Visualiser des indices

Cette semaine, le #Tidytuesday nous fournit une base de données de Spotify.

CONTEXTE

Les données de cette semaine proviennent de spotifyr et un article sur le sujet peut être trouvé ici

OBJECTIFS

Visualiser les indicateurs d’énergie et de dansabilité de tempo et de bonheur pour chaque genre sur un même axe.

IMPORTER

spotify_songs <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-01-21/spotify_songs.csv')

FALSE Parsed with column specification:  
FALSE cols(  
FALSE   .default = col_double(),  
FALSE   track_id = col_character(),  
FALSE   track_name = col_character(),  
FALSE   track_artist = col_character(),  
FALSE   track_album_id = col_character(),  
FALSE   track_album_name = col_character(),  
FALSE   track_album_release_date = col_character(),  
FALSE   playlist_name = col_character(),  
FALSE   playlist_id = col_character(),  
FALSE   playlist_genre = col_character(),  
FALSE   playlist_subgenre = col_character()  
FALSE )

FALSE See spec(...) for full column specifications.

EXPLORER

summary(spotify_songs)

##    track_id          track_name        track_artist       track_popularity  
##  Length:32833       Length:32833       Length:32833       Min.   :  0.00    
##  Class :character   Class :character   Class :character   1st Qu.: 24.00    
##  Mode  :character   Mode  :character   Mode  :character   Median : 45.00    
##                                                           Mean   : 42.48    
##                                                           3rd Qu.: 62.00    
##                                                           Max.   :100.00    
##  track_album_id     track_album_name   track_album_release_date  
##  Length:32833       Length:32833       Length:32833              
##  Class :character   Class :character   Class :character          
##  Mode  :character   Mode  :character   Mode  :character          
##                                                                  
##                                                                  
##                                                                  
##  playlist_name      playlist_id        playlist_genre      
##  Length:32833       Length:32833       Length:32833        
##  Class :character   Class :character   Class :character    
##  Mode  :character   Mode  :character   Mode  :character    
##                                                            
##                                                            
##                                                            
##  playlist_subgenre   danceability        energy              key          
##  Length:32833       Min.   :0.0000   Min.   :0.000175   Min.   : 0.000    
##  Class :character   1st Qu.:0.5630   1st Qu.:0.581000   1st Qu.: 2.000    
##  Mode  :character   Median :0.6720   Median :0.721000   Median : 6.000    
##                     Mean   :0.6548   Mean   :0.698619   Mean   : 5.374    
##                     3rd Qu.:0.7610   3rd Qu.:0.840000   3rd Qu.: 9.000    
##                     Max.   :0.9830   Max.   :1.000000   Max.   :11.000    
##     loudness            mode         speechiness      acousticness     
##  Min.   :-46.448   Min.   :0.0000   Min.   :0.0000   Min.   :0.0000    
##  1st Qu.: -8.171   1st Qu.:0.0000   1st Qu.:0.0410   1st Qu.:0.0151    
##  Median : -6.166   Median :1.0000   Median :0.0625   Median :0.0804    
##  Mean   : -6.720   Mean   :0.5657   Mean   :0.1071   Mean   :0.1753    
##  3rd Qu.: -4.645   3rd Qu.:1.0000   3rd Qu.:0.1320   3rd Qu.:0.2550    
##  Max.   :  1.275   Max.   :1.0000   Max.   :0.9180   Max.   :0.9940    
##  instrumentalness       liveness         valence           tempo         
##  Min.   :0.0000000   Min.   :0.0000   Min.   :0.0000   Min.   :  0.00    
##  1st Qu.:0.0000000   1st Qu.:0.0927   1st Qu.:0.3310   1st Qu.: 99.96    
##  Median :0.0000161   Median :0.1270   Median :0.5120   Median :121.98    
##  Mean   :0.0847472   Mean   :0.1902   Mean   :0.5106   Mean   :120.88    
##  3rd Qu.:0.0048300   3rd Qu.:0.2480   3rd Qu.:0.6930   3rd Qu.:133.92    
##  Max.   :0.9940000   Max.   :0.9960   Max.   :0.9910   Max.   :239.44    
##   duration_ms      
##  Min.   :  4000    
##  1st Qu.:187819    
##  Median :216000    
##  Mean   :225800    
##  3rd Qu.:253585    
##  Max.   :517810

glimpse(spotify_songs)

