hyperparams) + rf_model = LinearRegression("spotify.linear_regression_spotify", **hyperparams) # train the model rf_model.fit(polish_tracks, predictors, response) @@ -619,7 +619,7 @@ Thanks to AutoML, we know best model type and its hyperparameters. Let's create # use the model to predict res = rf_model.predict( polish_tracks, - name = 'estimated_popularity' + name = "estimated_popularity", ) html_file = open("/project/data/VerticaPy/docs/figures/examples_spotify_lr_prediction.html", "w") html_file.write(res._repr_html_()) @@ -646,9 +646,6 @@ View the regression report and the importance of each feature. .. raw:: html :file: /project/data/VerticaPy/docs/figures/examples_spotify_lr_report.html - - - .. code-block:: rf_model.features_importance() @@ -663,17 +660,21 @@ View the regression report and the importance of each feature. .. raw:: html :file: /project/data/VerticaPy/docs/figures/examples_spotify_lr_featrures.html - -To see how our model performs, let's plot the popularity and estimated popularity of -songs by other Polish artists like Brodka and Akcent. +To see how our model performs, let's plot the popularity and estimated popularity of songs by other Polish artists like Brodka and Akcent. .. code-block:: # results for Brodka polish_tracks.search( - "LOWER(artists) LIKE '%brodka%'", - usecols = ['popularity', 'name', 'estimated_popularity']).plot( - ts='name', columns=['popularity', 'estimated_popularity'] + "LOWER(artists) LIKE '%brodka%'", + usecols = [ + "popularity", + "name", + "estimated_popularity", + ], + ).plot( + ts = "name", + columns = ["popularity", "estimated_popularity"], ) .. ipython:: python @@ -681,23 +682,37 @@ songs by other Polish artists like Brodka and Akcent. :okwarning: fig = polish_tracks.search( - "LOWER(artists) LIKE '%brodka%'", - usecols = ['popularity', 'name', 'estimated_popularity']).plot( - ts='name', columns=['popularity', 'estimated_popularity'] + "LOWER(artists) LIKE '%brodka%'", + usecols = [ + "popularity", + "name", + "estimated_popularity", + ], + ).plot( + ts = "name", + columns = ["popularity", "estimated_popularity"], ) fig.write_html("/project/data/VerticaPy/docs/figures/examples_spotify_lr_brodaka_predict_plot.html") .. raw:: html :file: /project/data/VerticaPy/docs/figures/examples_spotify_lr_brodaka_predict_plot.html - .. code-block:: # results for Brodka polish_tracks.search( - "LOWER(artists) LIKE '%akcent%'", - usecols = ['popularity', 'name', 'estimated_popularity']).plot( - ts='name', columns=['popularity', 'estimated_popularity'] + "LOWER(artists) LIKE '%akcent%'", + usecols = [ + "popularity", + "name", + "estimated_popularity", + ], + ).plot( + ts = "name", + columns = [ + "popularity", + "estimated_popularity", + ], ) .. ipython:: python @@ -705,9 +720,18 @@ songs by other Polish artists like Brodka and Akcent. :okwarning: fig = polish_tracks.search( - "LOWER(artists) LIKE '%akcent%'", - usecols = ['popularity', 'name', 'estimated_popularity']).plot( - ts='name', columns=['popularity', 'estimated_popularity'] + "LOWER(artists) LIKE '%akcent%'", + usecols = [ + "popularity", + "name", + "estimated_popularity", + ], + ).plot( + ts = "name", + columns = [ + "popularity", + "estimated_popularity", + ], ) fig.write_html("/project/data/VerticaPy/docs/figures/examples_spotify_lr_akcent_predict_plot.html") @@ -721,23 +745,22 @@ While our tracks don't have an explicit "genre" feature, we can approximate the Let's start by taking the averages of these numerical features for each artist. - .. code-block:: # group by artist artists_features = polish_tracks.groupby( [ - 'id_artists', - 'artists' + "id_artists", + "artists", ], expr=[ - 'AVG(danceability) AS danceability', - 'AVG(energy) AS energy', - 'AVG(speechiness) AS speechiness', - 'AVG(acousticness) AS acousticness', - 'AVG(instrumentalness) AS instrumentalness', - 'AVG(valence) AS valence', - 'AVG(liveness) AS liveness' + "AVG(danceability) AS danceability", + "AVG(energy) AS energy", + "AVG(speechiness) AS speechiness", + "AVG(acousticness) AS acousticness", + "AVG(instrumentalness) AS instrumentalness", + "AVG(valence) AS valence", + "AVG(liveness) AS liveness", ] ) @@ -750,17 +773,17 @@ Let's start by taking the averages of these numerical features for each artist. artists_features = polish_tracks.groupby( [ - 'id_artists', - 'artists' + "id_artists", + "artists", ], expr=[ - 'AVG(danceability) AS danceability', - 'AVG(energy) AS energy', - 'AVG(speechiness) AS speechiness', - 'AVG(acousticness) AS acousticness', - 'AVG(instrumentalness) AS instrumentalness', - 'AVG(valence) AS valence', - 'AVG(liveness) AS liveness' + "AVG(danceability) AS danceability", + "AVG(energy) AS energy", + "AVG(speechiness) AS speechiness", + "AVG(acousticness) AS acousticness", + "AVG(instrumentalness) AS instrumentalness", + "AVG(valence) AS valence", + "AVG(liveness) AS liveness", ] ) @@ -774,7 +797,7 @@ Let's start by taking the averages of these numerical features for each artist. .. raw:: html :file: /project/data/VerticaPy/docs/figures/examples_spotify_artists_features.html -Grouping means clustering, so we use an elbow curve to find a suitable number of clusters. +Grouping means clustering, so we use an ``elbow`` curve to find a suitable number of clusters. .. ipython:: python :okwarning: @@ -789,7 +812,7 @@ Grouping means clustering, so we use an elbow curve to find a suitable number of "acousticness", "instrumentalness", "liveness", - "valence" + "valence", ] # elbow curve @@ -797,7 +820,7 @@ Grouping means clustering, so we use an elbow curve to find a suitable number of '"spotify"."artists_features"', preds, n_cluster = (1, 20), - show = True + show = True, ) .. code-block:: @@ -814,7 +837,7 @@ Grouping means clustering, so we use an elbow curve to find a suitable number of .. raw:: html :file: /project/data/VerticaPy/docs/figures/examples_spotify_lr_elbow.html -Let's define and use the Vertica k-means algorithm to create a model that can group artists together. +Let's define and use the Vertica ``k-means`` algorithm to create a model that can group artists together. .. ipython:: python :okwarning: @@ -824,7 +847,7 @@ Let's define and use the Vertica k-means algorithm to create a model that can gr # define k-means model = KMeans( '"spotify"."KMeans_spotify"', - n_cluster = 7 + n_cluster = 7, ) We can train our new model on the "artists_features" relation we saved earlier. @@ -834,7 +857,7 @@ We can train our new model on the "artists_features" relation we saved earlier. # train the model model.fit( '"spotify"."artists_features"', - X = preds + X = preds, ) Plot the result of the k-means algoritm: @@ -853,7 +876,6 @@ Plot the result of the k-means algoritm: .. raw:: html :file: /project/data/VerticaPy/docs/figures/examples_spotify_cluster_plot.html - .. ipython:: python # predict the genres @@ -866,9 +888,9 @@ Plot the result of the k-means algoritm: "acousticness", "instrumentalness", "liveness", - "valence" + "valence", ], - name="pred_genres" + name = "pred_genres", ) Let's see how our model groups these artists together: @@ -876,13 +898,13 @@ Let's see how our model groups these artists together: .. code-block:: # observe the results - pred_genres['artists','pred_genres'].sort({'pred_genres':'desc'}) + pred_genres["artists", "pred_genres"].sort({"pred_genres": "desc"}) .. ipython:: python :suppress: :okwarning: - res = pred_genres['artists','pred_genres'].sort({'pred_genres':'desc'}) + res = pred_genres["artists", "pred_genres"].sort({"pred_genres": "desc"}) html_file = open("/project/data/VerticaPy/docs/figures/examples_spotify_pred_genres.html", "w") html_file.write(res._repr_html_()) html_file.close() @@ -893,6 +915,4 @@ Let's see how our model groups these artists together: Conclusion ----------- -We were able to predict the popularity Polish songs with a RandomForestRegressor -model suggested by AutoML. We then created a k-means model to group artists -into "genres" (clusters) based on the feature-commonalities in their tracks. \ No newline at end of file +We were able to predict the popularity Polish songs with a ``RandomForestRegressor`` model suggested by ``AutoML``. We then created a ``k-means`` model to group artists into "genres" (clusters) based on the feature-commonalities in their tracks. \ No newline at end of file diff --git a/examples/business/spotify/spotify.ipynb b/examples/business/spotify/spotify.ipynb index 3bf885930..c77ef765b 100644 --- a/examples/business/spotify/spotify.ipynb +++ b/examples/business/spotify/spotify.ipynb @@ -87,6 +87,7 @@ "outputs": [], "source": [ "import verticapy as vp\n", + "\n", "%load_ext verticapy.sql" ] }, @@ -215,845 +216,857 @@ { "cell_type": "code", "execution_count": 6, - "id": "06c2758a", + "id": "923e564c", "metadata": {}, "outputs": [ { "data": { "text/html": [ - "
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Rows: 1-100 | Columns: 5
" + "
Abc
id
Varchar(44)
123
followers
Numeric(13)
Abc
Varchar(206)
Abc
Varchar(56)
123
popularity
Integer
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1001Kjs5u8GQf6zCFdTj6SI9E549301.068
Rows: 1-100 | Columns: 5
" ], "text/plain": [ "None id followers genres \\\\\n", - "1 004reCzVFOidvBuYrYia9Y 12726.0 ['polish punk'] \\\\\n", - "2 00drc18J6PkIXn24widBC5 3.0 ['polish ambient'] \\\\\n", - "3 00ekfPE5ZS3NwF8H8o8GBk 17574.0 ['disco polo'] \\\\\n", - "4 018gIUaP08hROTOiVdiEQ3 584.0 ['polish black metal'] \\\\\n", - "5 01BlTZ696EkKe6xr56Gu6G 362.0 ['polish free jazz'] \\\\\n", - "6 01TgMAgIALWvVXlKjUwpfn 1063.0 ['polish alternative rock', 'polish p... \\\\\n", - "7 0244q9rIqAIzBFXKNNRN6O 27393.0 ['classic polish pop', 'polish pop'] \\\\\n", - "8 02Cq85QmaYHDi4dW7AxTRZ 748.0 ['polish electronica'] \\\\\n", - "9 02ESuuto8Jwyo4PeiJ1Xim 149.0 ['polish synthpop'] \\\\\n", - "10 02JmHOSFJi2bLjGnO274di 8817.0 ['polish punk', 'szanty'] \\\\\n", - "11 02LrsTMdnHVvKmXxN0epQF 753.0 ['deep soundtrack', 'polish synthpop'] \\\\\n", - "12 02eZEXslMzAjHDkygNJHSX 8010.0 ['polish trap'] \\\\\n", - "13 02keDoJak6YO12KBJFMFNm 1873.0 ['polish punk', 'polish reggae'] \\\\\n", - "14 02tQ309SzZZ0bYs2yyO60G 11734.0 ['polish hip hop'] \\\\\n", - "15 0338weYyACbkc5ERuLnFTa 270.0 ['classic polish pop'] \\\\\n", - "16 033WIygOyXwUjc1vfCGxJ2 126.0 ['polish black metal'] \\\\\n", - "17 03Dy3XKBUsC3vJLCuF0T7I 152.0 ['polish jazz'] \\\\\n", - "18 03FgbE2vKKVEFBFHi8IfJG 184761.0 ['polish hip hop'] \\\\\n", - "19 03KLzHVK6la8dVop1iVI5x 63817.0 ['poezja spiewana', 'polish alternati... \\\\\n", - "20 03ZzgzybQr8UyvWCMSCvRy 1363.0 ['polish noise rock'] \\\\\n", - "21 03jLJnyfZXs1ssrIALfGRm 2633.0 ['classic polish pop'] \\\\\n", - "22 03ohDYwWFrXfgp0VEtSTiF 706.0 ['polish thrash metal'] \\\\\n", - "23 03qKjVTzyKc3SyTjHaOpFc 2376.0 ['neo-progressive', 'polish prog'] \\\\\n", - "24 03rREATXGWcD2CfG3OXDZY 10155.0 ['polish alternative rap', 'polish hi... \\\\\n", - "25 03wQEnXSEAI6GmOKZ90G25 1597.0 ['historic piano performance', 'polis... \\\\\n", - "26 03xKZpOUZOQjf7g5WBN4ee 3676.0 ['polish alternative', 'polish indie'] \\\\\n", - "27 03yP3BHBnpGyvddEoIGnsx 2089.0 ['polish black metal'] \\\\\n", - "28 04Lio76CKJCMPbK5hV6J4w 1876.0 ['black noise', 'polish black metal',... \\\\\n", - "29 04Loj16dRX1yZodeEQlCOv 308.0 ['polish jazz'] \\\\\n", - "30 04WxKoI0kS5JclvQ8rn8qp 13.0 ['polish contemporary classical'] \\\\\n", - "31 04bDWf1u7HxKdskC3N2nIk 27127.0 ['polish metal', 'polish punk', 'poli... \\\\\n", - "32 05AVHcWP9DF6y6LEU845uz 1545.0 ['classic polish pop'] \\\\\n", - "33 05Fgqq7GfWeNol1TR5H3og 15868.0 ['polish pop'] \\\\\n", - "34 05UsyksBcAUVdfyREMxbDm 294.0 ['disco polo'] \\\\\n", - "35 063D0MKbIbbBjKgtYRGBga 7458.0 ['polish alternative', 'polish electr... \\\\\n", - "36 0690wuO0NVERuqxuoi2mTF 319.0 ['polish ambient', 'polish experiment... \\\\\n", - "37 06O52v4thQuBoLC6jWatGW 21.0 ['polish free jazz'] \\\\\n", - "38 06UcKJxYJXthEwn0c8XOCt 11024.0 ['dark black metal', 'polish black me... \\\\\n", - "39 06wBGqhkbyUAtVNMbbcK1x 607.0 ['polish folk'] \\\\\n", - "40 070tdNOiP3pIsGlqNfVkG3 86130.0 ['polish hip hop'] \\\\\n", - "41 072HrG3T5BaaBj4YhKIkxv 1166.0 ['polish alternative rock'] \\\\\n", - "42 07ILo13zpakvXxTL3VtqwS 540.0 ['disco polo'] \\\\\n", - "43 07PJCYnjHeYanDnFnUALU4 269.0 ['historic piano performance', 'polis... \\\\\n", - "44 098RsUTij7grC7evZUhWwA 720.0 ['polish trap'] \\\\\n", - "45 09MjLGtslj39ILxA1MqUny 556.0 ['polish hip hop'] \\\\\n", - "46 09ScR35g0VzipHacuPtXZd 440.0 ['polish modern jazz'] \\\\\n", - "47 09Z3SI4GkhYjpCB6884vC8 10395.0 ['polish alternative', 'polish indie'... \\\\\n", - "48 09j4UTVH7vk7fVfVB71roU 348.0 ['polish indie', 'polish indie rock'] \\\\\n", - "49 0AEQNlJAZeghMaFyIYfrQG 138546.0 ['polish hip hop'] \\\\\n", - "50 0AYJ3eg4zKi9ilGrhVaINs 2186.0 ['polish jazz', 'polish modern jazz'] \\\\\n", - "51 0AZgkXW6n0zfyOhVAnIopA 1109.0 ['polish alternative'] \\\\\n", - "52 0At3wjxYzZL9WwqbFR0JL8 24.0 ['polish jazz'] \\\\\n", - "53 0BBB9DjvskQV0oReJMxTP1 30889.0 ['polish alternative rap'] \\\\\n", - "54 0BQIhJ61mCyaOrVrMJ7e8k 5.0 ['polish ambient'] \\\\\n", - "55 0CEw36eWG0dYKCXOX8eUoO 77804.0 ['polish pop'] \\\\\n", - "56 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['disco polo'] \\\\\n", - "71 0FbccBQBb69lfv4arbt6kX 9237.0 ['polish alternative', 'polish indie'] \\\\\n", - "72 0G2VUqbZ4C28aN9y41Wp3G 1186.0 ['polish jazz'] \\\\\n", - "73 0G6miz5dLrc3NZWi4ZYdJK 2813.0 ['disco polo'] \\\\\n", - "74 0GF5CJ7nKXsMTiWHK4ZQJN 30925.0 ['polish pop'] \\\\\n", - "75 0GPJYkHJm0Fpbhjovpm1h1 2261.0 ['polish synthpop'] \\\\\n", - "76 0GPfyyiTlLdG6rQthueRBM 682.0 ['disco polo'] \\\\\n", - "77 0GQZc3zcll9HXIVaUA1XzJ 11211.0 ['polish reggae'] \\\\\n", - "78 0Gfk7Ww29CWVyrnkqC4KUt 7.0 ['polish punk'] \\\\\n", - "79 0Gk98lHv6LlqbWPwdMiga2 247229.0 ['polish alternative', 'polish pop'] \\\\\n", - "80 