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danceability
float64 | energy
float64 | key
int64 | loudness
float64 | mode
int64 | speechiness
float64 | acousticness
float64 | instrumentalness
float64 | liveness
float64 | valence
float64 | tempo
float64 | duration_ms
int64 | time_signature
int64 | liked
int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0.803
| 0.624
| 7
| -6.764
| 0
| 0.0477
| 0.451
| 0.000734
| 0.1
| 0.628
| 95.968
| 304,524
| 4
| 0
|
0.762
| 0.703
| 10
| -7.951
| 0
| 0.306
| 0.206
| 0
| 0.0912
| 0.519
| 151.329
| 247,178
| 4
| 1
|
0.261
| 0.0149
| 1
| -27.528
| 1
| 0.0419
| 0.992
| 0.897
| 0.102
| 0.0382
| 75.296
| 286,987
| 4
| 0
|
0.722
| 0.736
| 3
| -6.994
| 0
| 0.0585
| 0.431
| 0.000001
| 0.123
| 0.582
| 89.86
| 208,920
| 4
| 1
|
0.787
| 0.572
| 1
| -7.516
| 1
| 0.222
| 0.145
| 0
| 0.0753
| 0.647
| 155.117
| 179,413
| 4
| 1
|
0.778
| 0.632
| 8
| -6.415
| 1
| 0.125
| 0.0404
| 0
| 0.0912
| 0.827
| 140.951
| 224,029
| 4
| 1
|
0.666
| 0.589
| 0
| -8.405
| 0
| 0.324
| 0.555
| 0
| 0.114
| 0.776
| 74.974
| 146,053
| 4
| 1
|
0.922
| 0.712
| 7
| -6.024
| 1
| 0.171
| 0.0779
| 0.00004
| 0.175
| 0.904
| 104.964
| 161,800
| 4
| 1
|
0.794
| 0.659
| 7
| -7.063
| 0
| 0.0498
| 0.143
| 0.00224
| 0.0944
| 0.308
| 112.019
| 247,460
| 4
| 0
|
0.853
| 0.668
| 3
| -6.995
| 1
| 0.447
| 0.263
| 0
| 0.104
| 0.745
| 157.995
| 165,363
| 4
| 1
|
0.297
| 0.993
| 9
| -7.173
| 1
| 0.118
| 0.000057
| 0.77
| 0.0766
| 0.178
| 127.693
| 182,427
| 4
| 0
|
0.816
| 0.433
| 1
| -9.19
| 1
| 0.241
| 0.00471
| 0
| 0.132
| 0.676
| 147.942
| 225,000
| 4
| 1
|
0.297
| 0.973
| 1
| -4.505
| 1
| 0.151
| 0.00146
| 0.918
| 0.139
| 0.234
| 102.757
| 170,520
| 4
| 0
|
0.564
| 0.743
| 6
| -5.782
| 1
| 0.22
| 0.584
| 0
| 0.101
| 0.191
| 168.849
| 185,667
| 4
| 1
|
0.64
| 0.957
| 8
| -2.336
| 1
| 0.0741
| 0.0431
| 0
| 0.0789
| 0.692
| 134.992
| 178,013
| 4
| 1
|
0.684
| 0.64
| 5
| -9.906
| 0
| 0.0309
| 0.221
| 0.0102
| 0.179
| 0.777
| 106.023
| 234,267
| 4
| 0
|
0.85
| 0.853
| 8
| -5.65
| 1
| 0.123
| 0.0155
| 0
| 0.105
| 0.734
| 142.03
| 136,901
| 4
| 1
|
0.745
| 0.456
| 8
| -9.482
| 1
| 0.0874
| 0.44
| 0
| 0.072
| 0.124
| 94.032
| 314,367
| 4
| 0
|
0.754
| 0.475
| 1
| -10.889
| 1
| 0.154
| 0.523
| 0
| 0.113
| 0.235
| 117.006
| 201,384
| 4
| 1
|
0.797
| 0.852
| 8
| -5.202
| 1
| 0.241
| 0.0555
| 0.000025
| 0.0536
| 0.48
| 136.035
| 102,353
| 4
| 1
|
0.798
| 0.835
| 9
| -3.832
| 1
| 0.202
| 0.165
| 0
| 0.112
| 0.609
| 150.04
| 139,240
| 4
| 1
|
0.438
| 0.0825
| 9
| -21.686
| 0
| 0.0695
| 0.983
| 0.0749
| 0.0461
| 0.37
| 106.275
| 270,000
| 5
| 0
|
0.802
| 0.549
| 5
| -8.6
| 0
| 0.0631
| 0.268
| 0.00496
| 0.0984
