This post is as much something to do on a rainy day as it is an exercise in data visualization. I found a dataset of over 6,000 songs on Spotify that were tagged according to their weather connection. Per the author, “The data set was obtained as a result of scraping studies on Spotify with the weather information coming from Open-Weather API.” At first I misinterpreted the set to mean that the lyrics of the songs mentioned said meteorological conditions but I soon determined that that was not the case. These are weather pairings akin to wine pairings: flavors, notes, moods. Nevertheless, this was a fun project that could become a mega playlist. (As an aside, a weather-themed playlist would be a fun “rainy day” project. Start with “I Love a Rainy Night” by Eddie Rabbitt. Add on some “Set Fire to the Rain” by Adele. Fold in some “Misty Mountain Hop” by Led Zeppelin. “It’s Raining Men” by the Pointer Sisters. “I’ve Seen Fire and I’ve Seen Rain” by James Taylor.)

The “forecast” below represents the percentage of the playlist for any of the sic categories. I combined “Mist,” “Fog” and “Drizzle” into one single category even through they were three separate ones on the data table. The songs on the graphic are my selections.

The distribution of the songs on this playlist is pretty moody, pretty atmospheric. This works for the stated purpose of this Spotify playlist: to enhance and/or complement scenes in movies or videos. This means that while there are some popular songs from artists like Taylor Swift, Bad Bunny and The Weeknd, there are many less popular artists and songs. If we were to make this a pop chart, that is sort by category and popularity rating, we get a different forecast: 52% clear, 12.5% clouds, 8% rain, 8% fog, 6% snow, 6% mist, 2% drizzle, 2% thunderstorms. Pop seems to make the sun peak through.

Future studies could look at the following: the combination of lyrics and weather tag, the connection between genre and weather tag, the related connection of language and weather tag.

WeatherTrack NameArtistPopularity
ClearLa Bebe – RemixYng Lvcas99
Clearun x100toGrupo Frontera99
ClearBoy’s a liar Pt. 2PinkPantheress96
ClearTQGKAROL G96
ClearBESOROSALÍA96
ClearCalm Down (with Selena Gomez)Rema95
ClearShakira: Bzrp Music Sessions, Vol. 53Bizarrap95
ClearI’m Good (Blue)David Guetta94
ClearI Ain’t WorriedOneRepublic93
ClearStarboyThe Weeknd93
ClearQuevedo: Bzrp Music Sessions, Vol. 52Bizarrap93
ClearDie For You – RemixThe Weeknd93
ClearPlayersCoi Leray92
ClearMe Porto BonitoBad Bunny92
ClearMiracle (with Ellie Goulding)Calvin Harris91
ClearCruel SummerTaylor Swift91
ClearEscapism.RAYE91
ClearSure ThingMiguel91
ClearEl MerengueMarshmello91
ClearWatermelon SugarHarry Styles90
ClearNonsenseSabrina Carpenter90
ClearLa BachataManuel Turizo90
ClearTiti­ Me PreguntóBad Bunny90
ClearLast NightMorgan Wallen90
ClearChemicalPost Malone90
CloudsAnti-HeroTaylor Swift94
CloudsKill BillSZA94
CloudsBlinding LightsThe Weeknd92
CloudsAngels Like YouMiley Cyrus91
CloudsDon’t Blame MeTaylor Swift90
CloudsAll Of The Girls You Loved BeforeTaylor Swift90
DrizzleDandelionsRuth B.90
FogAnother LoveTom Odell92
FogSweater WeatherThe Neighbourhood91
FogceilingsLizzy McAlpine91
FogYellowColdplay90
MistDaylightDavid Kushner96
MistCreepin’ (with The Weeknd & 21 Savage)Metro Boomin96
MistUntil I Found You (with Em Beihold) – Em Beihold VersionStephen Sanchez93
RainI Wanna Be YoursArctic Monkeys94
RainRomantic Homicided4vd91
Rainlovely (with Khalid)Billie Eilish90
RainPerfectEd Sheeran90
SnowCupid – Twin Ver.FIFTY FIFTY97
SnowSee You Again (feat. Kali Uchis)Tyler, The Creator94
SnowHere With Med4vd94
SnowSNAPRosa Linn90
ThunderstormUnholy (feat. Kim Petras)Sam Smith91

For more on ways to use Spotify songs and data in class, check out this post from the archives: “Seven Ways To Use Spotify In School.” For bonus words on “wind,” check out this offering from Merriam-Webster.