0GnO5BjJfHFwkesoObGU36 61.0 ['polish modern jazz'] \\\\\n", - "81 0GsCeqHAG63k8CRj1NH8e4 164.0 ['polish alternative rock', 'polish i... \\\\\n", - "82 0GxARImYCmCNz0v04YjPq2 179.0 ['polish indie'] \\\\\n", - "83 0GykMtlKoc68Hj2jwZLXul 79213.0 ['classic polish pop', 'polish altern... \\\\\n", - "84 0HC5DGqdUzXorIXUudkeWG 1805.0 ['polish classical', 'post-romantic e... \\\\\n", - "85 0HLMuuBFA7R4boMxVl9QgQ 9967.0 ['polish alternative', 'polish indie'] \\\\\n", - "86 0HTub0NhKSRgggtmJBP9aR 59.0 ['polish techno'] \\\\\n", - "87 0HZL4dV60t13CHasIHwaLP 385.0 ['polish post-rock', 'poznan indie'] \\\\\n", - "88 0HhejlCvg1WCO9nXNZGEkc 144.0 ['polish experimental electronic'] \\\\\n", - "89 0Hob9LUr2x0SULSZjuf6li 10701.0 ['disco polo'] \\\\\n", - "90 0Id5ZU9SxHcgE32nfJMTbh 259.0 ['polish trap'] \\\\\n", - "91 0It4rGfBk31UDyK9x6uZvP 3056.0 ['melodic black metal', 'polish black... \\\\\n", - "92 0IuXBtCmOjyRjzbfJmfKHa 13.0 ['polish ambient'] \\\\\n", - "93 0Jl6TFKAJR7zIv2kvA1RNf 60054.0 ['polish pop'] \\\\\n", - "94 0K0Sa7amVwCmQKz7ZHRRim 3005.0 ['polish pop'] \\\\\n", - "95 0KNOQSBwQim4GXpZHekrvu 1728.0 ['polish trap'] \\\\\n", - "96 0KTn3DOb57GcGjPoA09ABL 4.0 ['polish techno'] \\\\\n", - "97 0KZLEvrZHdqVDKdclXRVK0 7.0 ['polish techno'] \\\\\n", - "98 0KirHnU7pIfeMYWSJ6xm8I 1309.0 ['polish blues'] \\\\\n", - "99 0Ks3WKQ64ZmWa3QkbbeCbj 129.0 ['polish indie'] \\\\\n", - "100 0LX2VNf5w4iOHW1yyIqb74 1016980.0 ['polish hip hop', 'polish trap'] \\\\\n", + "1 00drc18J6PkIXn24widBC5 3.0 ['polish ambient'] \\\\\n", + "2 02LrsTMdnHVvKmXxN0epQF 753.0 ['deep soundtrack', 'polish synthpop'] \\\\\n", + "3 02eZEXslMzAjHDkygNJHSX 8010.0 ['polish trap'] \\\\\n", + "4 033WIygOyXwUjc1vfCGxJ2 126.0 ['polish black metal'] \\\\\n", + "5 03ohDYwWFrXfgp0VEtSTiF 706.0 ['polish thrash metal'] \\\\\n", + "6 063D0MKbIbbBjKgtYRGBga 7458.0 ['polish alternative', 'polish electr... \\\\\n", + "7 0690wuO0NVERuqxuoi2mTF 319.0 ['polish ambient', 'polish experiment... \\\\\n", + "8 06UcKJxYJXthEwn0c8XOCt 11024.0 ['dark black metal', 'polish black me... \\\\\n", + "9 09Z3SI4GkhYjpCB6884vC8 10395.0 ['polish alternative', 'polish indie'... \\\\\n", + "10 0AYJ3eg4zKi9ilGrhVaINs 2186.0 ['polish jazz', 'polish modern jazz'] \\\\\n", + "11 0At3wjxYzZL9WwqbFR0JL8 24.0 ['polish jazz'] \\\\\n", + "12 0BBB9DjvskQV0oReJMxTP1 30889.0 ['polish alternative rap'] \\\\\n", + "13 0D5kXlS7UOApMpTyuSrFAW 40370.0 ['polish punk', 'polish rock', 'pozna... \\\\\n", + "14 0EQaqT3oKtxAGR0Y5c1Jme 3572.0 ['polish jazz'] \\\\\n", + "15 0Emf6MyFoCjKazTqoaUu6T 1107.0 ['polish jazz'] \\\\\n", + "16 0G2VUqbZ4C28aN9y41Wp3G 1186.0 ['polish jazz'] \\\\\n", + "17 0GF5CJ7nKXsMTiWHK4ZQJN 30925.0 ['polish pop'] \\\\\n", + "18 0GPJYkHJm0Fpbhjovpm1h1 2261.0 ['polish synthpop'] \\\\\n", + "19 0GnO5BjJfHFwkesoObGU36 61.0 ['polish modern jazz'] \\\\\n", + "20 0GxARImYCmCNz0v04YjPq2 179.0 ['polish indie'] \\\\\n", + "21 0GykMtlKoc68Hj2jwZLXul 79213.0 ['classic polish pop', 'polish altern... \\\\\n", + "22 0Hob9LUr2x0SULSZjuf6li 10701.0 ['disco polo'] \\\\\n", + "23 0IuXBtCmOjyRjzbfJmfKHa 13.0 ['polish ambient'] \\\\\n", + "24 0MGE7m2KV6Db6jOZFy93aD 140674.0 ['classic polish pop', 'poezja spiewa... \\\\\n", + "25 0Oq1xHw1LNRQ3ANiwZt3Ph 772.0 ['polish death metal'] \\\\\n", + "26 0PN0H94fqF9G9FiJrw1R3Q 2551.0 ['polish hip hop'] \\\\\n", + "27 0QR764k0D36npmTMWx5bft 592968.0 ['polish hip hop', 'polish trap'] \\\\\n", + "28 0RGqYHpCdjYsgMDeDYVSmm 4953.0 ['polish alternative rap'] \\\\\n", + "29 0RfWjL7edmNiMbYDEi2pP2 2422.0 ['polish alternative rock'] \\\\\n", + "30 0SDrlYVunFnYysq5m42rC1 534.0 ['polish electronica'] \\\\\n", + "31 0SxiQwgMtIXFRmIwLgKq2k 469.0 ['polish hip hop'] \\\\\n", + "32 0TuKUQF4NwLBWN7sibSBu5 592.0 ['polish punk'] \\\\\n", + "33 0TwM0vzeyhAMTegVdIq8rx 9313.0 ['chamber folk', 'polish alternative'] \\\\\n", + "34 0U4PBLO0Sstp9gXxMh4TUU 245.0 ['polish blues'] \\\\\n", + "35 0UF823aEz8Kqsf0LwQwYkL 849.0 ['polish jazz'] \\\\\n", + "36 0UKQxbhQLlpTNPhw6Cp4Sl 1539.0 ['polish jazz'] \\\\\n", + "37 0V6p8nX4l2BQ68bjrZ4EPf 98368.0 ['polish punk'] \\\\\n", + "38 0VH4jCA2Gt2WkfYn7zIBUK 318.0 ['polish reggae'] \\\\\n", + "39 0VpXPTuw4wRvor9ZZq1hbB 62959.0 ['polish pop'] \\\\\n", + "40 0WZxQOkr6LVnYYSEA6v2oA 757.0 ['polish alternative rap'] \\\\\n", + "41 0YYxsW13yGiA2e80fu4VIA 82804.0 ['polish alternative', 'polish pop'] \\\\\n", + "42 0ZBpILo0t843hKaw2jgVzm 246.0 ['polish post-rock'] \\\\\n", + "43 0ZXDvZqBzwZLsHRXhuTbpR 206075.0 ['polish pop'] \\\\\n", + "44 0aQdei01h0utRbgPvYBpQH 1726.0 ['disco polo'] \\\\\n", + "45 0agLQQe1W7jkJPXN3bI0sU 1689.0 ['polish reggae'] \\\\\n", + "46 0bP2aOqJBwjWEvA6MrKD7i 257.0 ['polish indie rock'] \\\\\n", + "47 0cok0udh8093N9RTG2BSNV 3735.0 ['polish alternative rap'] \\\\\n", + "48 0dJ5KNObzuV2aK76ucVV1l 38411.0 ['polish folk metal', 'polish metal',... \\\\\n", + "49 0e3vm4qeNHWvUzjyocIbBq 934.0 ['polish metal'] \\\\\n", + "50 0eyIohBjpkL2zl5TJbGnTC 79.0 ['disco polo'] \\\\\n", + "51 0fjBJAeBASIOe0LsONiaVL 1024.0 ['polish experimental', 'polish noise... \\\\\n", + "52 0gGAo7qaMlnNcngFKl3myA 10041.0 ['classic polish pop', 'poezja spiewa... \\\\\n", + "53 0gOwRicMmlIZsHeAMXRhFS 18894.0 ['polish trap'] \\\\\n", + "54 0hHp1yLqUUMEMmrtx9lJua 24589.0 ['polish hip hop', 'polish trap'] \\\\\n", + "55 0klnXt9e0AfPQVFpKq9XH9 556.0 ['polish experimental', 'polish noise... \\\\\n", + "56 0mPwQtcfSfJTDRp8WW0Qzv 371.0 ['polish alternative'] \\\\\n", + "57 0ov3NwkivwP03icKu8jQBy 15981.0 ['polish alternative rock', 'polish p... \\\\\n", + "58 0p5YayfdhmkAd0rtiu6mlP 10644.0 ['classic polish pop'] \\\\\n", + "59 0pPojVZ5STREV6CWdiZxQp 1313.0 ['polish alternative', 'polish altern... \\\\\n", + "60 0qp4NhoMGGrzCtWu4CkEsE 29108.0 ['polish hardcore', 'polish punk'] \\\\\n", + "61 0rP5p0yoDQbR6P5Yxbb05Y 2103.0 ['polish punk', 'polish reggae'] \\\\\n", + "62 0s9uKGVQnXFnWvXxBW0WJa 3896.0 ['polish punk', 'polish reggae'] \\\\\n", + "63 0sHLfY4lPndXOBM1xwj62G 50.0 ['polish death metal'] \\\\\n", + "64 0sKdZaAhTTobH1I6OHB2tY 29215.0 ['polish hip hop'] \\\\\n", + "65 0uSvJ4VrevOt9qkOM8TljE 144.0 ['polish experimental', 'polish noise... \\\\\n", + "66 0uYix4krQWE2zDQO17Shlu 253.0 ['polish modern jazz'] \\\\\n", + "67 0vyk3V4Aqior26kicJPsoy 17.0 ['polish experimental electronic'] \\\\\n", + "68 0w64dXwb17ICltM1oyeePF 3501.0 ['polish ambient', 'polish electronica'] \\\\\n", + "69 0wDaCF2sYnSECH0XQ1oEKh 74.0 ['polish ambient'] \\\\\n", + "70 0x2yGzKouDBJ3Zh50HihEO 85.0 ['polish folk'] \\\\\n", + "71 0yPYc2FYG8meYkcIEaRJ0r 181.0 ['disco polo'] \\\\\n", + "72 0ySTqxzTMONJoEvj8MkULW 33.0 ['polish black metal'] \\\\\n", + "73 0zo109NM3S7CqHpvlXwqEN 25448.0 ['polish techno', 'raw techno'] \\\\\n", + "74 10iF348LBI6gOnLue1qnG5 15672.0 ['polish alternative rap', 'polish hi... \\\\\n", + "75 10iwq8N2ktHK5XwvOmbUE6 225.0 ['polish modern jazz'] \\\\\n", + "76 124sGtDIjkbuOt1uDcZ2Lz 3808.0 ['polish ambient'] \\\\\n", + "77 131bNZOisbe6CP8PnBNeaB 5251.0 ['polish pop'] \\\\\n", + "78 13XggX75z0Hk0VNvOuTJoB 24354.0 ['brutal death metal', 'death metal',... \\\\\n", + "79 14YzutUdMwS9yTnI0IFBaD 54586.0 ['compositional ambient', 'neo-classi... \\\\\n", + "80 15LsRgSmN0t8VLcsUFYW5J 92833.0 ['black metal', 'polish black metal',... \\\\\n", + "81 16Pd9XZrfoLM74GGR0VVrY 110.0 ['polish ambient'] \\\\\n", + "82 17uBgxZCZw8onXi8yahFtq 4643.0 ['polish metal'] \\\\\n", + "83 183C4P5B8pmW1zmI4himpF 31103.0 ['polish alternative rap', 'polish hi... \\\\\n", + "84 1AqZBFOsmjh656TvqtDcGr 187.0 ['polish post-punk'] \\\\\n", + "85 1BF0aa62IknlGAF8zDEJ9L 5562.0 ['melodic death metal', 'polish death... \\\\\n", + "86 1BmEPjXHyBgwuCPsQTmChB 3064.0 ['disco polo'] \\\\\n", + "87 1CEONobXawu0XPgPhgTD5a 60878.0 ['polish hip hop'] \\\\\n", + "88 1DM6hiVCSx27KbkORhC1kC 69.0 ['deep symphonic black metal', 'polis... \\\\\n", + "89 1DViThfGuJuJZHGGd9zclE 12756.0 ['polish reggae'] \\\\\n", + "90 1De6ncCXtVKWkbrgNL3nqt 392.0 ['polish punk'] \\\\\n", + "91 1EzvfumDDDz3rkI2EE1fXo 14437.0 ['black metal', 'pagan black metal', ... \\\\\n", + "92 1F2IODAEO0rjZHY1qmtd0N 144.0 ['polish punk'] \\\\\n", + "93 1GEUSlrLX2UTFwb70oBKI8 89.0 ['polish post-punk'] \\\\\n", + "94 1GQSVoAW34pw29ugWtjDjM 30.0 ['polish techno'] \\\\\n", + "95 1GRpnNhXWlNMgnFf3NqEjv 16389.0 ['polish hip hop'] \\\\\n", + "96 1Ga4875GerJjwcX7lXpHBT 35.0 ['polish techno'] \\\\\n", + "97 1HS9CtXIY0zwXbl8Dh3vJu 2404.0 ['polish folk'] \\\\\n", + "98 1I1ssMo5ZvJXkpII1dwjCV 10.0 ['polish early music'] \\\\\n", + "99 1IWG2vK6UbbxYn8EPJ4c5y 178.0 ['polish hardcore'] \\\\\n", + "100 1Kjs5u8GQf6zCFdTj6SI9E 549301.0 ['polish hip hop', 'polish trap'] \\\\\n", "None name popularity \n", - "1 Zielone Żabki 27 \n", - "2 Nasoshnik 0 \n", - "3 Mig 47 \n", - "4 Massemord 8 \n", - "5 Mazzoll 3 \n", - "6 Radio Bagdad 9 \n", - "7 Ryszard Rynkowski 40 \n", - "8 Evorevo 9 \n", - "9 Polpo Motel 1 \n", - "10 Spięty 31 \n", - "11 Andrzej Korzyñski 22 \n", - "12 Popkiller Młode Wilki 5 26 \n", - "13 Skampararas 15 \n", - "14 Buczer 30 \n", - "15 Iwona Loranc 17 \n", - "16 Demonic Slaughter 0 \n", - "17 Chromosomos 1 \n", - "18 Chada 55 \n", - "19 Natalia Przybysz 50 \n", - "20 Zwidy 14 \n", - "21 Krzysztof Daukszewicz 22 \n", - "22 RAGEHAMMER 9 \n", - "23 Millenium 22 \n", - "24 Bober 44 \n", - "25 Josef Hofmann 15 \n", - "26 Sonar 30 \n", - "27 Over the Voids... 16 \n", - "28 Thaw 5 \n", - "29 Andrzej Trzaskowski 1 \n", - "30 Boleslaw Szabelski 0 \n", - "31 Acid Drinkers 37 \n", - "32 Mariusz Lubomski 15 \n", - "33 Honorata Skarbek 35 \n", - "34 Cassel 11 \n", - "35 Baasch 36 \n", - "36 Mirt 4 \n", - "37 Magnolia Acoustic Quartet 0 \n", - "38 Blaze of Perdition 20 \n", - "39 Krzikopa 8 \n", - "40 Bonus RPK 51 \n", - "41 Agressiva 69 8 \n", - "42 Andre$ 10 \n", - "43 Raoul Koczalski 19 \n", - "44 SOSO 31 \n", - "45 Bezimienni 7 \n", - "46 Pawel Kaczmarczyk 7 \n", - "47 Muchy 25 \n", - "48 Iowa Super Soccer 1 \n", - "49 SB Maffija 61 \n", - "50 Marek Napiórkowski 18 \n", - "51 LUNA 33 \n", - "52 Tomek Sowinski and the Collective Imp... 0 \n", - "53 Jano Polska Wersja 45 \n", - "54 Matowy 0 \n", - "55 Agnieszka Chylinska 47 \n", - "56 Wojciech Świtała 7 \n", - "57 Obara International 0 \n", - "58 Nmls 0 \n", - "59 Luxtorpeda 39 \n", - "60 Xantotol 4 \n", - "61 Dianoya 0 \n", - "62 Deriglasoff 18 \n", - "63 This Cold 0 \n", - "64 Deys 53 \n", - "65 Komeda Quintet 11 \n", - "66 1984 4 \n", - "67 Adam Makowicz 8 \n", - "68 TSA 31 \n", - "69 Albo Inaczej 45 \n", - "70 Bartek Wrona 5 \n", - "71 Ofelia 36 \n", - "72 Jerzy Milian 17 \n", - "73 CamaSutra 35 \n", - "74 Beata Kozidrak 46 \n", - "75 Felicjan Andrzejczak 41 \n", - "76 Malibu 26 \n", - "77 Tabu 32 \n", - "78 Schizma 0 \n", - "79 Paweł Domagała 50 \n", - "80 Wojciech Majewski 1 \n", - "81 We Call It a Sound 0 \n", - "82 Materac 1 \n", - "83 Nosowska 49 \n", - "84 Leopold Godowsky 29 \n", - "85 Lilly Hates Roses 29 \n", - "86 Daniel Stetting 0 \n", - "87 Beyond the Event Horizon 4 \n", - "88 Wudec 1 \n", - "89 Power Play 42 \n", - "90 JonyPapa 19 \n", - "91 Christ Agony 13 \n", - "92 Ovvoid 0 \n", - "93 Patrycja Markowska 40 \n", - "94 Marcin Rozynek 29 \n", - "95 esceh 47 \n", - "96 Mooslip 0 \n", - "97 Damian Malec 0 \n", - "98 Nocna Zmiana Bluesa 12 \n", - "99 Newest Zealand 0 \n", - "100 Bedoes 73 \n", + "1 Nasoshnik 0 \n", + "2 Andrzej Korzyñski 22 \n", + "3 Popkiller Młode Wilki 5 26 \n", + "4 Demonic Slaughter 0 \n", + "5 RAGEHAMMER 9 \n", + "6 Baasch 36 \n", + "7 Mirt 4 \n", + "8 Blaze of Perdition 20 \n", + "9 Muchy 25 \n", + "10 Marek Napiórkowski 18 \n", + "11 Tomek Sowinski and the Collective Imp... 0 \n", + "12 Jano Polska Wersja 45 \n", + "13 Luxtorpeda 39 \n", + "14 Komeda Quintet 11 \n", + "15 Adam Makowicz 8 \n", + "16 Jerzy Milian 17 \n", + "17 Beata Kozidrak 46 \n", + "18 Felicjan Andrzejczak 41 \n", + "19 Wojciech Majewski 1 \n", + "20 Materac 1 \n", + "21 Nosowska 49 \n", + "22 Power Play 42 \n", + "23 Ovvoid 0 \n", + "24 Marek Grechuta 49 \n", + "25 Valkenrag 3 \n", + "26 Hellfield 44 \n", + "27 Żabson 69 \n", + "28 Hans Solo 37 \n", + "29 Tymon & The Transistors 16 \n", + "30 Palmer Eldritch 7 \n", + "31 Diox / The Returners 0 \n", + "32 Fort BS 8 \n", + "33 Lor 41 \n", + "34 Daddy's Cash 4 \n", + "35 Zbigniew Namysłowski Quartet 4 \n", + "36 Jarek Smietana 15 \n", + "37 Kazik 47 \n", + "38 Lion Vibrations 0 \n", + "39 BARANOVSKI 53 \n", + "40 OER 10 \n", + "41 Fisz Emade Tworzywo 49 \n", + "42 Fobia Inc. 2 \n", + "43 Cleo 52 \n", + "44 Impuls 11 \n", + "45 Pajujo 16 \n", + "46 Poradnia G 3 \n", + "47 Hukos 33 \n", + "48 Laboratorium Pieśni 40 \n", + "49 Lux Perpetua 3 \n", + "50 Jago Young 4 \n", + "51 BNNT 4 \n", + "52 Hanna Banaszak 29 \n", + "53 Mlodyskiny 41 \n", + "54 Bedoes & Kubi Producent 31 \n", + "55 Ugory 5 \n", + "56 ATLVNTA 29 \n", + "57 Dr Misio 38 \n", + "58 Izabela Trojanowska 35 \n", + "59 Biały Tunel 27 \n", + "60 KSU 40 \n", + "61 Alians 12 \n", + "62 Podwórkowi Chuligani 22 \n", + "63 Black Mad Lice 1 \n", + "64 Rahim 41 \n", + "65 Królestwo 0 \n", + "66 Mateusz Smoczynski 10 \n", + "67 Ambot 0 \n", + "68 Hatti Vatti 30 \n", + "69 Souvenir de Tanger 0 \n", + "70 Się Gra 0 \n", + "71 Claudia Chwołka; Kasia Chwołka 13 \n", + "72 Tobc 0 \n", + "73 VTSS 40 \n", + "74 Te-Tris 36 \n", + "75 Jerzy Mączyński 2 \n", + "76 Wacław Zimpel 18 \n", + "77 Patryk Kumór 26 \n", + "78 Hate 30 \n", + "79 Hania Rani 53 \n", + "80 Batushka 45 \n", + "81 Bass Jan Other 0 \n", + "82 Night Mistress 19 \n", + "83 W.E.N.A. 40 \n", + "84 Searching For Calm 1 \n", + "85 Made Of Hate 24 \n", + "86 Andre 37 \n", + "87 Dwa Sławy 47 \n", + "88 Luna Ad Noctum 0 \n", + "89 Natural Dread Killaz 25 \n", + "90 One Million Bulgarians 2 \n", + "91 Graveland 22 \n", + "92 Śmierć Kliniczna 0 \n", + "93 Cytadela 0 \n", + "94 Sovinsky 0 \n", + "95 L.U.C. 39 \n", + "96 Pablo Rouve 0 \n", + "97 Kapela Maliszów 15 \n", + "98 Jan Podbielski 0 \n", + "99 Czerń 1 \n", + "100 Malik Montana 68 \n", "Rows: 1-100 | Columns: 5" ] }, + "execution_count": 6, "metadata": {}, - "output_type": "display_data" - }, + "output_type": "execute_result" + } + ], + "source": [ + "artists.head(100)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "06c2758a", + "metadata": {}, + "outputs": [ { "data": { "text/html": [ - "