| 0.498
| 138.984
| 184,627
| 4
| 1
|
0.6
| 0.535
| 4
| -12.028
| 1
| 0.376
| 0.274
| 0
| 0.0984
| 0.205
| 180.036
| 176,000
| 3
| 1
|
0.729
| 0.533
| 9
| -10.104
| 0
| 0.444
| 0.747
| 0.000005
| 0.0848
| 0.422
| 155.999
| 225,953
| 4
| 0
|
0.867
| 0.457
| 1
| -7.908
| 1
| 0.237
| 0.0987
| 0
| 0.0967
| 0.193
| 101.052
| 210,733
| 4
| 1
|
0.65
| 0.545
| 4
| -7.712
| 0
| 0.0514
| 0.271
| 0.000007
| 0.102
| 0.113
| 76.503
| 240,924
| 4
| 1
|
0.809
| 0.574
| 5
| -8.546
| 0
| 0.385
| 0.4
| 0
| 0.105
| 0.756
| 151.974
| 185,493
| 4
| 1
|
0.749
| 0.839
| 6
| -4.847
| 1
| 0.297
| 0.0867
| 0
| 0.204
| 0.804
| 172.068
| 111,000
| 4
| 1
|
0.657
| 0.333
| 8
| -13.553
| 1
| 0.526
| 0.0608
| 0
| 0.157
| 0.313
| 148.168
| 98,615
| 4
| 1
|
0.689
| 0.68
| 7
| -6.551
| 0
| 0.0774
| 0.392
| 0.000001
| 0.107
| 0.567
| 75.445
| 168,574
| 4
| 1
|
0.668
| 0.459
| 6
| -12.072
| 0
| 0.118
| 0.0499
| 0.000001
| 0.408
| 0.525
| 159.021
| 186,415
| 4
| 1
|
0.291
| 0.98
| 1
| -5.138
| 1
| 0.153
| 0.00127
| 0.091
| 0.102
| 0.257
| 79.792
| 270,920
| 4
| 0
|
0.573
| 0.581
| 10
| -9.026
| 0
| 0.339
| 0.753
| 0.000001
| 0.13
| 0.351
| 76.506
| 169,347
| 4
| 1
|
0.608
| 0.471
| 0
| -8.664
| 1
| 0.0945
| 0.446
| 0.000004
| 0.369
| 0.682
| 70.702
| 165,800
| 3
| 0
|
0.307
| 0.0515
| 4
| -28.493
| 0
| 0.0324
| 0.708
| 0.631
| 0.42
| 0.154
| 128.056
| 125,533
| 4
| 0
|
0.784
| 0.7
| 7
| -7.649
| 0
| 0.108
| 0.491
| 0
| 0.108
| 0.769
| 82.028
| 190,067
| 4
| 0
|
0.448
| 0.97
| 1
| -4.197
| 1
| 0.105
| 0.000428
| 0.912
| 0.376
| 0.381
| 119.215
| 123,880
| 4
| 0
|
0.648
| 0.751
| 8
| -8.582
| 1
| 0.0806
| 0.0182
| 0.000401
| 0.0418
| 0.863
| 100.437
| 244,827
| 4
| 0
|
0.895
| 0.479
| 11
| -9.071
| 0
| 0.273
| 0.208
| 0
| 0.0902
| 0.719
| 146.049
| 134,554
| 4
| 1
|
0.358
| 0.977
| 8
| -8.179
| 0
| 0.0727
| 0.000082
| 0.924
| 0.103
| 0.449
| 137.681
| 194,160
| 4
| 0
|
0.742
| 0.423
| 1
| -9.795
| 0
| 0.108
| 0.832
| 0.00001
| 0.0644
| 0.712
| 75.026
| 194,000
| 4
| 1
|
0.603
| 0.886
| 5
| -3.777
| 0
| 0.0837
| 0.00045
| 0
| 0.26
| 0.395
| 126.025
| 229,933
| 4
| 1
|
0.839
| 0.629
| 3
| -5.663
| 0
| 0.147
| 0.241
| 0
| 0.108
| 0.724
| 94.008
| 207,772
| 4
| 1
|
0.184
| 0.974
| 8
| -6.237
| 0
| 0.106
| 0.000023
| 0.886
| 0.241
| 0.33
| 93.771
| 257,390
| 3
| 0
|
0.373
| 0.98
| 1
| -5.016
| 0
| 0.122
| 0.000319
| 0.906
| 0.105
| 0.34
| 97.346
| 211,947
| 4
| 0
|
0.826
| 0.76
| 11
| -6.382
| 0
| 0.117
| 0.392
| 0
| 0.132
| 0.813
| 99.974
| 216,285
| 4
| 0
|
0.924
| 0.748
| 2
| -3.645
| 1
| 0.188
| 0.174
| 0
| 0.207
| 0.381
| 121.063
| 209,667
| 4
| 1
|
0.267
| 0.0024
| 1
| -42.261
| 0
| 0.0531
| 0.995
| 0.897
| 0.0942
| 0.267
