Data
Music-Dataset--1950-to-2019

Music-Dataset--1950-to-2019

active ARFF Attribution 4.0 International (CC BY 4.0) Visibility: public Uploaded 24-03-2022 by Elif Ceren Gok
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Context This dataset provides a list of lyrics from 1950 to 2019 describing music metadata as sadness, danceability, loudness, acousticness, etc. Authors also provide some information as lyrics which can be used to natural language processing. Acknowledgements Moura, Luan; Fontelles, Emanuel; Sampaio, Vinicius; Frana, Mardnio (2020), Music Dataset: Lyrics and Metadata from 1950 to 2019, Mendeley Data, V3, doi: 10.17632/3t9vbwxgr5.3

31 features

Unnamed:_0numeric28372 unique values
0 missing
artist_namestring5423 unique values
4 missing
track_namestring23677 unique values
9 missing
release_datenumeric70 unique values
0 missing
genrestring7 unique values
0 missing
lyricsstring28372 unique values
0 missing
lennumeric199 unique values
0 missing
datingnumeric27918 unique values
0 missing
violencenumeric28189 unique values
0 missing
world/lifenumeric28195 unique values
0 missing
night/timenumeric28169 unique values
0 missing
shake_the_audiencenumeric27161 unique values
0 missing
family/gospelnumeric28050 unique values
0 missing
romanticnumeric27892 unique values
0 missing
communicationnumeric28192 unique values
0 missing
obscenenumeric28203 unique values
0 missing
musicnumeric28177 unique values
0 missing
movement/placesnumeric28200 unique values
0 missing
light/visual_perceptionsnumeric28182 unique values
0 missing
family/spiritualnumeric27932 unique values
0 missing
like/girlsnumeric28094 unique values
0 missing
sadnessnumeric28191 unique values
0 missing
feelingsnumeric27707 unique values
0 missing
danceabilitynumeric859 unique values
0 missing
loudnessnumeric13066 unique values
0 missing
acousticnessnumeric3786 unique values
0 missing
instrumentalnessnumeric4939 unique values
0 missing
valencenumeric1295 unique values
0 missing
energynumeric1348 unique values
0 missing
topicstring8 unique values
0 missing
agenumeric70 unique values
0 missing
Show all 31 features

19 properties

NumberOfInstances
28372
Number of instances (rows) of the dataset.
NumberOfFeatures
31
Number of attributes (columns) of the dataset.
NumberOfClasses
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
13
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
9
Number of instances with at least one value missing.
NumberOfNumericFeatures
26
Number of numeric attributes.
NumberOfSymbolicFeatures
0
Number of nominal attributes.
Dimensionality
0
Number of attributes divided by the number of instances.
PercentageOfNumericFeatures
83.87
Percentage of numeric attributes.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
PercentageOfSymbolicFeatures
0
Percentage of nominal attributes.
MajorityClassSize
Number of instances belonging to the most frequent class.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MinorityClassSize
Number of instances belonging to the least frequent class.
NumberOfBinaryFeatures
0
Number of binary attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0.03
Percentage of instances having missing values.
AutoCorrelation
Average class difference between consecutive instances.
PercentageOfMissingValues
0
Percentage of missing values.
Show all 19 properties

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