Abc
id
Varchar(44)
Abc
Varchar(196)
123
popularity
Integer
123
duration_ms
Integer
123
explicit
Integer
Abc
Varchar(344)
Abc
Varchar(364)
📅
release_date
Date
123
danceability
Numeric(10)
123
energy
Numeric(9)
123
key
Integer
123
loudness
Numeric(11)
123
mode
Integer
123
speechiness
Numeric(10)
123
acousticness
Numeric(11)
123
instrumentalness
Float(22)
123
liveness
Numeric(11)
123
valence
Numeric(9)
123
tempo
Numeric(12)
123
time_signature
Integer
100147h65HDYSncB3byziPP1224144001961-01-010.2380.25310-13.89810.03150.8770.00.07480.16490.8554
200AS1Cy5BASzGnl8MrVUcv2039660001969-03-110.5580.3072-20.49210.03430.910.6510.08660.674119.0334
300AUl5n7ASRaqGGk8cY7ec2112428001981-01-010.550.55211-10.17210.02910.4381.37e-050.1260.843134.5474
400Bk1lDmnlpeM7rp9nmFCn418720001954-12-310.3870.3010-12.98210.04960.9770.04240.3950.58580.4654
500DK20f7WgF2t1eTwlveGu018476401953-01-010.4880.3940-8.48510.04930.9440.0002360.360.739132.384
600GYv0FzYgssmzaMoZHsxd018242701950-01-010.5080.1059-25.08310.07680.9790.8890.1030.64130.2144
700Hkq26u850QhOO5baOWHA1521229302005-07-250.7870.5662-6.27200.03070.01450.0001140.1130.438118.0254
800IYjifEpVxgKz5r66lYOt4342596001995-08-070.3960.87-10.10210.03190.02130.2790.1220.533147.0534
900K3yuFVb33hBNoEyWcdnj3436122702012-04-030.7180.8165-6.16310.05440.04420.001410.04420.836125.6424
1000LNJ3WTbYZufZOrwHV0sG319006701959-01-010.4710.3050-12.28610.03830.7711.05e-060.07420.327121.0954
1100LQ1LG1WCfyYEgyg17ZeK021273301953-01-010.3710.2841-15.41410.04040.9820.07620.1780.441107.914
1200LpqPZSfnDVoiaLBrieJb1612500001981-01-150.4930.8687-10.65610.03490.001855.69e-050.1260.72796.1744
1300MAWNbKDCBUMjqmyx7ipK020666101952-01-010.4270.1021-17.79400.04410.9940.9570.1890.55572.4914
1400OC3hIGlu5BuK6xVriAPZ723473301966-04-110.4880.8237-7.55910.07910.8110.1290.2510.777101.3634
1500PPopDfcYt0QOu8vxMqm5018500001929-11-060.6650.1322-12.76210.06120.9930.0340.1390.531116.3894
1600PVvXOTonYJRSItustZhr019457301951-01-010.5980.2082-15.82410.04040.8913.1e-050.1210.72880.5664
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1900WO1oBxZcj9aBoeiODXDx3723179102018-12-140.8030.5375-7.92800.05640.6739.61e-060.1330.404112.9644
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2300iXlZ8jMVxSrxXvQomYU12711112001971-10-010.4590.06530-20.00410.04670.9610.001830.1070.30192.2174
2400jK3BvNcO3lf2TdxHwo9d017053301924-07-110.5890.2542-16.08110.05760.9960.9520.2550.352116.6024
2500kTY2h5rdJwP600uhCDkT1835998701987-09-120.4950.4596-11.46210.04090.7853.9e-060.1520.696109.4944
2600m7Q2wHED7wAbYq83XxOh3718757301969-03-110.6330.1960-19.93610.04340.9020.03130.1610.751116.3754
2700mhVzrdTvOr6v9AOklzdD3012080001982-05-010.7180.5085-9.18110.9420.8260.00.08210.734123.8814
2800qTlNBM62qVriou9qedWC018100001947-03-150.5060.2672-8.18100.04790.9770.4580.3310.597109.9241
2900winjndpTmWDldOEPjquu319112001981-07-010.6750.4231-11.92610.5940.4760.00.150.506110.3853
3000wvVSUEvQpmuEfX2ljq8c2712109301963-11-150.3250.1148-17.80810.0340.9440.006840.1340.23474.3784
31012eyTyyRCHaWTOhVGVMPR1432792001988-05-060.7870.5882-11.94900.03110.2280.5010.3620.636106.7764
32017tyGFxZEvwmaZ65Gjt3v015181301927-09-040.4370.27110-15.40310.1140.9950.8660.1140.845209.8414
3301AaVwdRjbSIvolvCifrv5020294201953-12-310.3390.1635-14.68400.04550.9940.9120.3110.33767.5334
3401FPelZNyPM7XAkQjg3dQ1124797301958-01-010.2460.35611-13.08610.03730.8880.0003530.1310.0661128.5564
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3801JPQ87UHeGysPVwTqMJHK7026409812016-02-150.6490.4787-7.50300.04810.2740.00.1760.15199.9674
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4201OxAEheiMQZSiqiQ4dn8L1514700001981-01-150.390.8117-10.81210.05850.02970.00.2740.904182.3574
4301UbgMTwcnuWX7OvZucvBy017022701949-12-010.4490.2085-13.82310.04930.9940.04090.1340.68762.8144
4401VFtIxyINCveL0nGCkp6X015748001939-01-240.3970.350-13.4810.09760.9920.9190.2360.808168.1553
4501ZMPq6QyqEM2k5G6Rdfwm016796001927-08-160.6530.1866-17.08800.06130.9920.9080.1130.821115.4344
4601caZ2bPL258w22yoiDVHg329332901959-01-010.3540.261-20.87710.03830.940.0008280.1470.59793.4394
4701dnrnEOVLKJ5prX36hPcn1422689301959-01-010.4510.3975-11.9210.04210.7921.49e-060.05660.43795.0994
4801eQIOIzFxetNf2t59xF5f1014316001958-01-010.5720.5255-4.72100.09740.7670.00.9150.858129.1094
4901gVBCp26pEKA1oWqTYBhA017400001926-08-150.7040.4269-15.60110.05280.9930.9160.1150.964118.1764
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5301u6AEzGbGbQyYVdxajxqk6012289301958-03-210.6970.552-11.49610.180.8563.44e-050.09070.84484.8024
5401uQi6D1KPZhdpS9JaU5Xa019332601955-12-310.5150.1385-14.51700.1210.9940.6560.2720.6126.3364
5501whPz5NnbknJ3cc5upgwy826261301963-01-010.40.5752-8.48310.06490.9380.007310.2740.453113.4843
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6102M0qdOryJfRJEiIGpAdQN3624910701978-10-040.470.1922-17.28610.0310.3391.32e-050.1270.233152.7324
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6402QmAcjoZHU1ZQMvEPB8jN522513301956-01-010.530.42711-10.48910.04670.8391.54e-050.2940.92598.9314
6502S7g2MHlhh9xBc5xm9YMq1121562701974-12-310.4580.4614-8.81310.05130.9670.000460.1180.692144.4233
6602VH0kDq60k9Qd5bV5v0IH018992001953-12-310.4570.1453-13.24900.07180.9875.18e-050.1230.55781.7173
6702Vns40XKL0ZjBuG7TTc1K021342701952-12-010.4420.1495-19.23600.04780.9830.3690.1990.48274.1873
6802XnQdf7sipaKBBHixz3Zp7220830702008-01-010.7620.6925-3.97300.04380.1130.00.0940.397114.9064
6902YVzb8Aw5rx3tzuSKcmzz3416624001972-06-010.4780.7256-12.41900.05810.1060.1660.6330.692152.14
7002aaEPQolGKSGef4VSfCwY2910073301985-03-010.5520.4969-11.34710.7630.7720.00.5220.44678.7064
7102adYtFMlhp7IpdxRj23TL017700001928-09-250.6690.1417-12.710.06020.9950.4830.1240.54114.584
7202ahlvx5eYw5gdfx21MS86417385301939-01-240.6830.34910-7.77710.08130.9410.001570.0890.82136.5154
7302b0KuMW4nP2CwcgZFPXEw020274601953-12-310.6990.2234-13.64110.1530.980.004490.09760.85984.9094
7402cC87YyLKhCQjU8IH1Frm4431170712010-08-130.6130.3738-10.25510.05630.2960.006710.1520.41979.9834
7502d1E4NRuh7OEQO4vCb9PD6126452002011-05-230.6120.8770-4.4310.0640.0009920.005630.4620.38131.0684
7602ez4pi2F5ZAPIdVQq8hBI2421850701997-11-060.9330.97610-5.41400.06160.05830.0004530.3210.931124.0094
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8002lI7Q5IBgWpl4CNiB5k8h024200001933-01-070.410.1113-19.87610.1110.9950.3030.2490.511147.3193
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8302yKk07IYQa2k68UVjOays018520201948-01-010.4150.2155-13.42800.0920.9950.8770.1880.8377.0974
84034Ef8hgYbtZli4BroCbo11317100001981-01-150.5760.9122-10.30410.03070.001520.002790.04520.961148.8994
85036CtUcmWCKyUwXIvdublh2731388002004-12-270.5830.3622-13.76710.02530.08240.0007290.08620.323130.0534
86036VdTP0ggdePwbvbFuT8w3913386701957-06-200.2540.04321-18.94110.03540.9740.002790.1030.357172.8723
8703AMfxhiuPDtqVBUGdzFOU020662701951-12-310.3820.4576-9.40410.03340.9391.05e-060.1540.60979.2844
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8903CKdROJ3sAs87hzM9Hjnh817660001956-01-010.7870.2859-12.88500.05650.6240.0870.1480.709129.2784
9003HF18PyO2aob3htRSW0js279864001990-02-010.690.4850-10.64510.9380.4570.00.5820.75380.9824
9103L76Pappow8L5V2fK71wk3027374701973-02-040.2110.2760-14.40310.04920.8250.410.6960.14484.1464
9203M69YsUjWF7wGfQ4hwBd6017501301927-09-050.8990.2621-10.06110.2470.9950.3740.2060.693112.4314
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9703UVgidiSdTQMo6nKItb3A020005301953-12-310.5230.34911-10.3610.03490.9910.00.2520.593120.2074
9803UcRmYgoTYJkLmIYcniqp816809301956-01-010.580.4747-11.71600.06280.4958.34e-050.2140.966132.2394
9903UfanaHgYdhu45vUfh9Kb2712720001992-06-010.5870.7947-9.21610.8350.1790.00.4730.266120.384
10003Vs6b3jee5YNsJhNKwzej2318860001962-01-010.2980.3194-13.63710.04130.9680.03860.1240.579159.1595
Rows: 1-100 | Columns: 20
" + "
Abc
id
Varchar(44)
Abc
Varchar(196)
123
popularity
Integer
123
duration_ms
Integer
123
explicit
Integer
Abc
Varchar(344)
Abc
Varchar(364)
📅
release_date
Date
123
danceability
Numeric(10)
123
energy
Numeric(9)
123
key
Integer
123
loudness
Numeric(11)
123
mode
Integer
123
speechiness
Numeric(10)
123
acousticness
Numeric(11)
123
instrumentalness
Float(22)
123
liveness
Numeric(11)
123
valence
Numeric(9)
123
tempo
Numeric(12)
123
time_signature
Integer
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600a8mZIrYshErBYRiY6J7d019333301950-01-010.3520.09899-16.73810.1280.9950.9180.09890.41650.6884
700iXlZ8jMVxSrxXvQomYU12711112001971-10-010.4590.06530-20.00410.04670.9610.001830.1070.30192.2174
800kTY2h5rdJwP600uhCDkT1835998701987-09-120.4950.4596-11.46210.04090.7853.9e-060.1520.696109.4944
900qTlNBM62qVriou9qedWC018100001947-03-150.5060.2672-8.18100.04790.9770.4580.3310.597109.9241
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11017tyGFxZEvwmaZ65Gjt3v015181301927-09-040.4370.27110-15.40310.1140.9950.8660.1140.845209.8414
1201AaVwdRjbSIvolvCifrv5020294201953-12-310.3390.1635-14.68400.04550.9940.9120.3110.33767.5334
1301JPQ87UHeGysPVwTqMJHK7026409812016-02-150.6490.4787-7.50300.04810.2740.00.1760.15199.9674
1401gpCBvSLYcpMjbLPykc1B018460001953-12-310.3060.3045-14.58400.04680.9940.2540.1730.471133.7165
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17021jmGJUrMmS92WnBWvoAC2711522701990-06-010.7460.5787-9.47710.9470.5690.00.7410.6384.945
1802cC87YyLKhCQjU8IH1Frm4431170712010-08-130.6130.3738-10.25510.05630.2960.006710.1520.41979.9834
1902lI7Q5IBgWpl4CNiB5k8h024200001933-01-070.410.1113-19.87610.1110.9950.3030.2490.511147.3193
20036VdTP0ggdePwbvbFuT8w3913386701957-06-200.2540.04321-18.94110.03540.9740.002790.1030.357172.8723
2103AMfxhiuPDtqVBUGdzFOU020662701951-12-310.3820.4576-9.40410.03340.9391.05e-060.1540.60979.2844
2203HF18PyO2aob3htRSW0js279864001990-02-010.690.4850-10.64510.9380.4570.00.5820.75380.9824
2303L76Pappow8L5V2fK71wk3027374701973-02-040.2110.2760-14.40310.04920.8250.410.6960.14484.1464
2403MB4uIPXZJ63F1HQk0Bns226565301972-06-010.3310.1680-14.82910.0330.5380.09970.5890.058871.563
2503TIKoaX56q27pRyYZ9zPe1626292401970-12-310.3880.41211-8.47110.03550.9452.46e-050.1840.45137.5114
2603YZ3SmELE9LlojJG3GgEl1415016001958-01-010.6320.2635-11.06610.06590.8490.00.3530.539118.8414
2703w0JAy22hxUDRKLNPradE017000001928-10-030.7910.1511-12.25610.1120.9940.5530.220.706116.3264
2804N18CfIbOJPnVLGOKgJNB5425005302003-07-010.630.51410-8.00510.05210.2470.00.09890.47789.1284
2904RedUeDN5QjRSJveIz6vp2321297601965-12-060.3450.5245-11.20410.05210.9740.2390.7320.798137.6645
3004wUuScZcskGGpnSEt5Vmb2134068001977-12-010.3020.5486-12.17810.05090.5854.13e-050.1350.76396.0854
31058A8NFVMcfRphgOpxXH9M822100001991-01-010.7170.6045-10.38310.03260.1031.49e-050.1010.582130.9234
3205CBEqQ8CWilFUNW7vYPi9018762801949-12-310.3590.21211-16.66710.06390.9950.9770.3370.78772.7534
3305CM8z8uYj064zvn6YOAHj013249301951-03-140.5890.4328-9.43510.1630.9950.790.1260.90388.2924
3405E60GLnBS8eMhcAsIbfpM018900001931-12-110.840.4182-6.50500.07370.9848.11e-060.1440.818122.7624
3505T5cnFmAXiiBWV5wtM3tX349430701982-01-010.7090.3371-11.51110.9180.5580.00.5920.436113.175
3605UEdT06NxdH4JTgltDnaw019180001953-12-310.4370.14611-16.73700.06030.9920.9430.1080.50776.4384
3705r5QhWMq0T0EQDhYZouLO018792901948-12-310.6380.147-10.60300.6220.9950.6380.1040.58480.5544
38064WS0WvMzTXKl0xx45ryF289997301984-09-010.7410.48111-11.38300.9420.6060.00.4020.556102.0664
3906FoaUqbBSpO4crPQ1GXrF021826901953-01-010.5930.17311-16.73210.2440.9880.4930.4520.73886.6154
4006GtF3borSXnkXfCyeUUmX017688001924-07-120.6860.2359-14.02310.1040.9960.9780.3070.556118.7734
4106LtO6ogcuQktXe0pQghdh1330417601965-09-030.4280.4133-6.63810.03190.9850.2880.1740.654125.2963
4206NEuecnoNSQxDC3lfHpyy4326492002016-09-140.40.9930-1.68810.1280.0007320.03720.1030.338185.934
4306XszKvYdMfzwpoxHDnpun2810040001982-08-010.6580.5540-11.67410.9360.7540.00.8220.553109.2411
4406uDJ8qAO6btD89f4aMlEk3010244001985-06-010.6630.5489-9.95310.8880.2840.00.7570.53799.8844
4507KD6sXOexgCnzd2ux4uTe3120436001989-12-010.5460.4368-11.92910.03530.6670.02230.3370.466120.6444
4607UmbTUVteqSGrFZkMdBvG1028760001961-12-300.280.5116-7.00500.03530.8390.00.3130.636188.354
4707XHoD2XHmzgxGHhWw7fLx022270701953-01-010.5950.39-20.30610.04810.8820.00.3470.789116.4614
4807c11BxeE28llfHSPSRqFv4622903202018-03-230.7630.3117-9.1310.03590.6940.00.1030.34185.0524
4907kKdEH4zfobUFfahc7RcW020904001936-01-180.3930.3185-10.83210.04630.9850.8090.3930.46966.654
5007rAh606hDOjnTaHlJoT0C1137950001989-01-010.5630.4515-10.23200.0380.8022.83e-060.2820.538131.9261
5107ubKGIpVTG49naAmpe8gt020034801954-12-310.5350.15911-13.64300.1150.9920.7250.4040.70462.2693
520874YaGRpvsVw92BDQZr2A016090701929-10-150.6060.3325-15.34410.3610.9920.8390.1690.964165.5643
5308CVQP4qjws8a6DtNG3aVK625308001955-12-010.2990.3052-11.97910.03650.9860.0360.1170.403162.4073
5408SpaYq4TuWsuqHoxJg3xM017769301924-07-110.5240.5323-14.63110.3850.9960.9430.1310.63116.6614
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Rows: 1-100 | Columns: 20