| 71.428
| 397,773
| 4
| 0
|
0.462
| 0.974
| 1
| -5.82
| 1
| 0.0816
| 0.000029
| 0.723
| 0.0751
| 0.399
| 107.877
| 186,576
| 3
| 0
|
0.616
| 0.534
| 10
| -10.264
| 0
| 0.483
| 0.639
| 0
| 0.0844
| 0.556
| 170.054
| 146,480
| 4
| 1
|
0.878
| 0.622
| 2
| -6.995
| 1
| 0.405
| 0.153
| 0
| 0.0917
| 0.638
| 84.991
| 163,765
| 4
| 1
|
0.581
| 0.85
| 5
| -3.45
| 0
| 0.0734
| 0.185
| 0.00046
| 0.149
| 0.357
| 152.018
| 178,809
| 4
| 1
|
0.656
| 0.381
| 0
| -8.757
| 0
| 0.0802
| 0.653
| 0
| 0.116
| 0.166
| 84.907
| 325,556
| 4
| 0
|
0.363
| 0.994
| 8
| -5.781
| 1
| 0.131
| 0.000037
| 0.582
| 0.207
| 0.139
| 108.017
| 247,564
| 4
| 0
|
0.568
| 0.788
| 2
| -7.654
| 1
| 0.069
| 0.191
| 0.000176
| 0.0774
| 0.328
| 139.959
| 219,077
| 4
| 1
|
0.809
| 0.653
| 0
| -7.178
| 0
| 0.306
| 0.335
| 0
| 0.11
| 0.639
| 139.981
| 199,093
| 4
| 1
|
0.757
| 0.451
| 2
| -11.121
| 1
| 0.292
| 0.0485
| 0.000002
| 0.337
| 0.506
| 150.035
| 167,062
| 4
| 1
|
0.364
| 0.00799
| 8
| -33.09
| 1
| 0.0395
| 0.978
| 0.894
| 0.109
| 0.0674
| 101.226
| 216,093
| 4
| 0
|
0.247
| 0.992
| 8
| -7.766
| 0
| 0.0772
| 0.000029
| 0.799
| 0.0808
| 0.318
| 142.891
| 237,093
| 4
| 0
|
0.598
| 0.673
| 2
| -10.431
| 1
| 0.0693
| 0.0422
| 0.000068
| 0.289
| 0.59
| 102.035
| 197,693
| 4
| 0
|
0.826
| 0.556
| 5
| -8.516
| 0
| 0.191
| 0.684
| 0
| 0.119
| 0.591
| 150.067
| 187,006
| 4
| 1
|
0.318
| 0.0633
| 6
| -23.869
| 1
| 0.0507
| 0.992
| 0.871
| 0.0831
| 0.0384
| 129.466
| 199,133
| 3
| 0
|
0.506
| 0.881
| 5
| -5.491
| 0
| 0.108
| 0.000163
| 0.00143
| 0.23
| 0.556
| 148.084
| 187,322
| 4
| 1
|
0.138
| 0.991
| 8
| -5.661
| 1
| 0.175
| 0.000015
| 0.831
| 0.337
| 0.0718
| 94.443
| 244,239
| 1
| 0
|
0.531
| 0.803
| 8
| -3.929
| 0
| 0.339
| 0.325
| 0
| 0.368
| 0.414
| 97.51
| 191,133
| 5
| 1
|
0.791
| 0.5
| 1
| -9.805
| 0
| 0.42
| 0.603
| 0
| 0.0993
| 0.492
| 130.027
| 170,582
| 4
| 1
|
0.68
| 0.877
| 5
| -10.241
| 0
| 0.0353
| 0.191
| 0.000656
| 0.349
| 0.922
| 108.674
| 185,107
| 4
| 0
|
0.752
| 0.468
| 0
| -9.966
| 1
| 0.333
| 0.805
| 0
| 0.136
| 0.716
| 82.795
| 179,253
| 4
| 1
|
0.797
| 0.654
| 8
| -7.373
| 1
| 0.245
| 0.633
| 0
| 0.106
| 0.64
| 145.121
| 172,520
| 4
| 1
|
0.774
| 0.853
| 1
| -6.933
| 1
| 0.246
| 0.0275
| 0
| 0.0876
| 0.619
| 123.041
| 106,000
| 4
| 1
|
0.851
| 0.686
| 11
| -8.143
| 1
| 0.222
| 0.597
| 0.000001
| 0.111
| 0.752
| 154.986
| 195,344
| 4
| 1
|
0.75
| 0.772
| 10
| -8.706
| 0
| 0.157
| 0.206
| 0
| 0.0748
| 0.561
| 139.98
| 224,496
| 4
| 1
|
0.843
| 0.656
| 1
| -11.184
| 1
| 0.0595
| 0.0466
| 0.0187
| 0.169
| 0.931
| 121.112
| 215,653
| 4
| 0
|
0.539
| 0.487
| 1
| -9.653
| 1
| 0.202
| 0.309
| 0
| 0.097
| 0.375
| 169.985