## Observations: 32,833  
## Variables: 23  
## $ track_id                 <chr> "6f807x0ima9a1j3VPbc7VN", "0r7CVbZTWZgb…  
## $ track_name               <chr> "I Don't Care (with Justin Bieber) - Lo…  
## $ track_artist             <chr> "Ed Sheeran", "Maroon 5", "Zara Larsson…  
## $ track_popularity         <dbl> 66, 67, 70, 60, 69, 67, 62, 69, 68, 67,…  
## $ track_album_id           <chr> "2oCs0DGTsRO98Gh5ZSl2Cx", "63rPSO264uRj…  
## $ track_album_name         <chr> "I Don't Care (with Justin Bieber) [Lou…  
## $ track_album_release_date <chr> "2019-06-14", "2019-12-13", "2019-07-05…  
## $ playlist_name            <chr> "Pop Remix", "Pop Remix", "Pop Remix", …  
## $ playlist_id              <chr> "37i9dQZF1DXcZDD7cfEKhW", "37i9dQZF1DXc…  
## $ playlist_genre           <chr> "pop", "pop", "pop", "pop", "pop", "pop…  
## $ playlist_subgenre        <chr> "dance pop", "dance pop", "dance pop", …  
## $ danceability             <dbl> 0.748, 0.726, 0.675, 0.718, 0.650, 0.67…  
## $ energy                   <dbl> 0.916, 0.815, 0.931, 0.930, 0.833, 0.91…  
## $ key                      <dbl> 6, 11, 1, 7, 1, 8, 5, 4, 8, 2, 6, 8, 1,…  
## $ loudness                 <dbl> -2.634, -4.969, -3.432, -3.778, -4.672,…  
## $ mode                     <dbl> 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, …  
## $ speechiness              <dbl> 0.0583, 0.0373, 0.0742, 0.1020, 0.0359,…  
## $ acousticness             <dbl> 0.10200, 0.07240, 0.07940, 0.02870, 0.0…  
## $ instrumentalness         <dbl> 0.00e+00, 4.21e-03, 2.33e-05, 9.43e-06,…  
## $ liveness                 <dbl> 0.0653, 0.3570, 0.1100, 0.2040, 0.0833,…  
## $ valence                  <dbl> 0.518, 0.693, 0.613, 0.277, 0.725, 0.58…  
## $ tempo                    <dbl> 122.036, 99.972, 124.008, 121.956, 123.…  
## $ duration_ms              <dbl> 194754, 162600, 176616, 169093, 189052,…

PRÉPARER

# convertir le tempo en un indicateur qui varie entre 0 et 1  
tempo<-data.frame(tempo=c(0,99.96,120.88,133.92,239.44),tempo_0_1=c(0,0.25,0.50,0.75,1))  

formula <- y ~ x  
gg<- ggplot(data=tempo, aes(x=tempo, y=tempo_0_1))  
gg<- gg + geom_point()  
gg<- gg + geom_smooth(method='lm', se=FALSE, formula=formula)  
gg<- gg +  stat_poly_eq(aes(label =  paste(..eq.label.., ..adj.rr.label.., sep = "~~~~")),
                     formula = formula, parse = TRUE)  
gg<- gg + theme_classic()  
gg<- gg + scale_y_continuous(limits=c(0,1))  
gg

data<-spotify_songs %>%
     select(playlist_genre, danceability, energy,valence,tempo) %>%
     mutate(tempo_0_1=0.00438*tempo-0.0208) %>%
     select(-tempo) %>%
     gather(type, valeur,-playlist_genre) %>%
     group_by(playlist_genre, type) %>%
     summarise_if(is.numeric, median, na.rm = TRUE) %>%
    ungroup()