" ], "text/plain": [ "None id name \\\\\n", - "1 00147h65HDYSncB3byziPP My Shining Hour \\\\\n", - "2 00AS1Cy5BASzGnl8MrVUcv Ride the Wind \\\\\n", - "3 00AUl5n7ASRaqGGk8cY7ec Kasme Vaade Nibhayenge Hum - Part II ... \\\\\n", - "4 00Bk1lDmnlpeM7rp9nmFCn Jayen To Jayen Kahan - Female Vocals \\\\\n", - "5 00DK20f7WgF2t1eTwlveGu O Sajna Barkha Bahar (From ''Parakh'') \\\\\n", - "6 00GYv0FzYgssmzaMoZHsxd Yaad Aanewale Phir Yaad \\\\\n", - "7 00Hkq26u850QhOO5baOWHA Par Dni \\\\\n", - "8 00IYjifEpVxgKz5r66lYOt I'm the Ocean \\\\\n", - "9 00K3yuFVb33hBNoEyWcdnj Złoty Paw - 2003 Remaster \\\\\n", - "10 00LNJ3WTbYZufZOrwHV0sG Shall We Dance? \\\\\n", - "11 00LQ1LG1WCfyYEgyg17ZeK Pee Bin Soona Ji \\\\\n", - "12 00LpqPZSfnDVoiaLBrieJb Niño Mimado \\\\\n", - "13 00MAWNbKDCBUMjqmyx7ipK Kal Jalega Chand Sari Raat \\\\\n", - "14 00OC3hIGlu5BuK6xVriAPZ Mera Mehboob Hai Bemisaal \\\\\n", - "15 00PPopDfcYt0QOu8vxMqm5 Rumoreando - Remasterizado \\\\\n", - "16 00PVvXOTonYJRSItustZhr Dil Ki Kahani \\\\\n", - "17 00Sh9dNsH8p16ykGD5LDfm Kehdo Kehdo - Sachaa Jhutha / Soundtr... \\\\\n", - "18 00VqMy5MnBX2zGHWPHrJpM Meri Dil Ki Nagariya Mein Aana \\\\\n", - "19 00WO1oBxZcj9aBoeiODXDx Tavallinen \\\\\n", - "20 00a8mZIrYshErBYRiY6J7d Aesi Mohabbat Se Ham Baaz Aaye \\\\\n", - "21 00aUP0V7nUmbda1X93jAOV One Note Man \\\\\n", - "22 00c1SFo6Bka0zlkIeUHRFI Leoncavallo: Pagliacci, Act II Scene ... \\\\\n", - "23 00iXlZ8jMVxSrxXvQomYU1 Home Is Where the Heart Is \\\\\n", - "24 00jK3BvNcO3lf2TdxHwo9d Fantasio - Remasterizado \\\\\n", - "25 00kTY2h5rdJwP600uhCDkT Ghata Chha Gayee Hai \\\\\n", - "26 00m7Q2wHED7wAbYq83XxOh Sunlight \\\\\n", - "27 00mhVzrdTvOr6v9AOklzdD 015 - UFOs in Bad Finkenstein - Teil 24 \\\\\n", - "28 00qTlNBM62qVriou9qedWC Sus Ojos Se Cerraron - Remasterizado \\\\\n", - "29 00winjndpTmWDldOEPjquu 005 - Das Phantom auf dem Feuerstuhl ... \\\\\n", - "30 00wvVSUEvQpmuEfX2ljq8c Love Me Tonight \\\\\n", - "31 012eyTyyRCHaWTOhVGVMPR Kharisma \\\\\n", - "32 017tyGFxZEvwmaZ65Gjt3v Amapola - Instrumental (Remasterizado) \\\\\n", - "33 01AaVwdRjbSIvolvCifrv5 Ankhon Se Door Dilbar \\\\\n", - "34 01FPelZNyPM7XAkQjg3dQ1 Arabella / Act 3: Dann aber, wie ich ... \\\\\n", - "35 01FUaONfgFKMCcGxT6v5yd Bach Ke Rahnaji \\\\\n", - "36 01HfJDBGjh2sGbyX27LR7K Noites Cariocas \\\\\n", - "37 01IHl3vTIl6O35e2ADUn0p La Maestrita - Remasterizado \\\\\n", - "38 01JPQ87UHeGysPVwTqMJHK She Don't (feat. Ty Dolla $Ign) \\\\\n", - "39 01L0ctQDUJ8StQM0HDhykH Main To Man Ki Pyas \\\\\n", - "40 01LLSAYjBA6VbyzGnERWMU Yo Quiero a Otra Mujer - Instrumental... \\\\\n", - "41 01MrLGGMQN5znKjdQiLgVj Jhan Jhan Jhan Baje Payaliya \\\\\n", - "42 01OxAEheiMQZSiqiQ4dn8L Me Aburro \\\\\n", - "43 01UbgMTwcnuWX7OvZucvBy Yaad Rakhna Chand Taron, Pt. 2 \\\\\n", - "44 01VFtIxyINCveL0nGCkp6X Amor Imposible - Remasterizado \\\\\n", - "45 01ZMPq6QyqEM2k5G6Rdfwm Mucha Clase - Instrumental (Remasteri... \\\\\n", - "46 01caZ2bPL258w22yoiDVHg Preetam Daras Dikhao \\\\\n", - "47 01dnrnEOVLKJ5prX36hPcn The Real American Folk Song \\\\\n", - "48 01eQIOIzFxetNf2t59xF5f Lullaby Of Birdland - Live At The New... \\\\\n", - "49 01gVBCp26pEKA1oWqTYBhA Madona - Instrumental (Remasterizado) \\\\\n", - "50 01gpCBvSLYcpMjbLPykc1B Kya Hamse Hua Qusoor \\\\\n", - "51 01ie0dwhOQIvsSi6BKAbv8 How Long Has This Been Going On? \\\\\n", - "52 01kKvDxBNQ6WZNQSpSWPyV Le coup de soleil \\\\\n", - "53 01u6AEzGbGbQyYVdxajxqk Don't Be Cruel \\\\\n", - "54 01uQi6D1KPZhdpS9JaU5Xa Ishq Aaya Meri Duniya Men \\\\\n", - "55 01whPz5NnbknJ3cc5upgwy Raat Bhi Hai Kuchh Bheegi Bheegi \\\\\n", - "56 01wv59vPOUdqAfTeCN6yQs Por Vos Yo Me Rompo Todo - Remasterizado \\\\\n", - "57 021jmGJUrMmS92WnBWvoAC 072 - Taschengeld für ein Gespenst - ... \\\\\n", - "58 02CWfH3Rb58j6VkDvJyAt5 Just Look Into His Eyes \\\\\n", - "59 02CrIoIsxOy6z3JvL5SxQu Jee Ghabraye Jiya Jal Jaye \\\\\n", - "60 02HifoNqdIeUqRiq2cWyYF Muchachita Porteña - Remasterizado \\\\\n", - "61 02M0qdOryJfRJEiIGpAdQN Peace of Mind - 2016 Remaster \\\\\n", - "62 02M77uzlhcEl2kk3HGMBal Hum Tum Yeh Bahar Dekho Rang Laya \\\\\n", - "63 02OZXtKtnw8DTYKldfS5cZ You're Trash \\\\\n", - "64 02QmAcjoZHU1ZQMvEPB8jN Main Piya Teri \\\\\n", - "65 02S7g2MHlhh9xBc5xm9YMq Kiska Mahal Hai Kiska Yeh Ghar Hai \\\\\n", - "66 02VH0kDq60k9Qd5bV5v0IH Chandrabhagechya Tiri \\\\\n", - "67 02Vns40XKL0ZjBuG7TTc1K Dil-E-Beqarar Soja \\\\\n", - "68 02XnQdf7sipaKBBHixz3Zp Paparazzi \\\\\n", - "69 02YVzb8Aw5rx3tzuSKcmzz Proud Mary - Live \\\\\n", - "70 02aaEPQolGKSGef4VSfCwY 038 - Die weiße Schmuggler-Yacht - Te... \\\\\n", - "71 02adYtFMlhp7IpdxRj23TL Seria, Seriola - Remasterizado \\\\\n", - "72 02ahlvx5eYw5gdfx21MS86 No Me Pregunten Porque - Remasterizado \\\\\n", - "73 02b0KuMW4nP2CwcgZFPXEw Chhalke Na Gham Ke Pyale \\\\\n", - "74 02cC87YyLKhCQjU8IH1Frm Unsent Letter \\\\\n", - "75 02d1E4NRuh7OEQO4vCb9PD Marry The Night \\\\\n", - "76 02ez4pi2F5ZAPIdVQq8hBI ซักกะนิด \\\\\n", - "77 02fcjwBDIojIdeB6om1xpE Dil Deewana \\\\\n", - "78 02h44zLgeREsufs4mahj0B 029 - Hundediebe kennen keine Gnade -... \\\\\n", - "79 02l857T9AcfQ2JClmMe8CD Así \\\\\n", - "80 02lI7Q5IBgWpl4CNiB5k8h Amor Es Amar - Remasterizado \\\\\n", - "81 02tf4vrkTFIJSxvpJOcg8t Dama Española - Remasterizado \\\\\n", - "82 02uSeDrB7UyxUiJHRjtZRB 040 - Duell im Morgengrauen - Teil 25 \\\\\n", - "83 02yKk07IYQa2k68UVjOays Preetam Tera Mera Pyar \\\\\n", - "84 034Ef8hgYbtZli4BroCbo1 No Me Digas Nada \\\\\n", - "85 036CtUcmWCKyUwXIvdublh Anjelie \\\\\n", - "86 036VdTP0ggdePwbvbFuT8w Loving You \\\\\n", - "87 03AMfxhiuPDtqVBUGdzFOU Chhod Mujhe Na Ja \\\\\n", - "88 03BAOLLnYgpNz6FbVCcST7 Zulato Bai Ras Zula \\\\\n", - "89 03CKdROJ3sAs87hzM9Hjnh Este Cha Cha Chá \\\\\n", - "90 03HF18PyO2aob3htRSW0js 070 - Wer hat Tims Mutter entführt? -... \\\\\n", - "91 03L76Pappow8L5V2fK71wk An American Trilogy - Live at The Hon... \\\\\n", - "92 03M69YsUjWF7wGfQ4hwBd6 El Alacrán - Instrumental (Remasteriz... \\\\\n", - "93 03MB4uIPXZJ63F1HQk0Bns Introduction: Also Sprach Zarathustra... \\\\\n", - "94 03O9KGk9sL87OTISNZs3aE Ek Tu Na Mila Sari Duniya Mili \\\\\n", - "95 03Qa05M3eUKGGfoPdUKlAO Sandia Calada - Remasterizado \\\\\n", - "96 03TIKoaX56q27pRyYZ9zPe Mai Ri Main Kase Kahoon \\\\\n", - "97 03UVgidiSdTQMo6nKItb3A Woh Aayenge Khushi Bankar \\\\\n", - "98 03UcRmYgoTYJkLmIYcniqp Me Siento Enamorado \\\\\n", - "99 03UfanaHgYdhu45vUfh9Kb 081 - Horror-Trip im Luxusauto - Teil 04 \\\\\n", - "100 03Vs6b3jee5YNsJhNKwzej Aawaz Deke Humen Tum Bulao \\\\\n", + "1 00DK20f7WgF2t1eTwlveGu O Sajna Barkha Bahar (From ''Parakh'') \\\\\n", + "2 00LQ1LG1WCfyYEgyg17ZeK Pee Bin Soona Ji \\\\\n", + "3 00MAWNbKDCBUMjqmyx7ipK Kal Jalega Chand Sari Raat \\\\\n", + "4 00PPopDfcYt0QOu8vxMqm5 Rumoreando - Remasterizado \\\\\n", + "5 00PVvXOTonYJRSItustZhr Dil Ki Kahani \\\\\n", + "6 00a8mZIrYshErBYRiY6J7d Aesi Mohabbat Se Ham Baaz Aaye \\\\\n", + "7 00iXlZ8jMVxSrxXvQomYU1 Home Is Where the Heart Is \\\\\n", + "8 00kTY2h5rdJwP600uhCDkT Ghata Chha Gayee Hai \\\\\n", + "9 00qTlNBM62qVriou9qedWC Sus Ojos Se Cerraron - Remasterizado \\\\\n", + "10 012eyTyyRCHaWTOhVGVMPR Kharisma \\\\\n", + "11 017tyGFxZEvwmaZ65Gjt3v Amapola - Instrumental (Remasterizado) \\\\\n", + "12 01AaVwdRjbSIvolvCifrv5 Ankhon Se Door Dilbar \\\\\n", + "13 01JPQ87UHeGysPVwTqMJHK She Don't (feat. Ty Dolla $Ign) \\\\\n", + "14 01gpCBvSLYcpMjbLPykc1B Kya Hamse Hua Qusoor \\\\\n", + "15 01ie0dwhOQIvsSi6BKAbv8 How Long Has This Been Going On? \\\\\n", + "16 01kKvDxBNQ6WZNQSpSWPyV Le coup de soleil \\\\\n", + "17 021jmGJUrMmS92WnBWvoAC 072 - Taschengeld für ein Gespenst - ... \\\\\n", + "18 02cC87YyLKhCQjU8IH1Frm Unsent Letter \\\\\n", + "19 02lI7Q5IBgWpl4CNiB5k8h Amor Es Amar - Remasterizado \\\\\n", + "20 036VdTP0ggdePwbvbFuT8w Loving You \\\\\n", + "21 03AMfxhiuPDtqVBUGdzFOU Chhod Mujhe Na Ja \\\\\n", + "22 03HF18PyO2aob3htRSW0js 070 - Wer hat Tims Mutter entführt? -... \\\\\n", + "23 03L76Pappow8L5V2fK71wk An American Trilogy - Live at The Hon... \\\\\n", + "24 03MB4uIPXZJ63F1HQk0Bns Introduction: Also Sprach Zarathustra... \\\\\n", + "25 03TIKoaX56q27pRyYZ9zPe Mai Ri Main Kase Kahoon \\\\\n", + "26 03YZ3SmELE9LlojJG3GgEl The Song Is Ended \\\\\n", + "27 03w0JAy22hxUDRKLNPradE Un Sueño - Instrumental (Remasterizado) \\\\\n", + "28 04N18CfIbOJPnVLGOKgJNB Wherever I Lay My Hat (That's My Home) \\\\\n", + "29 04RedUeDN5QjRSJveIz6vp Saiyan Be-Imaan \\\\\n", + "30 04wUuScZcskGGpnSEt5Vmb Janeman Tum Kamal Karte Ho \\\\\n", + "31 058A8NFVMcfRphgOpxXH9M חנוך מחנך \\\\\n", + "32 05CBEqQ8CWilFUNW7vYPi9 Badla Nazar Aata Hai Zamane Ka \\\\\n", + "33 05CM8z8uYj064zvn6YOAHj El Llorón - Remasterizado \\\\\n", + "34 05E60GLnBS8eMhcAsIbfpM Besos de Miel - Remasterizado \\\\\n", + "35 05T5cnFmAXiiBWV5wtM3tX 007 - Rätsel um die alte Villa - Teil 05 \\\\\n", + "36 05UEdT06NxdH4JTgltDnaw Jhidkaruni Tu Jasi Rage \\\\\n", + "37 05r5QhWMq0T0EQDhYZouLO Dilwalo Dilon Ka Mel \\\\\n", + "38 064WS0WvMzTXKl0xx45ryF 034 - Vampir der Autobahn - Teil 23 \\\\\n", + "39 06FoaUqbBSpO4crPQ1GXrF Kitna Mitha Hota Hai \\\\\n", + "40 06GtF3borSXnkXfCyeUUmX El Vazquito - Remasterizado \\\\\n", + "41 06LtO6ogcuQktXe0pQghdh Aji Rooth Kar Ab Kahan Jaiyega \\\\\n", + "42 06NEuecnoNSQxDC3lfHpyy Nippon Manju \\\\\n", + "43 06XszKvYdMfzwpoxHDnpun 022 - In den Klauen des Tigers - Teil 18 \\\\\n", + "44 06uDJ8qAO6btD89f4aMlEk 039 - Die Gift-Party - Teil 12 \\\\\n", + "45 07KD6sXOexgCnzd2ux4uTe Aate Jaate Hanste Gaate \\\\\n", + "46 07UmbTUVteqSGrFZkMdBvG Lakhon Tare Aasman Per \\\\\n", + "47 07XHoD2XHmzgxGHhWw7fLx Kare Badra Tu Na Ja \\\\\n", + "48 07c11BxeE28llfHSPSRqFv My Favourite Position \\\\\n", + "49 07kKdEH4zfobUFfahc7RcW No Supe Vengarme - Remasterizado \\\\\n", + "50 07rAh606hDOjnTaHlJoT0C O Mere Saathi Re \\\\\n", + "51 07ubKGIpVTG49naAmpe8gt Rajni Hai Taron Bhari \\\\\n", + "52 0874YaGRpvsVw92BDQZr2A Sos Más Loca Que un Bagual - Instrume... \\\\\n", + "53 08CVQP4qjws8a6DtNG3aVK Man Mohana Bade Jhoothe \\\\\n", + "54 08SpaYq4TuWsuqHoxJg3xM Ki Ki - Remasterizado \\\\\n", + "55 08kHpj5FOW7LjNyVBz5Zvs What Will I Tell My Heart \\\\\n", + "56 08lHFwOBB8FnLwzuGwYMEh Relationship \\\\\n", + "57 08rO8bafPdrmQssvsAMxVl Tera Phoolon Jaisa Rang \\\\\n", + "58 08tC0ditym84D3NBG0jQqA Phool Ahista Phenko \\\\\n", + "59 093IYCNJHNy1cvAH0Mvkch Chaupaiyan - Ramayan \\\\\n", + "60 09Qxk2wRRsicvUtcLvtSTo Main Murlidhar Murli Laai \\\\\n", + "61 09aFzJT56dpsZfN8O2oR6U Aa Mohabbat Ki Basti Basayenge Hum \\\\\n", + "62 09bZ7ATMlxA7LNjCCoCzdA Hero \\\\\n", + "63 09dn63xIPf3n72HNizEElm No Me Fastidies Más - Remasterizado \\\\\n", + "64 0A2BKRDiiNpiRYtiOSajYX Wooden Heart \\\\\n", + "65 0ABNJ6silC7NHkocdiUxTF Dil Men Hamare Aag Lagakar \\\\\n", + "66 0ACKq3I2568VVrgcpwFkOI Guajojo \\\\\n", + "67 0AgnrqcD0dr22vaZeroGOX Chal Dariya Mein Doob Jayen \\\\\n", + "68 0AjhUemO2FH31c4Bda00tO Pahiles Tu Aikiles Tu \\\\\n", + "69 0AwtRpubA0XprHmhMkeFQf Stella By Starlight \\\\\n", + "70 0B4HWkQHhAzxW43V7Z0fQO Consejo Sano - Instrumental (Remaster... \\\\\n", + "71 0B6RBLFwXxp4CqOJ02SqdT Kashmir Ki Kali Hoon Main \\\\\n", + "72 0BNYfaz6wi8hwz2yWfGciG La Canción de Vidalita - Remasterizado \\\\\n", + "73 0BZK5owhrgOW72f0CAjDYB Senza fine \\\\\n", + "74 0BqR2YNnnicAYkkNFkHLvR Ae Dil Kahan Teri Manzil - Happy \\\\\n", + "75 0CGFSEHPCoxIql2t8D5Kjc Tu Kaun Hai Mera \\\\\n", + "76 0CK9b2dEDscskyQ0Xd7L4p Yara Seeli Seeli \\\\\n", + "77 0Cbra96lST7uHGZjSpfR46 Kari Kari Andhiyari Raat Mein \\\\\n", + "78 0Cmq2tmC0QGFVgliknr0MN Yeh Ruki Ruki Hawaen \\\\\n", + "79 0CrCsWktPpP2yO8hSKnCsy Zara Sun Lo Hum Apne \\\\\n", + "80 0D12JQoW6ljmJM86pgrJ1z Ήρθε κι έφυγε σαν ξένος \\\\\n", + "81 0D1pEisM3QkiacGXJe5dmd (You're The) Devil in Disguise \\\\\n", + "82 0DA0LWjbdBTmrlKr2CmQ62 Din Suhane Mausam Bahar Ka \\\\\n", + "83 0DXiJ6NXLtD5SRzsOHPQPI Noches de Carnaval - Instrumental (Re... \\\\\n", + "84 0DplGIOdpwkzdwKbOClMlJ El Desfile de Damas - Remasterizado \\\\\n", + "85 0DtqOgGu29ZUPyhlRdB54g Sawan Ke Jhoole Pade, Pt. 1 \\\\\n", + "86 0Dw6qWZblJ3cUKBobHHGlK Confusion \\\\\n", + "87 0E0nqXEw6HtFEqsQTTOMcJ パピヨン 〜papillon〜 \\\\\n", + "88 0E2UM5021iM76L4zvuIsGK Cinta Tak Perlu Dipaksa (Original Ver... \\\\\n", + "89 0EAJ0xn42jBzzD9BRJA0I8 One of These Days \\\\\n", + "90 0EDwfMkuOLWqZmEiYrAVIi 006 - Angst in der 9a - Teil 14 \\\\\n", + "91 0EOYB5Dhk3YeLrjvajYiIj Akhercha Ha Tula Dandvat \\\\\n", + "92 0EPBPqrmLxVl3UXzcJuqVj Itna To Yaad Hai Mujhe \\\\\n", + "93 0EQufZ7uB8mcnISIKfQtyJ O Ji Dheere Dheere \\\\\n", + "94 0ESg82SK2vuKfd8xfZ0f17 Zostań Tu \\\\\n", + "95 0EcQqsrUkVhPZsPc7InZwS 010 - Alarm im Zirkus Sarani! - Teil 08 \\\\\n", + "96 0Eh0NJcwxUrtIsyjsNpv1e I Want To Hold You In My Dreams Tonight \\\\\n", + "97 0EzFMcpJw2BaOpq4klnCbf Canto straniero \\\\\n", + "98 0F24HA5PftFkfETekL0cwm Jo Dil Mein Khushi Ban Kar Aai \\\\\n", + "99 0FA6uDYBkJ0yqiZwQZHwgg Spinout \\\\\n", + "100 0FVH9hZ1Xn1jgl0ehI5wjh Todo Es Mentira - Remasterizado \\\\\n", "None popularity duration_ms explicit artists \\\\\n", - "1 12 241440 0 ['Ella Fitzgerald'] \\\\\n", - "2 20 396600 0 ['The Youngbloods'] \\\\\n", - "3 21 124280 0 ['Kishore Kumar', 'Lata Mangeshkar'] \\\\\n", - "4 4 187200 0 ['Lata Mangeshkar'] \\\\\n", - "5 0 184764 0 ['Lata Mangeshkar'] \\\\\n", - "6 0 182427 0 ['Lata Mangeshkar', 'Talat Mahmood'] \\\\\n", - "7 15 212293 0 ['Desmod', 'Zuzana Smatanova'] \\\\\n", - "8 43 425960 0 ['Neil Young'] \\\\\n", - "9 34 361227 0 ['Dzem'] \\\\\n", - "10 3 190067 0 ['Ella Fitzgerald'] \\\\\n", - "11 0 212733 0 ['Lata Mangeshkar', 'Manna Dey'] \\\\\n", - "12 16 125000 0 ['Los Secretos'] \\\\\n", - "13 0 206661 0 ['Lata Mangeshkar'] \\\\\n", - "14 7 234733 0 ['Lata Mangeshkar'] \\\\\n", - "15 0 185000 0 ['Francisco Canaro', 'Charlo'] \\\\\n", - "16 0 194573 0 ['Lata Mangeshkar'] \\\\\n", - "17 22 289867 0 ['Kishore Kumar', 'Lata Mangeshkar'] \\\\\n", - "18 0 182840 0 ['Lata Mangeshkar'] \\\\\n", - "19 37 231791 0 ['Keko Salata'] \\\\\n", - "20 0 193333 0 ['Lata Mangeshkar'] \\\\\n", - "21 15 146227 0 ['The Youngbloods'] \\\\\n", - "22 0 179133 0 ['Ruggero Leoncavallo', 'Alfredo Simo... \\\\\n", - "23 27 111120 0 ['Elvis Presley'] \\\\\n", - "24 0 170533 0 ['Francisco Canaro'] \\\\\n", - "25 18 359987 0 ['Lata Mangeshkar', 'Suresh Wadkar'] \\\\\n", - "26 37 187573 0 ['The Youngbloods'] \\\\\n", - "27 30 120800 0 ['TKKG Retro-Archiv'] \\\\\n", - "28 0 181000 0 ['Francisco Canaro', 'Nelly Omar'] \\\\\n", - "29 31 91120 0 ['TKKG Retro-Archiv'] \\\\\n", - "30 27 121093 0 ['Elvis Presley'] \\\\\n", - "31 14 