| 186,353
| 4
| 0
|
0.454
| 0.968
| 6
| -6.289
| 1
| 0.0787
| 0.000017
| 0.338
| 0.0472
| 0.535
| 103.965
| 250,262
| 4
| 0
|
0.446
| 0.977
| 10
| -5.036
| 0
| 0.0781
| 0.000535
| 0.472
| 0.105
| 0.339
| 172.059
| 284,400
| 4
| 0
|
0.827
| 0.804
| 9
| -5.846
| 1
| 0.128
| 0.455
| 0.000001
| 0.272
| 0.566
| 146.079
| 178,588
| 4
| 1
|
0.74
| 0.403
| 6
| -9.311
| 0
| 0.0635
| 0.509
| 0.0247
| 0.104
| 0.331
| 138.013
| 173,120
| 4
| 1
|
0.833
| 0.813
| 4
| -5.708
| 0
| 0.29
| 0.244
| 0
| 0.128
| 0.705
| 154.062
| 217,760
| 4
| 1
|
0.789
| 0.84
| 9
| -5.29
| 1
| 0.097
| 0.0309
| 0
| 0.0916
| 0.494
| 136.059
| 84,000
| 4
| 1
|
0.62
| 0.573
| 0
| -11.893
| 1
| 0.0423
| 0.271
| 0
| 0.0607
| 0.897
| 81.548
| 231,333
| 4
| 0
|
0.752
| 0.905
| 11
| -7.015
| 0
| 0.181
| 0.0931
| 0.000739
| 0.355
| 0.521
| 150.991
| 179,107
| 4
| 1
|
0.701
| 0.341
| 1
| -12.26
| 0
| 0.0418
| 0.499
| 0.903
| 0.359
| 0.163
| 105.513
| 151,507
| 3
| 0
|
0.83
| 0.707
| 2
| -5.777
| 1
| 0.277
| 0.167
| 0
| 0.0797
| 0.682
| 146.154
| 190,685
| 4
| 1
|
0.779
| 0.705
| 4
| -7.834
| 0
| 0.0827
| 0.277
| 0
| 0.0804
| 0.228
| 103.048
| 233,597
| 4
| 0
|
0.263
| 0.202
| 1
| -17.687
| 1
| 0.0408
| 0.984
| 0.905
| 0.089
| 0.12
| 71.462
| 545,747
| 4
| 0
|
0.338
| 0.988
| 8
| -7.29
| 0
| 0.0865
| 0.000084
| 0.833
| 0.0377
| 0.449
| 99.046
| 221,960
| 4
| 0
|
0.814
| 0.672
| 9
| -12.068
| 1
| 0.0619
| 0.0435
| 0
| 0.061
| 0.933
| 109.394
| 300,000
| 4
| 0
|
0.78
| 0.551
| 5
| -13.038
| 0
| 0.0625
| 0.0613
| 0.104
| 0.0331
| 0.969
| 126.009
| 491,933
| 4
| 0
|
0.567
| 0.797
| 1
| -3.071
| 0
| 0.2
| 0.392
| 0
| 0.116
| 0.654
| 110.882
| 218,732
| 3
| 1
|
0.651
| 0.811
| 10
| -13.87
| 1
| 0.0318
| 0.0648
| 0.0293
| 0.1
| 0.962
| 112.126
| 186,573
| 4
| 0
|
0.798
| 0.564
| 2
| -5.98
| 1
| 0.047
| 0.23
| 0.000018
| 0.183
| 0.394
| 108.004
| 254,218
| 4
| 0
|
0.798
| 0.746
| 10
| -8.639
| 1
| 0.0313
| 0.0304
| 0.361
| 0.0703
| 0.965
| 128.553
| 655,213
| 4
| 0
|
0.908
| 0.61
| 9
| -5.735
| 1
| 0.271
| 0.213
| 0.000034
| 0.241
| 0.443
| 140.006
| 197,613
| 4
| 1
|
0.783
| 0.836
| 0
| -9.223
| 0
| 0.0486
| 0.396
| 0.0236
| 0.135
| 0.831
| 108.966
| 222,667
| 4
| 0
|
0.83
| 0.612
| 10
| -7.446
| 0
| 0.079
| 0.112
| 0
| 0.0892
| 0.252
| 97.989
| 243,956
| 4
| 1
|
0.832
| 0.553
| 7
| -13.705
| 1
| 0.0487
| 0.0422
| 0.00356
| 0.249
| 0.89
| 119.825
| 215,693
| 4
| 0
|
0.764
| 0.812
| 7
| -4.946
| 1
| 0.179
| 0.202
| 0
| 0.126
| 0.742
| 139.961
| 194,973
| 4
| 1
|
0.901
| 0.939
| 6
| -2.762
| 1
| 0.274
| 0.117
| 0
| 0.0643
| 0.805
| 142.948
| 356,347
| 4
| 1
|
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🎵 Music Feature Dataset Analysis
