Values below 0.33 most likely represent music and other non-speech-like tracks.Ī confidence measure from 0.0 to 1.0 of whether the track is acoustic. Values between 0.33 and 0.66 describe tracks that may contain both music and speech, either in sections or layered, including such cases as rap music. Values above 0.66 describe tracks that are probably made entirely of spoken words. talk show, audio book, poetry), the closer to 1.0 the attribute value. The more exclusively speech-like the recording (e.g. Speechiness detects the presence of spoken words in a track. Major is represented by 1 and minor is 0. Mode indicates the modality (major or minor) of a track, the type of scale from which its melodic content is derived. Values typical range between -60 and 0 db. Loudness is the quality of a sound that is the primary psychological correlate of physical strength (amplitude). Loudness values are averaged across the entire track and are useful for comparing relative loudness of tracks. The overall loudness of a track in decibels (dB). Integers map to pitches using standard Pitch Class notation. Perceptual features contributing to this attribute include dynamic range, perceived loudness, timbre, onset rate, and general entropy. For example, death metal has high energy, while a Bach prelude scores low on the scale.
Typically, energetic tracks feel fast, loud, and noisy. A value of 0.0 is least danceable and 1.0 is most danceable.Įnergy is a measure from 0.0 to 1.0 and represents a perceptual measure of intensity and activity. Song Popularity (0-100) where higher is betterĭanceability describes how suitable a track is for dancing based on a combination of musical elements including tempo, rhythm stability, beat strength, and overall regularity. Tuesdata <- tidytuesdayR::tt_load(2020, week = 4)ĭata Dictionary spotify_songs.csv variable # Install via devtools::install_github("thebioengineer/tidytuesdayR") # Either ISO-8601 date or year/week works! # PLEASE NOTE TO USE 2020 DATA YOU NEED TO UPDATE tidytuesdayR from GitHub # Or read in with tidytuesdayR package ()
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