327920 0 ['Karimata'] \\\\\n", - "32 0 151813 0 ['Francisco Canaro'] \\\\\n", - "33 0 202942 0 ['Lata Mangeshkar'] \\\\\n", - "34 1 247973 0 ['Richard Strauss', 'Lisa della Casa'... \\\\\n", - "35 0 326471 0 ['Chitalkar', 'Geeta Dutt', 'Lata Man... \\\\\n", - "36 25 169227 0 ['Tôco Preto'] \\\\\n", - "37 0 161160 0 ['Francisco Canaro'] \\\\\n", - "38 70 264098 1 ['Ella Mai', 'Ty Dolla $ign'] \\\\\n", - "39 0 202384 0 ['Lata Mangeshkar'] \\\\\n", - "40 0 165000 0 ['Francisco Canaro'] \\\\\n", - "41 2 190893 0 ['Mohammed Rafi', 'Lata Mangeshkar'] \\\\\n", - "42 15 147000 0 ['Los Secretos'] \\\\\n", - "43 0 170227 0 ['Lata Mangeshkar'] \\\\\n", - "44 0 157480 0 ['Francisco Canaro', 'Francisco Amor'] \\\\\n", - "45 0 167960 0 ['Francisco Canaro'] \\\\\n", - "46 3 293329 0 ['Lata Mangeshkar', 'Manna Dey'] \\\\\n", - "47 14 226893 0 ['Ella Fitzgerald'] \\\\\n", - "48 10 143160 0 ['Ella Fitzgerald'] \\\\\n", - "49 0 174000 0 ['Francisco Canaro'] \\\\\n", - "50 0 184600 0 ['Lata Mangeshkar'] \\\\\n", - "51 9 351627 0 ['Ella Fitzgerald'] \\\\\n", - "52 40 249987 0 ['Roberto Bellarosa'] \\\\\n", - "53 60 122893 0 ['Elvis Presley'] \\\\\n", - "54 0 193326 0 ['Lata Mangeshkar'] \\\\\n", - "55 8 262613 0 ['Lata Mangeshkar'] \\\\\n", - "56 1 178280 0 ['Francisco Canaro', 'Ernesto Fama'] \\\\\n", - "57 27 115227 0 ['TKKG Retro-Archiv'] \\\\\n", - "58 1 253080 0 ['Retta Young'] \\\\\n", - "59 0 174270 0 ['Lata Mangeshkar'] \\\\\n", - "60 0 158493 0 ['Francisco Canaro'] \\\\\n", - "61 36 249107 0 ['Neil Young'] \\\\\n", - "62 6 198766 0 ['Lata Mangeshkar', 'Mohammed Rafi'] \\\\\n", - "63 0 13640 0 ['Decreto 77'] \\\\\n", - "64 5 225133 0 ['Lata Mangeshkar'] \\\\\n", - "65 11 215627 0 ['Lata Mangeshkar', 'Kishore Kumar'] \\\\\n", - "66 0 189920 0 ['Lata Mangeshkar'] \\\\\n", - "67 0 213427 0 ['Talat Mahmood', 'Lata Mangeshkar'] \\\\\n", - "68 72 208307 0 ['Lady Gaga'] \\\\\n", - "69 34 166240 0 ['Elvis Presley'] \\\\\n", - "70 29 100733 0 ['TKKG Retro-Archiv'] \\\\\n", - "71 0 177000 0 ['Francisco Canaro', 'Charlo'] \\\\\n", - "72 4 173853 0 ['Francisco Canaro', 'Ernesto Fama'] \\\\\n", - "73 0 202746 0 ['Lata Mangeshkar'] \\\\\n", - "74 44 311707 1 ['Machine Gun Fellatio'] \\\\\n", - "75 61 264520 0 ['Lady Gaga'] \\\\\n", - "76 24 218507 0 ['Tata Young'] \\\\\n", - "77 44 355265 0 ['Lata Mangeshkar'] \\\\\n", - "78 28 88733 0 ['TKKG Retro-Archiv'] \\\\\n", - "79 11 122107 0 ['Chucho Avellanet'] \\\\\n", - "80 0 242000 0 ['Francisco Canaro', 'Lidia Desmond'] \\\\\n", - "81 0 193493 0 ['Francisco Canaro', 'Agustín Irusta'] \\\\\n", - "82 28 105347 0 ['TKKG Retro-Archiv'] \\\\\n", - "83 0 185202 0 ['Lata Mangeshkar'] \\\\\n", - "84 13 171000 0 ['Los Secretos'] \\\\\n", - "85 27 313880 0 ['Flanella'] \\\\\n", - "86 39 133867 0 ['Elvis Presley'] \\\\\n", - "87 0 206627 0 ['Lata Mangeshkar'] \\\\\n", - "88 9 277027 0 ['Lata Mangeshkar'] \\\\\n", - "89 8 176600 0 ['La Sonora Matancera'] \\\\\n", - "90 27 98640 0 ['TKKG Retro-Archiv'] \\\\\n", - "91 30 273747 0 ['Elvis Presley'] \\\\\n", - "92 0 175013 0 ['Francisco Canaro'] \\\\\n", - "93 22 65653 0 ['Elvis Presley'] \\\\\n", - "94 8 254250 0 ['Lata Mangeshkar'] \\\\\n", - "95 0 166507 0 ['Francisco Canaro', 'Charlo'] \\\\\n", - "96 16 262924 0 ['Lata Mangeshkar'] \\\\\n", - "97 0 200053 0 ['Lata Mangeshkar'] \\\\\n", - "98 8 168093 0 ['La Sonora Matancera', 'Leo Marini'] \\\\\n", - "99 27 127200 0 ['TKKG Retro-Archiv'] \\\\\n", - "100 23 188600 0 ['Lata Mangeshkar', 'Mohammed Rafi'] \\\\\n", + "1 0 184764 0 ['Lata Mangeshkar'] \\\\\n", + "2 0 212733 0 ['Lata Mangeshkar', 'Manna Dey'] \\\\\n", + "3 0 206661 0 ['Lata Mangeshkar'] \\\\\n", + "4 0 185000 0 ['Francisco Canaro', 'Charlo'] \\\\\n", + "5 0 194573 0 ['Lata Mangeshkar'] \\\\\n", + "6 0 193333 0 ['Lata Mangeshkar'] \\\\\n", + "7 27 111120 0 ['Elvis Presley'] \\\\\n", + "8 18 359987 0 ['Lata Mangeshkar', 'Suresh Wadkar'] \\\\\n", + "9 0 181000 0 ['Francisco Canaro', 'Nelly Omar'] \\\\\n", + "10 14 327920 0 ['Karimata'] \\\\\n", + "11 0 151813 0 ['Francisco Canaro'] \\\\\n", + "12 0 202942 0 ['Lata Mangeshkar'] \\\\\n", + "13 70 264098 1 ['Ella Mai', 'Ty Dolla $ign'] \\\\\n", + "14 0 184600 0 ['Lata Mangeshkar'] \\\\\n", + "15 9 351627 0 ['Ella Fitzgerald'] \\\\\n", + "16 40 249987 0 ['Roberto Bellarosa'] \\\\\n", + "17 27 115227 0 ['TKKG Retro-Archiv'] \\\\\n", + "18 44 311707 1 ['Machine Gun Fellatio'] \\\\\n", + "19 0 242000 0 ['Francisco Canaro', 'Lidia Desmond'] \\\\\n", + "20 39 133867 0 ['Elvis Presley'] \\\\\n", + "21 0 206627 0 ['Lata Mangeshkar'] \\\\\n", + "22 27 98640 0 ['TKKG Retro-Archiv'] \\\\\n", + "23 30 273747 0 ['Elvis Presley'] \\\\\n", + "24 22 65653 0 ['Elvis Presley'] \\\\\n", + "25 16 262924 0 ['Lata Mangeshkar'] \\\\\n", + "26 14 150160 0 ['Ella Fitzgerald', 'Paul Weston And ... \\\\\n", + "27 0 170000 0 ['Francisco Canaro'] \\\\\n", + "28 54 250053 0 ['Paul Young'] \\\\\n", + "29 23 212976 0 ['Lata Mangeshkar'] \\\\\n", + "30 21 340680 0 ['Lata Mangeshkar', 'Kishore Kumar'] \\\\\n", + "31 8 221000 0 ['Carmella Gross & Wagner'] \\\\\n", + "32 0 187628 0 ['Premlata', 'Satish Batra'] \\\\\n", + "33 0 132493 0 ['Francisco Canaro', 'Alberto Arenas'] \\\\\n", + "34 0 189000 0 ['Francisco Canaro', 'Charlo', 'Ada F... \\\\\n", + "35 34 94307 0 ['TKKG Retro-Archiv'] \\\\\n", + "36 0 191800 0 ['Lata Mangeshkar'] \\\\\n", + "37 0 187929 0 ['Lata Mangeshkar'] \\\\\n", + "38 28 99973 0 ['TKKG Retro-Archiv'] \\\\\n", + "39 0 218269 0 ['Lata Mangeshkar'] \\\\\n", + "40 0 176880 0 ['Francisco Canaro'] \\\\\n", + "41 13 304176 0 ['Lata Mangeshkar'] \\\\\n", + "42 43 264920 0 ['LADYBABY'] \\\\\n", + "43 28 100400 0 ['TKKG Retro-Archiv'] \\\\\n", + "44 30 102440 0 ['TKKG Retro-Archiv'] \\\\\n", + "45 31 204360 0 ['Lata Mangeshkar', 'S. P. Balasubrah... \\\\\n", + "46 10 287600 0 ['Lata Mangeshkar', 'Mukesh'] \\\\\n", + "47 0 222707 0 ['Lata Mangeshkar'] \\\\\n", + "48 46 229032 0 ['NOVAKANE', 'Cindercella'] \\\\\n", + "49 0 209040 0 ['Francisco Canaro', 'Roberto Maida'] \\\\\n", + "50 11 379500 0 ['Salil Chowdhury', 'Kishore Kumar', ... \\\\\n", + "51 0 200348 0 ['Lata Mangeshkar', 'T. A. Mothi'] \\\\\n", + "52 0 160907 0 ['Francisco Canaro'] \\\\\n", + "53 6 253080 0 ['Lata Mangeshkar'] \\\\\n", + "54 0 177693 0 ['Francisco Canaro'] \\\\\n", + "55 14 211893 0 ['Ella Fitzgerald'] \\\\\n", + "56 0 215307 0 ['Young Thug', 'Future'] \\\\\n", + "57 28 369787 0 ['Lata Mangeshkar', 'Kishore Kumar'] \\\\\n", + "58 23 317840 0 ['Lata Mangeshkar', 'Mukesh'] \\\\\n", + "59 10 301040 0 ['Hemlata'] \\\\\n", + "60 0 183269 0 ['Lata Mangeshkar'] \\\\\n", + "61 0 192333 0 ['Lata Mangeshkar', 'Kishore Kumar'] \\\\\n", + "62 0 253767 0 ['Lady Diva'] \\\\\n", + "63 0 186507 0 ['Francisco Canaro', 'Charlo'] \\\\\n", + "64 40 123480 0 ['Elvis Presley'] \\\\\n", + "65 0 181975 0 ['Lata Mangeshkar'] \\\\\n", + "66 14 166893 0 ['Gladys Moreno'] \\\\\n", + "67 14 295733 0 ['Lata Mangeshkar', 'Kishore Kumar'] \\\\\n", + "68 3 209440 0 ['Lata Mangeshkar'] \\\\\n", + "69 31 201093 0 ['Ella Fitzgerald'] \\\\\n", + "70 0 161000 0 ['Francisco Canaro'] \\\\\n", + "71 8 210800 0 ['Lata Mangeshkar'] \\\\\n", + "72 0 179000 0 ['Francisco Canaro', 'Charlo'] \\\\\n", + "73 35 188760 0 ['Ornella Vanoni'] \\\\\n", + "74 4 249333 0 ['Dwijen Mukherjee', 'Lata Mangeshkar'] \\\\\n", + "75 1 200067 0 ['Lata Mangeshkar'] \\\\\n", + "76 30 305880 0 ['Lata Mangeshkar'] \\\\\n", + "77 0 151533 0 ['Lata Mangeshkar'] \\\\\n", + "78 0 185667 0 ['Lata Mangeshkar', 'Asha Bhosle'] \\\\\n", + "79 0 335073 0 ['Lata Mangeshkar', 'Rajkumari'] \\\\\n", + "80 0 205813 0 ['Ioanna Georgakopoulou', 'Stellakis ... \\\\\n", + "81 64 140427 0 ['Elvis Presley'] \\\\\n", + "82 0 205173 0 ['Lata Mangeshkar'] \\\\\n", + "83 0 187000 0 ['Francisco Canaro'] \\\\\n", + "84 0 172000 0 ['Francisco Canaro', 'Luis Diaz'] \\\\\n", + "85 13 321631 0 ['Lata Mangeshkar'] \\\\\n", + "86 22 266286 0 ['Molella'] \\\\\n", + "87 37 255433 0 ['Hitomi Shimatani'] \\\\\n", + "88 23 334333 0 ['Budak Kacamata'] \\\\\n", + "89 44 297840 0 ['Neil Young'] \\\\\n", + "90 33 85187 0 ['TKKG Retro-Archiv'] \\\\\n", + "91 21 279120 0 ['Lata Mangeshkar'] \\\\\n", + "92 26 375627 0 ['Mohammed Rafi', 'Lata Mangeshkar'] \\\\\n", + "93 0 167045 0 ['Lata Mangeshkar'] \\\\\n", + "94 20 358609 0 ['Akcent'] \\\\\n", + "95 32 100720 0 ['TKKG Retro-Archiv'] \\\\\n", + "96 21 247613 0 ['Stella Parton'] \\\\\n", + "97 23 273240 0 ['Marcella Bella'] \\\\\n", + "98 1 202240 0 ['Lata Mangeshkar'] \\\\\n", + "99 23 153360 0 ['Elvis Presley'] \\\\\n", + "100 0 179573 0 ['Francisco Canaro', 'Carlos Roldán'] \\\\\n", "None id_artists release_date danceability \\\\\n", - "1 ['5V0MlUE1Bft0mbLlND7FJz'] 1961-01-01 0.238 \\\\\n", - "2 ['5I6MzhNEMk27cZsCqGAIYo'] 1969-03-11 0.558 \\\\\n", - "3 ['0GF4shudTAFv8ak9eWdd4Y', '61JrslREX... 1981-01-01 0.55 \\\\\n", - "4 ['61JrslREXq98hurYL2hYoc'] 1954-12-31 0.387 \\\\\n", - "5 ['61JrslREXq98hurYL2hYoc'] 1953-01-01 0.488 \\\\\n", - "6 ['61JrslREXq98hurYL2hYoc', '2fi9hpqNb... 1950-01-01 0.508 \\\\\n", - "7 ['5yLMeTi9Jxg5LLssjYz5s1', '4kJi5wbe2... 2005-07-25 0.787 \\\\\n", - "8 ['6v8FB84lnmJs434UJf2Mrm'] 1995-08-07 0.396 \\\\\n", - "9 ['5ADo6yIOeD8LJglejYcuen'] 2012-04-03 0.718 \\\\\n", - "10 ['5V0MlUE1Bft0mbLlND7FJz'] 1959-01-01 0.471 \\\\\n", - "11 ['61JrslREXq98hurYL2hYoc', '4kcoiVXIx... 1953-01-01 0.371 \\\\\n", - "12 ['2KEDbpUlz9nwtGywHT4gyf'] 1981-01-15 0.493 \\\\\n", - "13 ['61JrslREXq98hurYL2hYoc'] 1952-01-01 0.427 \\\\\n", - "14 ['61JrslREXq98hurYL2hYoc'] 1966-04-11 0.488 \\\\\n", - "15 ['2maQMqxNnlRrBrS1oAsrX9', '3Ry0Bx0jq... 1929-11-06 0.665 \\\\\n", - "16 ['61JrslREXq98hurYL2hYoc'] 1951-01-01 0.598 \\\\\n", - "17 ['0GF4shudTAFv8ak9eWdd4Y', '61JrslREX... 1970-01-01 0.504 \\\\\n", - "18 ['61JrslREXq98hurYL2hYoc'] 1951-12-31 0.593 \\\\\n", - "19 ['18KcOgLds5SUgIpQIveiJN'] 2018-12-14 0.803 \\\\\n", - "20 ['61JrslREXq98hurYL2hYoc'] 1950-01-01 0.352 \\\\\n", - "21 ['5I6MzhNEMk27cZsCqGAIYo'] 1967-03-10 0.569 \\\\\n", - "22 ['72auy9NefUbGecYVrTiPzq', '36O03XCmU... 1951-01-01 0.38 \\\\\n", - "23 ['43ZHCT0cAZBISjO8DG9PnE'] 1971-10-01 0.459 \\\\\n", - "24 ['2maQMqxNnlRrBrS1oAsrX9'] 1924-07-11 0.589 \\\\\n", - "25 ['61JrslREXq98hurYL2hYoc', '0w4e7HVbq... 1987-09-12 0.495 \\\\\n", - "26 ['5I6MzhNEMk27cZsCqGAIYo'] 1969-03-11 0.633 \\\\\n", - "27 ['0i38tQX5j4gZ0KS3eCMoIl'] 1982-05-01 0.718 \\\\\n", - "28 ['2maQMqxNnlRrBrS1oAsrX9', '6IyGH3tMg... 1947-03-15 0.506 \\\\\n", - "29 ['0i38tQX5j4gZ0KS3eCMoIl'] 1981-07-01 0.675 \\\\\n", - "30 ['43ZHCT0cAZBISjO8DG9PnE'] 1963-11-15 0.325 \\\\\n", - "31 ['3uml27dlkZH4fmfJnMOty7'] 1988-05-06 0.787 \\\\\n", - "32 ['2maQMqxNnlRrBrS1oAsrX9'] 1927-09-04 0.437 \\\\\n", - "33 ['61JrslREXq98hurYL2hYoc'] 1953-12-31 0.339 \\\\\n", - "34 ['6pAwHPeExeUbMd5w7Iny6D', '4ozpyL0BM... 1958-01-01 0.246 \\\\\n", - "35 ['32oVXwlB0RXbsch98lAcFT', '0QsbYX8Xs... 1947-08-15 0.541 \\\\\n", - "36 ['5YA8lPjPJRNrvShLKaA66C'] 1993-04-26 0.624 \\\\\n", - "37 ['2maQMqxNnlRrBrS1oAsrX9'] 1926-07-15 0.604 \\\\\n", - "38 ['7HkdQ0gt53LP4zmHsL0nap', '7c0XG5cIJ... 2016-02-15 0.649 \\\\\n", - "39 ['61JrslREXq98hurYL2hYoc'] 1952-12-31 0.686 \\\\\n", - "40 ['2maQMqxNnlRrBrS1oAsrX9'] 1931-12-11 0.825 \\\\\n", - "41 ['0gXDpqwYNDODn7fB0RDN8J', '61JrslREX... 1959-01-01 0.599 \\\\\n", - "42 ['2KEDbpUlz9nwtGywHT4gyf'] 1981-01-15 0.39 \\\\\n", - "43 ['61JrslREXq98hurYL2hYoc'] 1949-12-01 0.449 \\\\\n", - "44 ['2maQMqxNnlRrBrS1oAsrX9', '4fm9akHwC... 1939-01-24 0.397 \\\\\n", - "45 ['2maQMqxNnlRrBrS1oAsrX9'] 1927-08-16 0.653 \\\\\n", - "46 ['61JrslREXq98hurYL2hYoc', '4kcoiVXIx... 1959-01-01 0.354 \\\\\n", - "47 ['5V0MlUE1Bft0mbLlND7FJz'] 1959-01-01 0.451 \\\\\n", - "48 ['5V0MlUE1Bft0mbLlND7FJz'] 1958-01-01 0.572 \\\\\n", - "49 ['2maQMqxNnlRrBrS1oAsrX9'] 1926-08-15 0.704 \\\\\n", - "50 ['61JrslREXq98hurYL2hYoc'] 1953-12-31 0.306 \\\\\n", - "51 ['5V0MlUE1Bft0mbLlND7FJz'] 1957-01-01 0.317 \\\\\n", - "52 ['33JmoNaTffervAivA88tIB'] 2013-04-22 0.471 \\\\\n", - "53 ['43ZHCT0cAZBISjO8DG9PnE'] 1958-03-21 0.697 \\\\\n", - "54 ['61JrslREXq98hurYL2hYoc'] 1955-12-31 0.515 \\\\\n", - "55 ['61JrslREXq98hurYL2hYoc'] 1963-01-01 0.4 \\\\\n", - "56 ['2maQMqxNnlRrBrS1oAsrX9', '0nRShN4m4... 1939-01-24 0.782 \\\\\n", - "57 ['0i38tQX5j4gZ0KS3eCMoIl'] 1990-06-01 0.746 \\\\\n", - "58 ['2l66RZyrCDYIQ0PBdcLeBt'] 1976-01-01 0.594 \\\\\n", - "59 ['61JrslREXq98hurYL2hYoc'] 1954-01-01 0.397 \\\\\n", - "60 ['2maQMqxNnlRrBrS1oAsrX9'] 1940-01-24 0.467 \\\\\n", - "61 ['6v8FB84lnmJs434UJf2Mrm'] 1978-10-04 0.47 \\\\\n", - "62 ['61JrslREXq98hurYL2hYoc', '0gXDpqwYN... 1952-12-01 0.658 \\\\\n", - "63 ['5wWCsofKpu0j5YZEkUM99H'] 2012-09-21 0.0 \\\\\n", - "64 ['61JrslREXq98hurYL2hYoc'] 1956-01-01 0.53 \\\\\n", - "65 ['61JrslREXq98hurYL2hYoc', '0GF4shudT... 1974-12-31 0.458 \\\\\n", - "66 ['61JrslREXq98hurYL2hYoc'] 1953-12-31 0.457 \\\\\n", - "67 ['2fi9hpqNbi5neTbKSqG0vW', '61JrslREX... 1952-12-01 0.442 \\\\\n", - "68 ['1HY2Jd0NmPuamShAr6KMms'] 2008-01-01 0.762 \\\\\n", - "69 ['43ZHCT0cAZBISjO8DG9PnE'] 1972-06-01 0.478 \\\\\n", - "70 ['0i38tQX5j4gZ0KS3eCMoIl'] 1985-03-01 0.552 \\\\\n", - "71 ['2maQMqxNnlRrBrS1oAsrX9', '3Ry0Bx0jq... 1928-09-25 0.669 \\\\\n", - "72 ['2maQMqxNnlRrBrS1oAsrX9', '0nRShN4m4... 1939-01-24 0.683 \\\\\n", - "73 ['61JrslREXq98hurYL2hYoc'] 1953-12-31 0.699 \\\\\n", - "74 ['5aVKsCIE4jsTKODYwjVVLK'] 2010-08-13 0.613 \\\\\n", - "75 ['1HY2Jd0NmPuamShAr6KMms'] 2011-05-23 0.612 \\\\\n", - "76 ['7dJ3pPuDcHLEwhtlZNJKcr'] 1997-11-06 0.933 \\\\\n", - "77 ['61JrslREXq98hurYL2hYoc'] 1989-12-29 0.441 \\\\\n", - "78 ['0i38tQX5j4gZ0KS3eCMoIl'] 1984-04-01 0.638 \\\\\n", - "79 ['4fr6dA1fcSVYHEptBDaWzN'] 1965-05-06 0.227 \\\\\n", - "80 ['2maQMqxNnlRrBrS1oAsrX9', '4tWwEVgam... 1933-01-07 0.41 \\\\\n", - "81 ['2maQMqxNnlRrBrS1oAsrX9', '1QzkpIrrM... 