Welcome to the Exploratory Data Analysis (EDA) of a music feature dataset. This project aims to uncover insights into how audio features of songs influence user preferences, using the liked column as the target variable.
📁 Dataset Overview: train.csv
This dataset contains various musical/audio features for tracks, along with a liked score representing user preference.
🎼 Features Description
| Feature | Description |
|---|---|
danceability |
Suitability of a track for dancing. |
energy |
Intensity and activity level of the track. |
key |
Musical key as an integer (0 to 11). |
loudness |
Overall loudness in decibels (dB). |
mode |
Tonality: major (1) or minor (0). |
speechiness |
Presence of spoken words in the track. |
acousticness |
Likelihood the track is acoustic. |
instrumentalness |
Predicts whether a track contains no vocals. |
liveness |
Presence of an audience in the recording. |
valence |
Positiveness conveyed by the music. |
tempo |
Tempo in beats per minute (BPM). |
duration_ms |
Duration of the track in milliseconds. |
time_signature |
Estimated time signature (usually 3, 4, or 5). |
liked |
User preference score (continuous numerical value). |
🧼 Data Preprocessing
- ✅ Handled missing values
- ✅ Removed duplicates
- ✅ Normalized numeric features using Z-score normalization
- ✅ Detected outliers using box plots
- ✅ Computed summary statistics (mean, std, etc.)
📊 Visual Analysis
Visualizations included in the analysis:
| Visualization | Description |
|---|---|
 |
Heatmap of missing values |
 |
Count of unique and duplicate rows |
 |
Normalized feature distributions |
 |
Most and least liked tracks |
 |
Histograms of key features |
 |
Focused view on danceability distribution |
 |
Feature-wise mean and standard deviation |
 |
Feature correlation with liked |
 |
Outlier detection via box plots |
📈 Key Findings
- 🔹 Features like
energy,valence, anddanceabilityhave positive correlation with thelikedscore. - 🔹 Features like
keyandmodeshow low or no correlation with user preference. - 🔹 Most features are approximately normally distributed.
- 🔹 Tracks that are highly energetic, positive, and danceable are generally more liked.
🛠️ Tools & Libraries Used
- Language: Python 🐍
- Libraries:
pandas,numpyfor data handlingmatplotlib,seabornfor visualizationsscikit-learnfor preprocessing
📌 Conclusion
This analysis helps identify which audio features most impact user preferences. These insights can guide the development of:
- 🎧 Music recommendation systems
- 📊 User behavior models
- 🤖 Feature engineering in ML projects
👤 Author
Sujal Thakkar
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