VISUALISER

#Graphique  
gg<- ggplot(data=data,aes(x = valeur, y=playlist_genre))  
gg <- gg + geom_segment( aes(x=0.3, xend=0.9,y=playlist_genre, yend=playlist_genre),
                             color="#838A90", alpha=0.6, size=4)  
gg <- gg + geom_segment( aes(x=0.3, xend=0.9,y=playlist_genre, yend=playlist_genre),
                             color="#ffffff", alpha=1, size=0.5
)  
gg <- gg +  geom_point(aes(fill=type, group=playlist_genre), color="#FFFFFF", size=20, pch=21, alpha=0.5)  
gg <- gg +  geom_point(aes(fill=type, group=playlist_genre), color="#FFFFFF", size=12, pch=21)  
gg <- gg + scale_fill_brewer(palette = "Set1",labels=c("Dansabilité","Énergie", "Tempo", "Bonheur"))  
#ajouter les étiquettes de points  
gg<-gg + geom_text(data=data, aes(x=valeur, y=playlist_genre, label=(round(data$valeur,1)), group=NULL), color="#ffffff", size=4.5, vjust=0.5, hjust=0.5, fontface="bold")  
#pour l'axe des y à l'intérieur du graphique  
gg<-gg + annotate(geom="text",x=0.3, y=1.3, label="Edm", color="#ffffff", size=5.5, vjust=0.5, hjust=0, fontface="bold")  
gg<-gg + annotate(geom="text",x=0.3, y=2.3, label="Latin", color="#ffffff", size=5.5, vjust=0.5, hjust=0, fontface="bold") 
 gg<-gg + annotate(geom="text",x=0.3, y=3.3, label="Pop", color="#ffffff", size=5.5, vjust=0.5, hjust=0, fontface="bold")  
gg<-gg + annotate(geom="text",x=0.3, y=4.3, label="R&B", color="#ffffff", size=5.5, vjust=0.5, hjust=0, fontface="bold")  
gg<-gg + annotate(geom="text",x=0.3, y=5.3, label="Rap", color="#ffffff", size=5.5, vjust=0.5, hjust=0, fontface="bold")  
gg<-gg + annotate(geom="text",x=0.3, y=6.3, label="Rock", color="#ffffff", size=5.5, vjust=0.5, hjust=0, fontface="bold")  
#ajuster l'axe des x 
gg <- gg + scale_x_continuous(expand = c(0,0))  
#modifier le thème  
gg <- gg +  theme(plot.background = element_rect(fill = "#171717"),
                    panel.background = element_rect(fill = "#171717"),
                    panel.grid.major.y= element_blank(),
                    panel.grid.major.x= element_blank(),
                    panel.grid.minor = element_blank(),
                    axis.line.x = element_blank(),
                    axis.line.y =element_blank(),
                    axis.ticks.x = element_blank(),
                     axis.ticks.y = element_blank())  
gg <- gg +  theme(legend.position="top",
                     legend.title = element_blank(),
                     legend.background = element_blank(),
                     legend.key=element_blank(),
                     legend.spacing.x = unit(0.2, 'cm'),
                     legend.text= element_text(hjust =0.5,size= 8, colour = "#FFFFFF"))  
gg <- gg +    guides(fill = guide_legend(nrow = 1, reverse = TRUE))    
#ajouter les titres  
gg<-gg + labs(title="Quelle genre de musique préfères-tu?",
              subtitle = "\nSpotify classe les différents genre de musique en fonction de leurs caractéristiques pour aider\nles utilisateurs à faire leur choix.\n",
                x="Indice",
                y=" ", 
                caption="\nSOURCE: Spotifyr   |  DESIGN: Johanie Fournier, agr.")  
gg<-gg + theme(  plot.title    =  element_text(size=30, hjust=0,vjust=0.5, color="#FFFFFF", family="Tw Cen MT", face="bold"),
                   plot.subtitle = element_text(size=15, hjust=0,vjust=0.5, color="#FFFFFF", family="Tw Cen MT"),
                   plot.caption  = element_text(size=10, hjust=1,vjust=0.5, color="#FFFFFF", family="Tw Cen MT"),
                   axis.title.x  = element_text(size=
15, hjust=0.05,vjust=0.5, color="#FFFFFF", family="Tw Cen MT", angle =0),
                   axis.title.y  = element_blank(),
                   axis.text.y   = element_blank(),
                    axis.text.x   = element_blank())

Voici ce que ça donne:

Alors, tu veux en savoir plus sur ma démarche? Abonne-toi à mon infolettre pour savoir quand est-ce que le prochain épisode de podcast sera disponible. J’y expliquerai toute la réflexion et les concepts de data visualisation qui ont menés à la création de cette viz.

Johanie Fournier, agr.

Agriculture, données, visualisation

Visualiser des indices

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