1932-12-19 0.567 \\\\\n", - "82 ['0i38tQX5j4gZ0KS3eCMoIl'] 1985-09-01 0.521 \\\\\n", - "83 ['61JrslREXq98hurYL2hYoc'] 1948-01-01 0.415 \\\\\n", - "84 ['2KEDbpUlz9nwtGywHT4gyf'] 1981-01-15 0.576 \\\\\n", - "85 ['3cwdHWqqoGRUd57ERrbj1v'] 2004-12-27 0.583 \\\\\n", - "86 ['43ZHCT0cAZBISjO8DG9PnE'] 1957-06-20 0.254 \\\\\n", - "87 ['61JrslREXq98hurYL2hYoc'] 1951-12-31 0.382 \\\\\n", - "88 ['61JrslREXq98hurYL2hYoc'] 1979-12-31 0.261 \\\\\n", - "89 ['01p7Homi0d4XxZ06f2NYYD'] 1956-01-01 0.787 \\\\\n", - "90 ['0i38tQX5j4gZ0KS3eCMoIl'] 1990-02-01 0.69 \\\\\n", - "91 ['43ZHCT0cAZBISjO8DG9PnE'] 1973-02-04 0.211 \\\\\n", - "92 ['2maQMqxNnlRrBrS1oAsrX9'] 1927-09-05 0.899 \\\\\n", - "93 ['43ZHCT0cAZBISjO8DG9PnE'] 1972-06-01 0.331 \\\\\n", - "94 ['61JrslREXq98hurYL2hYoc'] 1965-01-01 0.319 \\\\\n", - "95 ['2maQMqxNnlRrBrS1oAsrX9', '3Ry0Bx0jq... 1928-09-24 0.743 \\\\\n", - "96 ['61JrslREXq98hurYL2hYoc'] 1970-12-31 0.388 \\\\\n", - "97 ['61JrslREXq98hurYL2hYoc'] 1953-12-31 0.523 \\\\\n", - "98 ['01p7Homi0d4XxZ06f2NYYD', '3Y5vifXLG... 1956-01-01 0.58 \\\\\n", - "99 ['0i38tQX5j4gZ0KS3eCMoIl'] 1992-06-01 0.587 \\\\\n", - "100 ['61JrslREXq98hurYL2hYoc', '0gXDpqwYN... 1962-01-01 0.298 \\\\\n", + "1 ['61JrslREXq98hurYL2hYoc'] 1953-01-01 0.488 \\\\\n", + "2 ['61JrslREXq98hurYL2hYoc', '4kcoiVXIx... 1953-01-01 0.371 \\\\\n", + "3 ['61JrslREXq98hurYL2hYoc'] 1952-01-01 0.427 \\\\\n", + "4 ['2maQMqxNnlRrBrS1oAsrX9', '3Ry0Bx0jq... 1929-11-06 0.665 \\\\\n", + "5 ['61JrslREXq98hurYL2hYoc'] 1951-01-01 0.598 \\\\\n", + "6 ['61JrslREXq98hurYL2hYoc'] 1950-01-01 0.352 \\\\\n", + "7 ['43ZHCT0cAZBISjO8DG9PnE'] 1971-10-01 0.459 \\\\\n", + "8 ['61JrslREXq98hurYL2hYoc', '0w4e7HVbq... 1987-09-12 0.495 \\\\\n", + "9 ['2maQMqxNnlRrBrS1oAsrX9', '6IyGH3tMg... 1947-03-15 0.506 \\\\\n", + "10 ['3uml27dlkZH4fmfJnMOty7'] 1988-05-06 0.787 \\\\\n", + "11 ['2maQMqxNnlRrBrS1oAsrX9'] 1927-09-04 0.437 \\\\\n", + "12 ['61JrslREXq98hurYL2hYoc'] 1953-12-31 0.339 \\\\\n", + "13 ['7HkdQ0gt53LP4zmHsL0nap', '7c0XG5cIJ... 2016-02-15 0.649 \\\\\n", + "14 ['61JrslREXq98hurYL2hYoc'] 1953-12-31 0.306 \\\\\n", + "15 ['5V0MlUE1Bft0mbLlND7FJz'] 1957-01-01 0.317 \\\\\n", + "16 ['33JmoNaTffervAivA88tIB'] 2013-04-22 0.471 \\\\\n", + "17 ['0i38tQX5j4gZ0KS3eCMoIl'] 1990-06-01 0.746 \\\\\n", + "18 ['5aVKsCIE4jsTKODYwjVVLK'] 2010-08-13 0.613 \\\\\n", + "19 ['2maQMqxNnlRrBrS1oAsrX9', '4tWwEVgam... 1933-01-07 0.41 \\\\\n", + "20 ['43ZHCT0cAZBISjO8DG9PnE'] 1957-06-20 0.254 \\\\\n", + "21 ['61JrslREXq98hurYL2hYoc'] 1951-12-31 0.382 \\\\\n", + "22 ['0i38tQX5j4gZ0KS3eCMoIl'] 1990-02-01 0.69 \\\\\n", + "23 ['43ZHCT0cAZBISjO8DG9PnE'] 1973-02-04 0.211 \\\\\n", + "24 ['43ZHCT0cAZBISjO8DG9PnE'] 1972-06-01 0.331 \\\\\n", + "25 ['61JrslREXq98hurYL2hYoc'] 1970-12-31 0.388 \\\\\n", + "26 ['5V0MlUE1Bft0mbLlND7FJz', '3EVyH5tLg... 1958-01-01 0.632 \\\\\n", + "27 ['2maQMqxNnlRrBrS1oAsrX9'] 1928-10-03 0.791 \\\\\n", + "28 ['6rqU9HQ57NYGBnBzbrY3a4'] 2003-07-01 0.63 \\\\\n", + "29 ['61JrslREXq98hurYL2hYoc'] 1965-12-06 0.345 \\\\\n", + "30 ['61JrslREXq98hurYL2hYoc', '0GF4shudT... 1977-12-01 0.302 \\\\\n", + "31 ['3Jek5TilNLhv1n7lyOrSCj'] 1991-01-01 0.717 \\\\\n", + "32 ['1z2MqEvpjBXSPiSEpoULkG', '1L2nBl0mN... 1949-12-31 0.359 \\\\\n", + "33 ['2maQMqxNnlRrBrS1oAsrX9', '18BHsxofh... 1951-03-14 0.589 \\\\\n", + "34 ['2maQMqxNnlRrBrS1oAsrX9', '3Ry0Bx0jq... 1931-12-11 0.84 \\\\\n", + "35 ['0i38tQX5j4gZ0KS3eCMoIl'] 1982-01-01 0.709 \\\\\n", + "36 ['61JrslREXq98hurYL2hYoc'] 1953-12-31 0.437 \\\\\n", + "37 ['61JrslREXq98hurYL2hYoc'] 1948-12-31 0.638 \\\\\n", + "38 ['0i38tQX5j4gZ0KS3eCMoIl'] 1984-09-01 0.741 \\\\\n", + "39 ['61JrslREXq98hurYL2hYoc'] 1953-01-01 0.593 \\\\\n", + "40 ['2maQMqxNnlRrBrS1oAsrX9'] 1924-07-12 0.686 \\\\\n", + "41 ['61JrslREXq98hurYL2hYoc'] 1965-09-03 0.428 \\\\\n", + "42 ['3KhZ8YvmlES9GgzDbh7RBk'] 2016-09-14 0.4 \\\\\n", + "43 ['0i38tQX5j4gZ0KS3eCMoIl'] 1982-08-01 0.658 \\\\\n", + "44 ['0i38tQX5j4gZ0KS3eCMoIl'] 1985-06-01 0.663 \\\\\n", + "45 ['61JrslREXq98hurYL2hYoc', '2ae6PxICS... 1989-12-01 0.546 \\\\\n", + "46 ['61JrslREXq98hurYL2hYoc', '4etv0ut4w... 1961-12-30 0.28 \\\\\n", + "47 ['61JrslREXq98hurYL2hYoc'] 1953-01-01 0.595 \\\\\n", + "48 ['5IMA7mgzzqtXuCQYBEYEzX', '4LNkAvde7... 2018-03-23 0.763 \\\\\n", + "49 ['2maQMqxNnlRrBrS1oAsrX9', '6OiarJpZW... 1936-01-18 0.393 \\\\\n", + "50 ['0Ck0U5EF4b0VBMmpZPuUmv', '0GF4shudT... 1989-01-01 0.563 \\\\\n", + "51 ['61JrslREXq98hurYL2hYoc', '3ON8CObQi... 1954-12-31 0.535 \\\\\n", + "52 ['2maQMqxNnlRrBrS1oAsrX9'] 1929-10-15 0.606 \\\\\n", + "53 ['61JrslREXq98hurYL2hYoc'] 1955-12-01 0.299 \\\\\n", + "54 ['2maQMqxNnlRrBrS1oAsrX9'] 1924-07-11 0.524 \\\\\n", + "55 ['5V0MlUE1Bft0mbLlND7FJz'] 1957-01-01 0.286 \\\\\n", + "56 ['50co4Is1HCEo8bhOyUWKpn', '1RyvyyTE3... 2021-04-16 0.841 \\\\\n", + "57 ['61JrslREXq98hurYL2hYoc', '0GF4shudT... 1976-01-27 0.422 \\\\\n", + "58 ['61JrslREXq98hurYL2hYoc', '4etv0ut4w... 1975-03-11 0.419 \\\\\n", + "59 ['7lkL9oVWXjPsVbLh4o1j6Y'] 1977-01-01 0.439 \\\\\n", + "60 ['61JrslREXq98hurYL2hYoc'] 1954-04-30 0.522 \\\\\n", + "61 ['61JrslREXq98hurYL2hYoc', '0GF4shudT... 1953-01-01 0.273 \\\\\n", + "62 ['4HSmSt4gkSk25OHmi7LPNf'] 2020-05-25 0.543 \\\\\n", + "63 ['2maQMqxNnlRrBrS1oAsrX9', '3Ry0Bx0jq... 1930-11-12 0.484 \\\\\n", + "64 ['43ZHCT0cAZBISjO8DG9PnE'] 1960-09-23 0.693 \\\\\n", + "65 ['61JrslREXq98hurYL2hYoc'] 1953-01-01 0.256 \\\\\n", + "66 ['6Fijroi7uqwlQCQk7jvqG5'] 1993-08-13 0.743 \\\\\n", + "67 ['61JrslREXq98hurYL2hYoc', '0GF4shudT... 1974-12-30 0.484 \\\\\n", + "68 ['61JrslREXq98hurYL2hYoc'] 1961-12-31 0.365 \\\\\n", + "69 ['5V0MlUE1Bft0mbLlND7FJz'] 1989-06-20 0.449 \\\\\n", + "70 ['2maQMqxNnlRrBrS1oAsrX9'] 1927-08-16 0.758 \\\\\n", + "71 ['61JrslREXq98hurYL2hYoc'] 1961-12-01 0.573 \\\\\n", + "72 ['2maQMqxNnlRrBrS1oAsrX9', '3Ry0Bx0jq... 1929-10-22 0.625 \\\\\n", + "73 ['4MR6tQyIrWK82b56cYPBDv'] 1961-12-13 0.27 \\\\\n", + "74 ['7cfW4DhoQEwuQsh4R2WEkH', '61JrslREX... 1961-01-01 0.339 \\\\\n", + "75 ['61JrslREXq98hurYL2hYoc'] 1951-12-31 0.463 \\\\\n", + "76 ['61JrslREXq98hurYL2hYoc'] 1991-10-11 0.403 \\\\\n", + "77 ['61JrslREXq98hurYL2hYoc'] 1952-01-01 0.629 \\\\\n", + "78 ['61JrslREXq98hurYL2hYoc', '5as8A4G47... 1951-01-01 0.35 \\\\\n", + "79 ['61JrslREXq98hurYL2hYoc', '1MmP6hxFl... 1949-12-31 0.448 \\\\\n", + "80 ['00tL3eyTBINfgHqk74bM6F', '0huMeTK6u... 1953-01-01 0.696 \\\\\n", + "81 ['43ZHCT0cAZBISjO8DG9PnE'] 2002-09-24 0.481 \\\\\n", + "82 ['61JrslREXq98hurYL2hYoc'] 1952-01-01 0.404 \\\\\n", + "83 ['2maQMqxNnlRrBrS1oAsrX9'] 1929-10-31 0.722 \\\\\n", + "84 ['2maQMqxNnlRrBrS1oAsrX9', '2XhcKxu25... 1930-11-20 0.336 \\\\\n", + "85 ['61JrslREXq98hurYL2hYoc'] 1978-12-31 0.305 \\\\\n", + "86 ['6PozOimyS8a9OxMddMSBCf'] 1996-02-09 0.663 \\\\\n", + "87 ['34eavfJpWV3DnvwqOmml18'] 2001-06-27 0.695 \\\\\n", + "88 ['4thhnp2dS6gYcYMUvEGqOw'] 2000-08-12 0.626 \\\\\n", + "89 ['6v8FB84lnmJs434UJf2Mrm'] 1992-11-02 0.632 \\\\\n", + "90 ['0i38tQX5j4gZ0KS3eCMoIl'] 1981-08-01 0.74 \\\\\n", + "91 ['61JrslREXq98hurYL2hYoc'] 1963-01-12 0.401 \\\\\n", + "92 ['0gXDpqwYNDODn7fB0RDN8J', '61JrslREX... 1970-01-01 0.43 \\\\\n", + "93 ['61JrslREXq98hurYL2hYoc'] 1950-01-01 0.678 \\\\\n", + "94 ['10wjV72OetIdsUQEcjSnOd'] 1998-01-01 0.792 \\\\\n", + "95 ['0i38tQX5j4gZ0KS3eCMoIl'] 1982-03-03 0.648 \\\\\n", + "96 ['4w6rQyebwaBZqbeNaDA6V2'] 1975-01-01 0.45 \\\\\n", + "97 ['6IvnpywSnAcBLBjlyme9oW'] 1998-01-01 0.68 \\\\\n", + "98 ['61JrslREXq98hurYL2hYoc'] 1949-12-01 0.678 \\\\\n", + "99 ['43ZHCT0cAZBISjO8DG9PnE'] 1966-10-24 0.605 \\\\\n", + "100 ['2maQMqxNnlRrBrS1oAsrX9', '5I982BSx3... 1944-03-11 0.569 \\\\\n", "None energy key loudness mode speechiness \\\\\n", - "1 0.253 10 -13.898 1 0.0315 \\\\\n", - "2 0.307 2 -20.492 1 0.0343 \\\\\n", - "3 0.552 11 -10.172 1 0.0291 \\\\\n", - "4 0.301 0 -12.982 1 0.0496 \\\\\n", - "5 0.394 0 -8.485 1 0.0493 \\\\\n", - "6 0.105 9 -25.083 1 0.0768 \\\\\n", - "7 0.566 2 -6.272 0 0.0307 \\\\\n", - "8 0.8 7 -10.102 1 0.0319 \\\\\n", - "9 0.816 5 -6.163 1 0.0544 \\\\\n", - "10 0.305 0 -12.286 1 0.0383 \\\\\n", - "11 0.284 1 -15.414 1 0.0404 \\\\\n", - "12 0.868 7 -10.656 1 0.0349 \\\\\n", - "13 0.102 1 -17.794 0 0.0441 \\\\\n", - "14 0.823 7 -7.559 1 0.0791 \\\\\n", - "15 0.132 2 -12.762 1 0.0612 \\\\\n", - "16 0.208 2 -15.824 1 0.0404 \\\\\n", - "17 0.639 10 -9.681 0 0.0858 \\\\\n", - "18 0.443 0 -8.42 1 0.0862 \\\\\n", - "19 0.537 5 -7.928 0 0.0564 \\\\\n", - "20 0.0989 9 -16.738 1 0.128 \\\\\n", - "21 0.571 7 -10.332 1 0.0297 \\\\\n", - "22 0.444 4 -11.25 1 0.0481 \\\\\n", - "23 0.0653 0 -20.004 1 0.0467 \\\\\n", - "24 0.254 2 -16.081 1 0.0576 \\\\\n", - "25 0.459 6 -11.462 1 0.0409 \\\\\n", - "26 0.196 0 -19.936 1 0.0434 \\\\\n", - "27 0.508 5 -9.181 1 0.942 \\\\\n", - "28 0.267 2 -8.181 0 0.0479 \\\\\n", - "29 0.423 1 -11.926 1 0.594 \\\\\n", - "30 0.114 8 -17.808 1 0.034 \\\\\n", - "31 0.588 2 -11.949 0 0.0311 \\\\\n", - "32 0.271 10 -15.403 1 0.114 \\\\\n", - "33 0.163 5 -14.684 0 0.0455 \\\\\n", - "34 0.356 11 -13.086 1 0.0373 \\\\\n", - "35 0.496 8 -7.984 1 0.379 \\\\\n", - "36 0.647 0 -11.926 1 0.033 \\\\\n", - "37 0.165 0 -9.838 1 0.0651 \\\\\n", - "38 0.478 7 -7.503 0 0.0481 \\\\\n", - "39 0.0786 10 -13.549 0 0.344 \\\\\n", - "40 0.311 11 -10.099 1 0.156 \\\\\n", - "41 0.357 2 -16.187 0 0.0908 \\\\\n", - "42 0.811 7 -10.812 1 0.0585 \\\\\n", - "43 0.208 5 -13.823 1 0.0493 \\\\\n", - "44 0.35 0 -13.48 1 0.0976 \\\\\n", - "45 0.186 6 -17.088 0 0.0613 \\\\\n", - "46 0.26 1 -20.877 1 0.0383 \\\\\n", - "47 0.397 5 -11.92 1 0.0421 \\\\\n", - "48 0.525 5 -4.721 0 0.0974 \\\\\n", - "49 0.426 9 -15.601 1 0.0528 \\\\\n", - "50 0.304 5 -14.584 0 0.0468 \\\\\n", - "51 0.0965 10 -14.877 1 0.0386 \\\\\n", - "52 0.572 5 -6.735 1 0.0633 \\\\\n", - "53 0.55 2 -11.496 1 0.18 \\\\\n", - "54 0.138 5 -14.517 0 0.121 \\\\\n", - "55 0.575 2 -8.483 1 0.0649 \\\\\n", - "56 0.292 11 -7.73 1 0.0437 \\\\\n", - "57 0.578 7 -9.477 1 0.947 \\\\\n", - "58 0.317 6 -11.887 1 0.0571 \\\\\n", - "59 0.255 8 -11.891 1 0.0445 \\\\\n", - "60 0.546 7 -7.799 0 0.0411 \\\\\n", - "61 0.192 2 -17.286 1 0.031 \\\\\n", - "62 0.439 10 -9.751 1 0.0513 \\\\\n", - "63 0.861 11 -5.77 0 0.0 \\\\\n", - "64 0.427 11 -10.489 1 0.0467 \\\\\n", - "65 0.461 4 -8.813 1 0.0513 \\\\\n", - "66 0.145 3 -13.249 0 0.0718 \\\\\n", - "67 0.149 5 -19.236 0 0.0478 \\\\\n", - "68 0.692 5 -3.973 0 0.0438 \\\\\n", - "69 0.725 6 -12.419 0 0.0581 \\\\\n", - "70 0.496 9 -11.347 1 0.763 \\\\\n", - "71 0.141 7 -12.7 1 0.0602 \\\\\n", - "72 0.349 10 -7.777 1 0.0813 \\\\\n", - "73 0.223 4 -13.641 1 0.153 \\\\\n", - "74 0.373 8 -10.255 1 0.0563 \\\\\n", - "75 0.877 0 -4.43 1 0.064 \\\\\n", - "76 0.976 10 -5.414 0 0.0616 \\\\\n", - "77 0.5 8 -7.526 1 0.0357 \\\\\n", - "78 0.43 1 -14.252 1 0.64 \\\\\n", - "79 0.389 7 -10.195 1 0.0306 \\\\\n", - "80 0.111 3 -19.876 1 0.111 \\\\\n", - "81 0.562 5 -5.525 1 0.0384 \\\\\n", - "82 0.633 5 -5.061 1 0.555 \\\\\n", - "83 0.215 5 -13.428 0 0.092 \\\\\n", - "84 0.912 2 -10.304 1 0.0307 \\\\\n", - "85 0.362 2 -13.767 1 0.0253 \\\\\n", - "86 0.0432 1 -18.941 1 0.0354 \\\\\n", - "87 0.457 6 -9.404 1 0.0334 \\\\\n", - "88 0.62 6 -12.014 1 0.0645 \\\\\n", - "89 0.285 9 -12.885 0 0.0565 \\\\\n", - "90 0.485 0 -10.645 1 0.938 \\\\\n", - "91 0.276 0 -14.403 1 0.0492 \\\\\n", - "92 0.262 1 -10.061 1 0.247 \\\\\n", - "93 0.168 0 -14.829 1 0.033 \\\\\n", - "94 0.435 9 -9.548 1 0.0331 \\\\\n", - "95 0.232 11 -14.15 1 0.221 \\\\\n", - "96 0.412 11 -8.471 1 0.0355 \\\\\n", - "97 0.349 11 -10.36 1 0.0349 \\\\\n", - "98 0.474 7 -11.716 0 0.0628 \\\\\n", - "99 0.794 7 -9.216 1 0.835 \\\\\n", - "100 0.319 4 -13.637 1 0.0413 \\\\\n", + "1 0.394 0 -8.485 1 0.0493 \\\\\n", + "2 0.284 1 -15.414 1 0.0404 \\\\\n", + "3 0.102 1 -17.794 0 0.0441 \\\\\n", + "4 0.132 2 -12.762 1 0.0612 \\\\\n", + "5 0.208 2 -15.824 1 0.0404 \\\\\n", + "6 0.0989 9 -16.738 1 0.128 \\\\\n", + "7 0.0653 0 -20.004 1 0.0467 \\\\\n", + "8 0.459 6 -11.462 1 0.0409 \\\\\n", + "9 0.267 2 -8.181 0 0.0479 \\\\\n", + "10 0.588 2 -11.949 0 0.0311 \\\\\n", + "11 0.271 10 -15.403 1 0.114 \\\\\n", + "12 0.163 5 -14.684 0 0.0455 \\\\\n", + "13 0.478 7 -7.503 0 0.0481 \\\\\n", + "14 0.304 5 -14.584 0 0.0468 \\\\\n", + "15 0.0965 10 -14.877 1 0.0386 \\\\\n", + "16 0.572 5 -6.735 1 0.0633 \\\\\n", + "17 0.578 7 -9.477 1 0.947 \\\\\n", + "18 0.373 8 -10.255 1 0.0563 \\\\\n", + "19 0.111 3 -19.876 1 0.111 \\\\\n", + "20 0.0432 1 -18.941 1 0.0354 \\\\\n", + "21 0.457 6 -9.404 1 0.0334 \\\\\n", + "22 0.485 0 -10.645 1 0.938 \\\\\n", + "23 0.276 0 -14.403 1 0.0492 \\\\\n", + "24 0.168 0 -14.829 1 0.033 \\\\\n", + "25 0.412 11 -8.471 1 0.0355 \\\\\n", + "26 0.263 5 -11.066 1 0.0659 \\\\\n", + "27 0.15 11 -12.256 1 0.112 \\\\\n", + "28 0.514 10 -8.005 1 0.0521 \\\\\n", + "29 0.524 5 -11.204 1 0.0521 \\\\\n", + "30 0.548 6 -12.178 1 0.0509 \\\\\n", + "31 0.604 5 -10.383 1 0.0326 \\\\\n", + "32 0.212 11 -16.667 1 0.0639 \\\\\n", + "33 0.432 8 -9.435 1 0.163 \\\\\n", + "34 0.418 2 -6.505 0 0.0737 \\\\\n", + "35 0.337 1 -11.511 1 0.918 \\\\\n", + "36 0.146 11 -16.737 0 0.0603 \\\\\n", + "37 0.14 7 -10.603 0 0.622 \\\\\n", + "38 0.481 11 -11.383 0 0.942 \\\\\n", + "39 0.173 11 -16.732 1 0.244 \\\\\n", + "40 0.235 9 -14.023 1 0.104 \\\\\n", + "41 0.413 3 -6.638 1 0.0319 \\\\\n", + "42 0.993 0 -1.688 1 0.128 \\\\\n", + "43 0.554 0 -11.674 1 0.936 \\\\\n", + "44 0.548 9 -9.953 1 0.888 \\\\\n", + "45 0.436 8 -11.929 1 0.0353 \\\\\n", + "46 0.511 6 -7.005 0 0.0353 \\\\\n", + "47 0.3 9 -20.306 1 0.0481 \\\\\n", + "48 0.311 7 -9.13 1 0.0359 \\\\\n", + "49 0.318 5 -10.832 1 0.0463 \\\\\n", + "50 0.451 5 -10.232 0 0.038 \\\\\n", + "51 0.159 11 -13.643 0 0.115 \\\\\n", + "52 0.332 5 -15.344 1 0.361 \\\\\n", + "53 0.305 2 -11.979 1 0.0365 \\\\\n", + "54 0.532 3 -14.631 1 0.385 \\\\\n", + "55 0.109 5 -16.118 0 0.0355 \\\\\n", + "56 0.595 2 -6.337 1 0.0624 \\\\\n", + "57 0.818 5 -6.325 1 0.0849 \\\\\n", + "58 0.49 9 -12.072 1 0.121 \\\\\n", + "59 0.407 4 -14.017 1 0.0368 \\\\\n", + "60 0.427 6 -10.027 1 0.104 \\\\\n", + "61 0.198 5 -15.998 0 0.0383 \\\\\n", + "62 0.299 4 -12.207 1 0.0297 \\\\\n", + "63 0.309 3 -7.278 1 0.226 \\\\\n", + "64 0.196 3 -15.17 1 0.0506 \\\\\n", + "65 0.217 6 -13.404 1 0.05 \\\\\n", + "66 0.294 7 -16.057 0 0.0691 \\\\\n", + "67 0.377 9 -11.853 1 0.108 \\\\\n", + "68 0.139 11 -14.305 0 0.074 \\\\\n", + "69 0.15 5 -14.033 1 0.0311 \\\\\n", + "70 0.247 6 -11.233 0 0.0549 \\\\\n", + "71 0.71 11 -9.749 1 0.125 \\\\\n", + "72 0.155 7 -14.572 1 0.0586 \\\\\n", + "73 0.305 6 -11.886 0 0.0323 \\\\\n", + "74 0.306 1 -14.054 1 0.0309 \\\\\n", + "75 0.44 9 -8.369 1 0.0972 \\\\\n", + "76 0.52 1 -7.658 1 0.0442 \\\\\n", + "77 0.245 5 -10.759 1 0.0641 \\\\\n", + "78 0.355 0 -15.049 1 0.0448 \\\\\n", + "79 0.212 6 -16.9 1 0.0913 \\\\\n", + "80 0.119 9 -12.514 0 0.041 \\\\\n", + "81 0.733 5 -7.633 1 0.165 \\\\\n", + "82 0.346 2 -15.688 1 0.072 \\\\\n", + "83 0.174 7 -13.415 0 0.136 \\\\\n", + "84 0.394 1 -7.035 1 0.108 \\\\\n", + "85 0.5 11 -6.829 1 0.0287 \\\\\n", + "86 0.979 1 -6.39 1 0.0317 \\\\\n", + "87 0.877 5 -5.747 0 0.0514 \\\\\n", + "88 0.674 2 -6.051 0 0.0233 \\\\\n", + "89 0.179 2 -17.321 1 0.0337 \\\\\n", + "90 0.362 0 -10.78 1 0.778 \\\\\n", + "91 0.191 2 -14.894 0 0.0326 \\\\\n", + "92 0.727 3 -11.18 1 0.134 \\\\\n", + "93 0.447 4 -9.813 1 0.0662 \\\\\n", + "94 0.712 11 -13.994 1 0.047 \\\\\n", + "95 0.696 11 -10.268 1 0.909 \\\\\n", + "96 0.246 7 -13.627 1 0.0291 \\\\\n", + "97 0.637 7 -10.58 1 0.0429 \\\\\n", + "98 0.259 8 -12.537 0 0.0564 \\\\\n", + "99 0.703 10 -7.189 1 0.0377 \\\\\n", + "100 0.0991 2 -13.946 1 0.101 \\\\\n", "None acousticness instrumentalness liveness valence \\\\\n", - "1 0.877 0.0 0.0748 0.164 \\\\\n", - "2 0.91 0.651 0.0866 0.674 \\\\\n", - "3 0.438 1.37e-05 0.126 0.843 \\\\\n", - "4 0.977 0.0424 0.395 0.585 \\\\\n", - "5 0.944 0.000236 0.36 0.739 \\\\\n", - "6 0.979 0.889 0.103 0.64 \\\\\n", - "7 0.0145 0.000114 0.113 0.438 \\\\\n", - "8 0.0213 0.279 0.122 0.533 \\\\\n", - "9 0.0442 0.00141 0.0442 0.836 \\\\\n", - "10 0.771 1.05e-06 0.0742 0.327 \\\\\n", - "11 0.982 0.0762 0.178 0.441 \\\\\n", - "12 0.00185 5.69e-05 0.126 0.727 \\\\\n", - "13 0.994 0.957 0.189 0.555 \\\\\n", - "14 0.811 0.129 0.251 0.777 \\\\\n", - "15 0.993 0.034 0.139 0.531 \\\\\n", - "16 0.891 3.1e-05 0.121 0.728 \\\\\n", - "17 0.976 0.0218 0.448 0.758 \\\\\n", - "18 0.987 0.0188 0.35 0.96 \\\\\n", - "19 0.673 9.61e-06 0.133 0.404 \\\\\n", - "20 0.995 0.918 0.0989 0.416 \\\\\n", - "21 0.792 6.24e-06 0.0735 0.844 \\\\\n", - "22 0.989 0.558 0.373 0.322 \\\\\n", - "23 0.961 0.00183 0.107 0.301 \\\\\n", - "24 0.996 0.952 0.255 0.352 \\\\\n", - "25 0.785 3.9e-06 0.152 0.696 \\\\\n", - "26 0.902 0.0313 0.161 0.751 \\\\\n", - "27 0.826 0.0 0.0821 0.734 \\\\\n", - "28 0.977 0.458 0.331 0.597 \\\\\n", - "29 0.476 0.0 0.15 0.506 \\\\\n", - "30 0.944 0.00684 0.134 0.234 \\\\\n", - "31 0.228 0.501 0.362 0.636 \\\\\n", - "32 0.995 0.866 0.114 0.845 \\\\\n", - "33 0.994 0.912 0.311 0.337 \\\\\n", - "34 0.888 0.000353 0.131 0.0661 \\\\\n", - "35 0.995 0.75 0.829 0.835 \\\\\n", - "36 0.619 0.32 0.0579 0.936 \\\\\n", - "37 0.996 0.531 0.0934 0.327 \\\\\n", - "38 0.274 0.0 0.176 0.151 \\\\\n", - "39 0.995 0.572 0.418 0.68 \\\\\n", - "40 0.993 0.653 0.336 0.902 \\\\\n", - "41 0.982 0.031 0.0925 0.703 \\\\\n", - "42 0.0297 0.0 0.274 0.904 \\\\\n", - "43 0.994 0.0409 0.134 0.687 \\\\\n", - "44 0.992 0.919 0.236 0.808 \\\\\n", - "45 0.992 0.908 0.113 0.821 \\\\\n", - "46 0.94 0.000828 0.147 0.597 \\\\\n", - "47 0.792 1.49e-06 0.0566 0.437 \\\\\n", - "48 0.767 0.0 0.915 0.858 \\\\\n", - "49 0.993 0.916 0.115 0.964 \\\\\n", - "50 0.994 0.254 0.173 0.471 \\\\\n", - "51 0.972 3.78e-06 0.0784 0.088 \\\\\n", - "52 0.317 0.0 0.0588 0.177 \\\\\n", - "53 0.856 3.44e-05 0.0907 0.844 \\\\\n", - "54 0.994 0.656 0.272 0.6 \\\\\n", - "55 0.938 0.00731 0.274 0.453 \\\\\n", - "56 0.988 0.0227 0.325 0.616 \\\\\n", - "57 0.569 0.0 0.741 0.63 \\\\\n", - "58 0.717 0.0312 0.169 0.257 \\\\\n", - "59 0.98 0.702 0.277 0.2 \\\\\n", - "60 0.967 0.325 0.373 0.847 \\\\\n", - "61 0.339 1.32e-05 0.127 0.233 \\\\\n", - "62 0.925 0.00063 0.129 0.85 \\\\\n", - "63 0.00209 0.0 0.2 0.0 \\\\\n", - "64 0.839 1.54e-05 0.294 0.925 \\\\\n", - "65 0.967 0.00046 0.118 0.692 \\\\\n", - "66 0.987 5.18e-05 0.123 0.557 \\\\\n", - "67 0.983 0.369 0.199 0.482 \\\\\n", - "68 0.113 0.0 0.094 0.397 \\\\\n", - "69 0.106 0.166 0.633 0.692 \\\\\n", - "70 0.772 0.0 0.522 0.446 \\\\\n", - "71 0.995 0.483 0.124 0.54 \\\\\n", - "72 0.941 0.00157 0.089 0.82 \\\\\n", - "73 0.98 0.00449 0.0976 0.859 \\\\\n", - "74 0.296 0.00671 0.152 0.419 \\\\\n", - "75 0.000992 0.00563 0.462 0.38 \\\\\n", - "76 0.0583 0.000453 0.321 0.931 \\\\\n", - "77 0.785 0.00441 0.0697 0.574 \\\\\n", - "78 0.719 0.0 0.813 0.448 \\\\\n", - "79 0.887 1e-06 0.104 0.422 \\\\\n", - "80 0.995 0.303 0.249 0.511 \\\\\n", - "81 0.945 0.0699 0.716 0.871 \\\\\n", - "82 0.655 0.0 0.456 0.669 \\\\\n", - "83 0.995 0.877 0.188 0.83 \\\\\n", - "84 0.00152 0.00279 0.0452 0.961 \\\\\n", - "85 0.0824 0.000729 0.0862 0.323 \\\\\n", - "86 0.974 0.00279 0.103 0.357 \\\\\n", - "87 0.939 1.05e-06 0.154 0.609 \\\\\n", - "88 0.962 0.868 0.579 0.803 \\\\\n", - "89 0.624 0.087 0.148 0.709 \\\\\n", - "90 0.457 0.0 0.582 0.753 \\\\\n", - "91 0.825 0.41 0.696 0.144 \\\\\n", - "92 0.995 0.374 0.206 0.693 \\\\\n", - "93 0.538 0.0997 0.589 0.0588 \\\\\n", - "94 0.949 0.00273 0.127 0.476 \\\\\n", - "95 0.993 0.721 0.108 0.809 \\\\\n", - "96 0.945 2.46e-05 0.184 0.45 \\\\\n", - "97 0.991 0.0 0.252 0.593 \\\\\n", - "98 0.495 8.34e-05 0.214 0.966 \\\\\n", - "99 0.179 0.0 0.473 0.266 \\\\\n", - "100 0.968 0.0386 0.124 0.579 \\\\\n", + "1 0.944 0.000236 0.36 0.739 \\\\\n", + "2 0.982 0.0762 0.178 0.441 \\\\\n", + "3 0.994 0.957 0.189 0.555 \\\\\n", + "4 0.993 0.034 0.139 0.531 \\\\\n", + "5 0.891 3.1e-05 0.121 0.728 \\\\\n", + "6 0.995 0.918 0.0989 0.416 \\\\\n", + "7 0.961 0.00183 0.107 0.301 \\\\\n", + "8 0.785 3.9e-06 0.152 0.696 \\\\\n", + "9 0.977 0.458 0.331 0.597 \\\\\n", + "10 0.228 0.501 0.362 0.636 \\\\\n", + "11 0.995 0.866 0.114 0.845 \\\\\n", + "12 0.994 0.912 0.311 0.337 \\\\\n", + "13 0.274 0.0 0.176 0.151 \\\\\n", + "14 0.994 0.254 0.173 0.471 \\\\\n", + "15 0.972 3.78e-06 0.0784 0.088 \\\\\n", + "16 0.317 0.0 0.0588 0.177 \\\\\n", + "17 0.569 0.0 0.741 0.63 \\\\\n", + "18 0.296 0.00671 0.152 0.419 \\\\\n", + "19 0.995 0.303 0.249 0.511 \\\\\n", + "20 0.974 0.00279 0.103 0.357 \\\\\n", + "21 0.939 1.05e-06 0.154 0.609 \\\\\n", + "22 0.457 0.0 0.582 0.753 \\\\\n", + "23 0.825 0.41 0.696 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0.809 0.393 0.469 \\\\\n", + "50 0.802 2.83e-06 0.282 0.538 \\\\\n", + "51 0.992 0.725 0.404 0.704 \\\\\n", + "52 0.992 0.839 0.169 0.964 \\\\\n", + "53 0.986 0.036 0.117 0.403 \\\\\n", + "54 0.996 0.943 0.131 0.63 \\\\\n", + "55 0.985 0.000465 0.33 0.128 \\\\\n", + "56 0.0025 0.0 0.12 0.3 \\\\\n", + "57 0.654 0.0 0.204 0.905 \\\\\n", + "58 0.841 2.74e-06 0.407 0.634 \\\\\n", + "59 0.957 0.00416 0.363 0.692 \\\\\n", + "60 0.955 0.201 0.125 0.727 \\\\\n", + "61 0.985 0.149 0.132 0.612 \\\\\n", + "62 0.608 0.0 0.136 0.183 \\\\\n", + "63 0.991 0.487 0.421 0.813 \\\\\n", + "64 0.906 0.0 0.0705 0.83 \\\\\n", + "65 0.995 0.914 0.472 0.654 \\\\\n", + "66 0.772 2.02e-05 0.178 0.724 \\\\\n", + "67 0.888 0.0 0.0867 0.683 \\\\\n", + "68 0.995 0.805 0.15 0.59 \\\\\n", + "69 0.918 0.0 0.125 0.221 \\\\\n", + "70 0.994 0.914 0.146 0.708 \\\\\n", + "71 0.904 0.000112 0.4 0.959 \\\\\n", + "72 0.995 0.766 0.115 0.725 \\\\\n", + "73 0.295 6.28e-06 0.189 0.366 \\\\\n", + "74 0.921 0.000508 0.153 0.706 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4 \n", + "93 118.425 4 \n", + "94 102.436 4 \n", + "95 117.78 3 \n", + "96 87.271 3 \n", + "97 97.285 3 \n", + "98 123.291 4 \n", + "99 139.878 4 \n", + "100 125.484 4 \n", "Rows: 1-100 | Columns: 20" ] }, + "execution_count": 7, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "display(artists)\n", - "display(tracks)" + "tracks.head(100)" ] }, { @@ -1066,222 +1079,222 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "id": "6569287c-5704-455e-b216-b262f70e3ff4", "metadata": {}, "outputs": [ { "data": { "text/html": [ - "
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Rows: 1-100 | Columns: 5
" ], "text/plain": [ "None id followers genres \\\\\n", "1 004reCzVFOidvBuYrYia9Y 12726.0 ['polish punk'] \\\\\n", - "2 00drc18J6PkIXn24widBC5 3.0 ['polish ambient'] \\\\\n", - "3 00ekfPE5ZS3NwF8H8o8GBk 17574.0 ['disco polo'] \\\\\n", - "4 018gIUaP08hROTOiVdiEQ3 584.0 ['polish black metal'] \\\\\n", - "5 01BlTZ696EkKe6xr56Gu6G 362.0 ['polish free jazz'] \\\\\n", - "6 01TgMAgIALWvVXlKjUwpfn 1063.0 ['polish alternative rock', 'polish p... \\\\\n", - "7 0244q9rIqAIzBFXKNNRN6O 27393.0 ['classic polish pop', 'polish pop'] \\\\\n", - "8 02Cq85QmaYHDi4dW7AxTRZ 748.0 ['polish electronica'] \\\\\n", - "9 02ESuuto8Jwyo4PeiJ1Xim 149.0 ['polish synthpop'] \\\\\n", - "10 02JmHOSFJi2bLjGnO274di 8817.0 ['polish punk', 'szanty'] \\\\\n", - "11 02LrsTMdnHVvKmXxN0epQF 753.0 ['deep soundtrack', 'polish synthpop'] \\\\\n", - "12 02eZEXslMzAjHDkygNJHSX 8010.0 ['polish trap'] \\\\\n", - "13 02keDoJak6YO12KBJFMFNm 1873.0 ['polish punk', 'polish reggae'] \\\\\n", - "14 02tQ309SzZZ0bYs2yyO60G 11734.0 ['polish hip hop'] \\\\\n", - "15 0338weYyACbkc5ERuLnFTa 270.0 ['classic polish pop'] \\\\\n", - "16 033WIygOyXwUjc1vfCGxJ2 126.0 ['polish black metal'] \\\\\n", - "17 03Dy3XKBUsC3vJLCuF0T7I 152.0 ['polish jazz'] \\\\\n", - "18 03FgbE2vKKVEFBFHi8IfJG 184761.0 ['polish hip hop'] \\\\\n", - "19 03KLzHVK6la8dVop1iVI5x 63817.0 ['poezja spiewana', 'polish alternati... \\\\\n", - "20 03ZzgzybQr8UyvWCMSCvRy 1363.0 ['polish noise rock'] \\\\\n", - "21 03jLJnyfZXs1ssrIALfGRm 2633.0 ['classic polish pop'] \\\\\n", - "22 03ohDYwWFrXfgp0VEtSTiF 706.0 ['polish thrash metal'] \\\\\n", - "23 03qKjVTzyKc3SyTjHaOpFc 2376.0 ['neo-progressive', 'polish prog'] \\\\\n", - "24 03rREATXGWcD2CfG3OXDZY 10155.0 ['polish alternative rap', 'polish hi... \\\\\n", - "25 03wQEnXSEAI6GmOKZ90G25 1597.0 ['historic piano performance', 'polis... \\\\\n", - "26 03xKZpOUZOQjf7g5WBN4ee 3676.0 ['polish alternative', 'polish indie'] \\\\\n", - "27 03yP3BHBnpGyvddEoIGnsx 2089.0 ['polish black metal'] \\\\\n", - "28 04Lio76CKJCMPbK5hV6J4w 1876.0 ['black noise', 'polish black metal',... \\\\\n", - "29 04Loj16dRX1yZodeEQlCOv 308.0 ['polish jazz'] \\\\\n", - "30 04WxKoI0kS5JclvQ8rn8qp 13.0 ['polish contemporary classical'] \\\\\n", - "31 04bDWf1u7HxKdskC3N2nIk 27127.0 ['polish metal', 'polish punk', 'poli... \\\\\n", - "32 05AVHcWP9DF6y6LEU845uz 1545.0 ['classic polish pop'] \\\\\n", - "33 05Fgqq7GfWeNol1TR5H3og 15868.0 ['polish pop'] \\\\\n", - "34 05UsyksBcAUVdfyREMxbDm 294.0 ['disco polo'] \\\\\n", - "35 063D0MKbIbbBjKgtYRGBga 7458.0 ['polish alternative', 'polish electr... \\\\\n", - "36 0690wuO0NVERuqxuoi2mTF 319.0 ['polish ambient', 'polish experiment... \\\\\n", - "37 06O52v4thQuBoLC6jWatGW 21.0 ['polish free jazz'] \\\\\n", - "38 06UcKJxYJXthEwn0c8XOCt 11024.0 ['dark black metal', 'polish black me... \\\\\n", - "39 06wBGqhkbyUAtVNMbbcK1x 607.0 ['polish folk'] \\\\\n", - "40 070tdNOiP3pIsGlqNfVkG3 86130.0 ['polish hip hop'] \\\\\n", - "41 072HrG3T5BaaBj4YhKIkxv 1166.0 ['polish alternative rock'] \\\\\n", - "42 07ILo13zpakvXxTL3VtqwS 540.0 ['disco polo'] \\\\\n", - "43 07PJCYnjHeYanDnFnUALU4 269.0 ['historic piano performance', 'polis... \\\\\n", - "44 098RsUTij7grC7evZUhWwA 720.0 ['polish trap'] \\\\\n", - "45 09MjLGtslj39ILxA1MqUny 556.0 ['polish hip hop'] \\\\\n", - "46 09ScR35g0VzipHacuPtXZd 440.0 ['polish modern jazz'] \\\\\n", - "47 09Z3SI4GkhYjpCB6884vC8 10395.0 ['polish alternative', 'polish indie'... \\\\\n", - "48 09j4UTVH7vk7fVfVB71roU 348.0 ['polish indie', 'polish indie rock'] \\\\\n", - "49 0AEQNlJAZeghMaFyIYfrQG 138546.0 ['polish hip hop'] \\\\\n", - "50 0AYJ3eg4zKi9ilGrhVaINs 2186.0 ['polish jazz', 'polish modern jazz'] \\\\\n", - "51 0AZgkXW6n0zfyOhVAnIopA 1109.0 ['polish alternative'] \\\\\n", - "52 0At3wjxYzZL9WwqbFR0JL8 24.0 ['polish jazz'] \\\\\n", - "53 0BBB9DjvskQV0oReJMxTP1 30889.0 ['polish alternative rap'] \\\\\n", - "54 0BQIhJ61mCyaOrVrMJ7e8k 5.0 ['polish ambient'] \\\\\n", - "55 0CEw36eWG0dYKCXOX8eUoO 77804.0 ['polish pop'] \\\\\n", - "56 0CI4rQj50Dcr30HpiD2LF6 165.0 ['polish classical piano'] \\\\\n", - "57 0CgCy79P84g1meaXcwwFqZ 80.0 ['polish free jazz'] \\\\\n", - "58 0CsrftI3Zs3nvfSW6MRglc 50.0 ['polish ambient'] \\\\\n", - "59 0D5kXlS7UOApMpTyuSrFAW 40370.0 ['polish punk', 'polish rock', 'pozna... \\\\\n", - "60 0D9mwbJP5sUH7XYXg4F7u9 580.0 ['polish black metal'] \\\\\n", - "61 0E6TslMisIITlZ1QjjPXeo 110.0 ['polish prog'] \\\\\n", - "62 0EDBV0NVPOftbsEM0fg7WZ 2004.0 ['polish alternative rock'] \\\\\n", - "63 0EMDndPZcpfg9Qqgos0S7G 73.0 ['polish post-punk'] \\\\\n", - "64 0EPzUAW8kwuPedmmVP6n9S 99964.0 ['polish hip hop'] \\\\\n", - "65 0EQaqT3oKtxAGR0Y5c1Jme 3572.0 ['polish jazz'] \\\\\n", - "66 0EYfWGAHPugeWUKKvoMU79 336.0 ['polish post-punk'] \\\\\n", - "67 0Emf6MyFoCjKazTqoaUu6T 1107.0 ['polish jazz'] \\\\\n", - "68 0EvkY8O19trlgsfrVOTQgg 26661.0 ['polish blues', 'polish punk', 'poli... \\\\\n", - "69 0F1DvSOKRaSA6XKSwDNs40 10792.0 ['polish alternative', 'polish pop'] \\\\\n", - "70 0FKOL5wp6sgB8VRNsJaUlz 430.0 ['disco polo'] \\\\\n", - "71 0FbccBQBb69lfv4arbt6kX 9237.0 ['polish alternative', 'polish indie'] \\\\\n", - "72 0G2VUqbZ4C28aN9y41Wp3G 1186.0 ['polish jazz'] \\\\\n", - "73 0G6miz5dLrc3NZWi4ZYdJK 2813.0 ['disco polo'] \\\\\n", - "74 0GF5CJ7nKXsMTiWHK4ZQJN 30925.0 ['polish pop'] \\\\\n", - "75 0GPJYkHJm0Fpbhjovpm1h1 2261.0 ['polish synthpop'] \\\\\n", - "76 0GPfyyiTlLdG6rQthueRBM 682.0 ['disco polo'] \\\\\n", - "77 0GQZc3zcll9HXIVaUA1XzJ 11211.0 ['polish reggae'] \\\\\n", - "78 0Gfk7Ww29CWVyrnkqC4KUt 7.0 ['polish punk'] \\\\\n", - "79 0Gk98lHv6LlqbWPwdMiga2 247229.0 ['polish alternative', 'polish pop'] \\\\\n", - "80 0GnO5BjJfHFwkesoObGU36 61.0 ['polish modern jazz'] \\\\\n", - "81 0GsCeqHAG63k8CRj1NH8e4 164.0 ['polish alternative rock', 'polish i... \\\\\n", - "82 0GxARImYCmCNz0v04YjPq2 179.0 ['polish indie'] \\\\\n", - "83 0GykMtlKoc68Hj2jwZLXul 79213.0 ['classic polish pop', 'polish altern... \\\\\n", - "84 0HC5DGqdUzXorIXUudkeWG 1805.0 ['polish classical', 'post-romantic e... \\\\\n", - "85 0HLMuuBFA7R4boMxVl9QgQ 9967.0 ['polish alternative', 'polish indie'] \\\\\n", - "86 0HTub0NhKSRgggtmJBP9aR 59.0 ['polish techno'] \\\\\n", - "87 0HZL4dV60t13CHasIHwaLP 385.0 ['polish post-rock', 'poznan indie'] \\\\\n", - "88 0HhejlCvg1WCO9nXNZGEkc 144.0 ['polish experimental electronic'] \\\\\n", - "89 0Hob9LUr2x0SULSZjuf6li 10701.0 ['disco polo'] \\\\\n", - "90 0Id5ZU9SxHcgE32nfJMTbh 259.0 ['polish trap'] \\\\\n", - "91 0It4rGfBk31UDyK9x6uZvP 3056.0 ['melodic black metal', 'polish black... \\\\\n", - "92 0IuXBtCmOjyRjzbfJmfKHa 13.0 ['polish ambient'] \\\\\n", - "93 0Jl6TFKAJR7zIv2kvA1RNf 60054.0 ['polish pop'] \\\\\n", - "94 0K0Sa7amVwCmQKz7ZHRRim 3005.0 ['polish pop'] \\\\\n", - "95 0KNOQSBwQim4GXpZHekrvu 1728.0 ['polish trap'] \\\\\n", - "96 0KTn3DOb57GcGjPoA09ABL 4.0 ['polish techno'] \\\\\n", - "97 0KZLEvrZHdqVDKdclXRVK0 7.0 ['polish techno'] \\\\\n", - "98 0KirHnU7pIfeMYWSJ6xm8I 1309.0 ['polish blues'] \\\\\n", - "99 0Ks3WKQ64ZmWa3QkbbeCbj 129.0 ['polish indie'] \\\\\n", - "100 0LX2VNf5w4iOHW1yyIqb74 1016980.0 ['polish hip hop', 'polish trap'] \\\\\n", + "2 00ekfPE5ZS3NwF8H8o8GBk 17574.0 ['disco polo'] \\\\\n", + "3 01TgMAgIALWvVXlKjUwpfn 1063.0 ['polish alternative rock', 'polish p... \\\\\n", + "4 02Cq85QmaYHDi4dW7AxTRZ 748.0 ['polish electronica'] \\\\\n", + "5 02ESuuto8Jwyo4PeiJ1Xim 149.0 ['polish synthpop'] \\\\\n", + "6 03FgbE2vKKVEFBFHi8IfJG 184761.0 ['polish hip hop'] \\\\\n", + "7 03KLzHVK6la8dVop1iVI5x 63817.0 ['poezja spiewana', 'polish alternati... \\\\\n", + "8 03jLJnyfZXs1ssrIALfGRm 2633.0 ['classic polish pop'] \\\\\n", + "9 04Lio76CKJCMPbK5hV6J4w 1876.0 ['black noise', 'polish black metal',... \\\\\n", + "10 05AVHcWP9DF6y6LEU845uz 1545.0 ['classic polish pop'] \\\\\n", + "11 05Fgqq7GfWeNol1TR5H3og 15868.0 ['polish pop'] \\\\\n", + "12 05UsyksBcAUVdfyREMxbDm 294.0 ['disco polo'] \\\\\n", + "13 070tdNOiP3pIsGlqNfVkG3 86130.0 ['polish hip hop'] \\\\\n", + "14 0CgCy79P84g1meaXcwwFqZ 80.0 ['polish free jazz'] \\\\\n", + "15 0CsrftI3Zs3nvfSW6MRglc 50.0 ['polish ambient'] \\\\\n", + "16 0EPzUAW8kwuPedmmVP6n9S 99964.0 ['polish hip hop'] \\\\\n", + "17 0EYfWGAHPugeWUKKvoMU79 336.0 ['polish post-punk'] \\\\\n", + "18 0EvkY8O19trlgsfrVOTQgg 26661.0 ['polish blues', 'polish punk', 'poli... \\\\\n", + "19 0FbccBQBb69lfv4arbt6kX 9237.0 ['polish alternative', 'polish indie'] \\\\\n", + "20 0GPfyyiTlLdG6rQthueRBM 682.0 ['disco polo'] \\\\\n", + "21 0Gk98lHv6LlqbWPwdMiga2 247229.0 ['polish alternative', 'polish pop'] \\\\\n", + "22 0GsCeqHAG63k8CRj1NH8e4 164.0 ['polish alternative rock', 'polish i... \\\\\n", + "23 0HTub0NhKSRgggtmJBP9aR 59.0 ['polish techno'] \\\\\n", + "24 0HZL4dV60t13CHasIHwaLP 385.0 ['polish post-rock', 'poznan indie'] \\\\\n", + "25 0HhejlCvg1WCO9nXNZGEkc 144.0 ['polish experimental electronic'] \\\\\n", + "26 0Id5ZU9SxHcgE32nfJMTbh 259.0 ['polish trap'] \\\\\n", + "27 0KTn3DOb57GcGjPoA09ABL 4.0 ['polish techno'] \\\\\n", + "28 0KZLEvrZHdqVDKdclXRVK0 7.0 ['polish techno'] \\\\\n", + "29 0KirHnU7pIfeMYWSJ6xm8I 1309.0 ['polish blues'] \\\\\n", + "30 0LcUNEKY8mVqNmYfrgZrxl 5803.0 ['disco polo'] \\\\\n", + "31 0M5UiR76X2ybfo6N9iVNWr 27540.0 ['polish pop'] \\\\\n", + "32 0MQyjuZSqwUlAmWo7bryry 352.0 ['historic piano performance', 'polis... \\\\\n", + "33 0MXVKY88dOygNxQSjYAiCn 1269.0 ['polish punk'] \\\\\n", + "34 0MzWXIO3Z73PfIwg0UUGHm 21677.0 ['polish punk'] \\\\\n", + "35 0NMfHNHHyEUp2DZxIXyA0c 43.0 ['polish post-punk'] \\\\\n", + "36 0NiIlOoQCQPrri3Mnzb41D 2747.0 ['polish reggae'] \\\\\n", + "37 0OWXK55YvtWja5pKp8vqXL 738.0 ['polish hardcore'] \\\\\n", + "38 0PbRHFtbXsxQfOHl6m86dd 9037.0 ['polish electronica'] \\\\\n", + "39 0PtPpPyhP8KRgSwYDvhPlE 398.0 ['disco polo'] \\\\\n", + "40 0Qo6PIs38oznVHFxs9WU0N 18675.0 ['polish alternative rap', 'polish hi... \\\\\n", + "41 0RLhLvcRdN4LsXUvRsL9rM 2290.0 ['disco polo'] \\\\\n", + "42 0T0rADxhl1CLxhSS3t4FJr 3710.0 ['polish alternative', 'polish indie'... \\\\\n", + "43 0T0yIgJd9ZIeVJqZw276iH 1162.0 ['polish punk'] \\\\\n", + "44 0TdjP78ddOnKTEVuF3LBrT 20752.0 ['disco polo'] \\\\\n", + "45 0UCbjuZR3UYm9XtycKimCz 28225.0 ['polish punk'] \\\\\n", + "46 0UvDCk7VwDQ0JWGeTTaGpB 25.0 ['polish black metal'] \\\\\n", + "47 0VJDqh2nHbXaafoaDbecop 285.0 ['polish jazz'] \\\\\n", + "48 0VeG3URJkBzh0CHJqZqmPL 2116.0 ['polish punk'] \\\\\n", + "49 0VhKsa9J4dkGjkSHwthPUl 508.0 ['polish experimental electronic'] \\\\\n", + "50 0W0udbffr9z2chRB5eiq9W 4087.0 ['polish hip hop'] \\\\\n", + "51 0WDJa0qnagyOnMaiD26wht 147984.0 ['polish hip hop', 'polish trap'] \\\\\n", + "52 0WKQQ0JVwqVfaCUeocL81k 60.0 ['polish experimental'] \\\\\n", + "53 0WRMNsx6J1XPOIYhxs2ZQy 5536.0 ['polish hip hop'] \\\\\n", + "54 0WX7MXOUx7elCFdxdgvdBU 24386.0 ['polish alternative', 'polish pop'] \\\\\n", + "55 0XqtseX3XzxM4MwPlVLDBJ 570.0 ['polish black metal', 'polish folk m... \\\\\n", + "56 0XuTvNiI3kFV0Jpt5MTaMf 58.0 ['polish modern jazz'] \\\\\n", + "57 0Y0MpkBrGD02Cx3Mmhfa9I 45819.0 ['polish rock'] \\\\\n", + "58 0aquWYdumRf3dKccHKaQ25 648.0 ['polish punk'] \\\\\n", + "59 0bbSbmpfnelM4nQfogVk9B 114.0 ['polish indie', 'polish indie rock',... \\\\\n", + "60 0bfBH61NEvZOmVTUyUL1yO 19271.0 ['polish pop'] \\\\\n", + "61 0buOvM3DxsknoPmgGufB5B 55.0 ['polish jazz'] \\\\\n", + "62 0c7soAA3Nv5aaDBMtCy7v4 7987.0 ['disco polo'] \\\\\n", + "63 0cFQLs28WprLqNslPA1vBH 232.0 ['polish ambient'] \\\\\n", + "64 0fgRKFA5ecwbbU6u6nSh2J 710.0 ['polish electronica'] \\\\\n", + "65 0g8uDsDCthOato1OArQG4d 106.0 ['disco polo'] \\\\\n", + "66 0hmW4jgeM8oo7PrTja7KzY 777.0 ['disco polo'] \\\\\n", + "67 0jEJGHxA3gkLdjviT1H0wk 6926.0 ['polish pop'] \\\\\n", + "68 0kh9Gvy9lGZsq84x7I37DC 132582.0 ['polish hip hop', 'polish trap'] \\\\\n", + "69 0lKCO7SCRiTCS4ZEU6l1zx 178580.0 ['polish pop'] \\\\\n", + "70 0lTe15Ofpyg39nXvLNAfcm 7723.0 ['historic piano performance', 'polis... \\\\\n", + "71 0lUa6o7QrvyJKszdaBnoAH 104060.0 ['polish alternative', 'polish post-p... \\\\\n", + "72 0mGMdkeDynbGXSVd0PY8Oq 38812.0 ['polish alternative rap', 'polish hi... \\\\\n", + "73 0mHLX59DLqrZHIo8mOhiBG 2147.0 ['polish punk'] \\\\\n", + "74 0mneo6UHjcOtZBm1Tw8t67 934.0 ['polish ambient', 'polish experiment... \\\\\n", + "75 0pUbw5HdKXcSz6luKNyOiR 234.0 ['polish reggae'] \\\\\n", + "76 0q4Dul29Bz5se2iYcKPQXA 503.0 ['polish electronica'] \\\\\n", + "77 0qI3BHXdNAjGHu3NqRaacs 145.0 ['polish hip hop'] \\\\\n", + "78 0sgX7YgncTMJs40ANv08V2 121.0 ['polish jazz'] \\\\\n", + "79 0sijpMmVF9ui4micUVn9d6 4055.0 ['classic polish pop'] \\\\\n", + "80 0tLpQEO7WioDR2cjo3SgWj 64.0 ['polish punk'] \\\\\n", + "81 0tMBk4ZobHzjogZ2911v6y 285.0 ['polish electronica'] \\\\\n", + "82 0tmTvcGSgfSn6dLFNxC3Sd 14545.0 ['polish punk'] \\\\\n", + "83 0xBUHtBX1kujjjbayPiYOq 222.0 ['experimental black metal', 'industr... \\\\\n", + "84 0z0ey55umWNi8s2HsNaGxB 49609.0 ['polish hip hop'] \\\\\n", + "85 0zrHcdKNA1olsruclYjy7h 2368.0 ['polish indie'] \\\\\n", + "86 10HoQ9uLWCt4YoiaYkmQVU 611.0 ['polish ambient', 'polish electronica'] \\\\\n", + "87 10ki5CunLQjvMB093EClw3 34.0 ['polish classical'] \\\\\n", + "88 11mE3U9BBkGQcOty6rOXUw 3389.0 ['polish hip hop'] \\\\\n", + "89 12C8rZ4SY6WxvuxqykeKw6 20.0 ['polish early music'] \\\\\n", + "90 12fqDmzvnOz7oQE5J2XDfL 24.0 ['polish reggae'] \\\\\n", + "91 138bq70hDEiUOtwGFRKB9M 4474.0 ['disco polo'] \\\\\n", + "92 13BySi42Trub84QyO83Q6c 42.0 ['polish psychedelia'] \\\\\n", + "93 154o9Wi0JpSDbYQPMtmpd5 27532.0 ['polish hip hop', 'polish trap'] \\\\\n", + "94 15kkqvIcypRQGUiE17Shej 1371.0 ['polish blues'] \\\\\n", + "95 161n5VNTH8MQ8hh5jgwewr 95.0 ['polish contemporary classical', 'po... \\\\\n", + "96 16E01HKHSbeo1s2GB0zam5 176.0 ['polish choir', 'uwielbienie'] \\\\\n", + "97 16IE8lpWA2U3bfB4kumGzW 4462.0 ['disco polo'] \\\\\n", + "98 16TsNPlesuA1R9kPLS6nta 4768.0 ['polish hip hop', 'polish trap'] \\\\\n", + "99 177K31OvglpG0Epy24mWyd 645.0 ['polish folk', 'polish modern jazz'] \\\\\n", + "100 17CHv5PPFzmVshxqUpGEdZ 2690.0 ['classic polish pop', 'poezja spiewa... \\\\\n", "None name popularity \n", "1 Zielone Żabki 27 \n", - "2 Nasoshnik 0 \n", - "3 Mig 47 \n", - "4 Massemord 8 \n", - "5 Mazzoll 3 \n", - "6 Radio Bagdad 9 \n", - "7 Ryszard Rynkowski 40 \n", - "8 Evorevo 9 \n", - "9 Polpo Motel 1 \n", - "10 Spięty 31 \n", - "11 Andrzej Korzyñski 22 \n", - "12 Popkiller Młode Wilki 5 26 \n", - "13 Skampararas 15 \n", - "14 Buczer 30 \n", - "15 Iwona Loranc 17 \n", - "16 Demonic Slaughter 0 \n", - "17 Chromosomos 1 \n", - "18 Chada 55 \n", - "19 Natalia Przybysz 50 \n", - "20 Zwidy 14 \n", - "21 Krzysztof Daukszewicz 22 \n", - "22 RAGEHAMMER 9 \n", - "23 Millenium 22 \n", - "24 Bober 44 \n", - "25 Josef Hofmann 15 \n", - "26 Sonar 30 \n", - "27 Over the Voids... 16 \n", - "28 Thaw 5 \n", - "29 Andrzej Trzaskowski 1 \n", - "30 Boleslaw Szabelski 0 \n", - "31 Acid Drinkers 37 \n", - "32 Mariusz Lubomski 15 \n", - "33 Honorata Skarbek 35 \n", - "34 Cassel 11 \n", - "35 Baasch 36 \n", - "36 Mirt 4 \n", - "37 Magnolia Acoustic Quartet 0 \n", - "38 Blaze of Perdition 20 \n", - "39 Krzikopa 8 \n", - "40 Bonus RPK 51 \n", - "41 Agressiva 69 8 \n", - "42 Andre$ 10 \n", - "43 Raoul Koczalski 19 \n", - "44 SOSO 31 \n", - "45 Bezimienni 7 \n", - "46 Pawel Kaczmarczyk 7 \n", - "47 Muchy 25 \n", - "48 Iowa Super Soccer 1 \n", - "49 SB Maffija 61 \n", - "50 Marek Napiórkowski 18 \n", - "51 LUNA 33 \n", - "52 Tomek Sowinski and the Collective Imp... 0 \n", - "53 Jano Polska Wersja 45 \n", - "54 Matowy 0 \n", - "55 Agnieszka Chylinska 47 \n", - "56 Wojciech Świtała 7 \n", - "57 Obara International 0 \n", - "58 Nmls 0 \n", - "59 Luxtorpeda 39 \n", - "60 Xantotol 4 \n", - "61 Dianoya 0 \n", - "62 Deriglasoff 18 \n", - "63 This Cold 0 \n", - "64 Deys 53 \n", - "65 Komeda Quintet 11 \n", - "66 1984 4 \n", - "67 Adam Makowicz 8 \n", - "68 TSA 31 \n", - "69 Albo Inaczej 45 \n", - "70 Bartek Wrona 5 \n", - "71 Ofelia 36 \n", - "72 Jerzy Milian 17 \n", - "73 CamaSutra 35 \n", - "74 Beata Kozidrak 46 \n", - "75 Felicjan Andrzejczak 41 \n", - "76 Malibu 26 \n", - "77 Tabu 32 \n", - "78 Schizma 0 \n", - "79 Paweł Domagała 50 \n", - "80 Wojciech Majewski 1 \n", - "81 We Call It a Sound 0 \n", - "82 Materac 1 \n", - "83 Nosowska 49 \n", - "84 Leopold Godowsky 29 \n", - "85 Lilly Hates Roses 29 \n", - "86 Daniel Stetting 0 \n", - "87 Beyond the Event Horizon 4 \n", - "88 Wudec 1 \n", - "89 Power Play 42 \n", - "90 JonyPapa 19 \n", - "91 Christ Agony 13 \n", - "92 Ovvoid 0 \n", - "93 Patrycja Markowska 40 \n", - "94 Marcin Rozynek 29 \n", - "95 esceh 47 \n", - "96 Mooslip 0 \n", - "97 Damian Malec 0 \n", - "98 Nocna Zmiana Bluesa 12 \n", - "99 Newest Zealand 0 \n", - "100 Bedoes 73 \n", + "2 Mig 47 \n", + "3 Radio Bagdad 9 \n", + "4 Evorevo 9 \n", + "5 Polpo Motel 1 \n", + "6 Chada 55 \n", + "7 Natalia Przybysz 50 \n", + "8 Krzysztof Daukszewicz 22 \n", + "9 Thaw 5 \n", + "10 Mariusz Lubomski 15 \n", + "11 Honorata Skarbek 35 \n", + "12 Cassel 11 \n", + "13 Bonus RPK 51 \n", + "14 Obara International 0 \n", + "15 Nmls 0 \n", + "16 Deys 53 \n", + "17 1984 4 \n", + "18 TSA 31 \n", + "19 Ofelia 36 \n", + "20 Malibu 26 \n", + "21 Paweł Domagała 50 \n", + "22 We Call It a Sound 0 \n", + "23 Daniel Stetting 0 \n", + "24 Beyond the Event Horizon 4 \n", + "25 Wudec 1 \n", + "26 JonyPapa 19 \n", + "27 Mooslip 0 \n", + "28 Damian Malec 0 \n", + "29 Nocna Zmiana Bluesa 12 \n", + "30 Megustar 24 \n", + "31 Pectus 36 \n", + "32 Witold Małcużyński 8 \n", + "33 Dee Facto 9 \n", + "34 Piersi 36 \n", + "35 Gardenia 6 \n", + "36 Grizzlee 43 \n", + "37 HOMOMILITIA 17 \n", + "38 Better Person 32 \n", + "39 Setus 2 \n", + "40 Leh 37 \n", + "41 Mariusz Kalaga 31 \n", + "42 Oxford Drama 40 \n", + "43 Kolaboranci 6 \n", + "44 Camasutra 30 \n", + "45 Oddział Zamknięty 20 \n", + "46 Diabolicon 0 \n", + "47 Joachim Mencel 6 \n", + "48 Partia 18 \n", + "49 ehh hahah 4 \n", + "50 Hans Solo 2 \n", + "51 Kubi Producent 65 \n", + "52 Mazzmelancolié 0 \n", + "53 Sokół i Marysia Starosta 0 \n", + "54 Sorry Boys 43 \n", + "55 Jarun 3 \n", + "56 Jachna Tarwid Karch 0 \n", + "57 Obywatel G.C 42 \n", + "58 El Banda 11 \n", + "59 New York Crasnals 0 \n", + "60 Mateusz Ziółko 40 \n", + "61 Michał Tokaj Trio 0 \n", + "62 Toledo 27 \n", + "63 Normal Bias 8 \n", + "64 Żółte Kalendarze 9 \n", + "65 Two Boys 16 \n", + "66 Śląskie Szwagry 9 \n", + "67 Felivers 40 \n", + "68 Beteo 64 \n", + "69 Sarsa 50 \n", + "70 Władysław Szpilman 29 \n", + "71 Republika 45 \n", + "72 Shellerini 49 \n", + "73 Skowyt 23 \n", + "74 Piotr Kurek 6 \n", + "75 PodobaMiSię 6 \n", + "76 Eltron John 1 \n", + "77 P.T.P 2 \n", + "78 Bogdan Hołownia - Wojciech Pulcyn 3 \n", + "79 Stanisława Celińska 30 \n", + "80 Inri 0 \n", + "81 Sarmacja 5 \n", + "82 The Bill 36 \n", + "83 Cssaba 2 \n", + "84 Eldo 1 \n", + "85 Jazzombie 19 \n", + "86 Grabek 27 \n", + "87 Grzegorz Fitelberg 1 \n", + "88 JedenSiedem 6 \n", + "89 Marcin Leopolita 4 \n", + "90 Ziemia Kanaan 0 \n", + "91 Rompey 23 \n", + "92 Owls Are Not 0 \n", + "93 Wiatr 57 \n", + "94 Cheap Tobacco 17 \n", + "95 Leszek Kułakowski 2 \n", + "96 Chór i zespół instrumentalny duszpast... 13 \n", + "97 After Party 45 \n", + "98 Favst 58 \n", + "99 Bester Quartet 8 \n", + "100 Elzbieta Adamiak 17 \n", "Rows: 1-100 | Columns: 5" ] }, - "execution_count": 7, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -1310,7 +1323,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "318706f7", "metadata": {}, "outputs": [ @@ -1319,18 +1332,75 @@ "text/html": [ "