Tidy Tuesday

Tidy Tuesday Week 42/2023 - Taylor Swift

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tidytuesday
2023
week 42

This R code generates an eye-catching chart that explores audio metrics in Taylor Swift's albums. It uses various libraries, custom fonts, and symbols to create an aesthetically pleasing visualization. The chart showcases metrics like danceability, energy, and more, providing valuable insights in a visually appealing format.

The Code

# Load necessary libraries
library(tidyverse)            # For data manipulation and visualization

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.2     ✔ readr     2.1.4
## ✔ forcats   1.0.0     ✔ stringr   1.5.0
## ✔ ggplot2   3.4.3     ✔ tibble    3.2.1
## ✔ lubridate 1.9.2     ✔ tidyr     1.3.0
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(tidytuesdayR)        # For accessing TidyTuesday datasets
library(showtext)            # For working with fonts

## Lade nötiges Paket: sysfonts
## Lade nötiges Paket: showtextdb

library(glue)                # For text formatting
library(ggtext)              # For enhanced text formatting in ggplot2
library(tayloRswift)         # Additional package, for color palette

# Load Data
# Load TidyTuesday dataset for the specified year and week
tuesdata <- tidytuesdayR::tt_load(2023, week = 42)

## --- Compiling #TidyTuesday Information for 2023-10-17 ----
## --- There are 3 files available ---
## --- Starting Download ---

## 
## 	Downloading file 1 of 3: `taylor_album_songs.csv`
## 	Downloading file 2 of 3: `taylor_all_songs.csv`
## 	Downloading file 3 of 3: `taylor_albums.csv`

## --- Download complete ---

taylor_album_songs <- tuesdata$taylor_album_songs
taylor_all_songs <- tuesdata$taylor_all_songs
taylor_albums <- tuesdata$taylor_albums

# Load Fonts and Define Colors
# Load custom fonts and define color codes for use in visualizations
font_add_google("IM Fell DW Pica", "pica")
font_add('fa-reg', 'c:/Users/info/OneDrive/Dokumente/fonts/Font Awesome 6 Free-Regular-400.otf')
font_add('fa-brands', 'c:/Users/info/OneDrive/Dokumente/fonts/Font Awesome 6 Brands-Regular-400.otf')
font_add('fa-solid', 'c:/Users/info/OneDrive/Dokumente/fonts/Font Awesome 6 Free-Solid-900.otf')
font_add('ts', 'c:/Users/info/OneDrive/Dokumente/fonts/Satisfaction.ttf')
showtext_auto()
bg <- "white"
col1 <- "black"
col2 <- "#b8396b"
col3 <- "#ffd1d7"
col4 <- "#fff5cc"
col5 <- "#76bae0"
col6 <- "#b28f81"
col7 <- "#54483e"

# Define Symbols
# Define symbols using HTML-style code with specified colors and fonts
twitter <- glue("<span style='color:{col3};font-family:fa-brands;'>&#xf099;</span>")
mastodon <- glue("<span style='color:{col3};font-family:fa-brands;'>&#xf4f6;</span>")
link <- glue("<span style='color:{col3};font-family:fa-solid;'>&#xf0c1;</span>")
data <- glue("<span style='color:{col3};font-family:fa-solid;'>&#xf1c0;</span>")
quote <- glue("<span style='color:{col3};font-family:fa-solid;'>&#xf10d;</span>")
space <- glue("<span style='color:{bg}'>-</span>")
space2 <- glue("<span style='color:{bg}'>--</span>") # This creates horizontal lines for formatting.
taylor <- glue("<span style='color:{col1};font-family:ts;'>Taylor Swift</span>")
acousticness <- glue("<span style='color:{col2}'>Acousticness</span>")
danceability <- glue("<span style='color:{col3}'>Danceability</span>")
energy <- glue("<span style='color:{col4}'>Energy</span>")
instrumentalness <- glue("<span style='color:{col5}'>Instrumentalness</span>")
speechiness <- glue("<span style='color:{col6}'>Speechiness</span>")
valence <- glue("<span style='color:{col7}'>Valence</span>")

# Define Title
t <- glue("{taylor}'s Album Song Metrics")
s <- glue("Exploring {acousticness}, {danceability}, {energy}, {instrumentalness},<br>{speechiness}, and {valence} in Taylor Swift's Albums")
cap <- glue("{twitter}{space2}@web_design_fh{space2} 
	{space2}{mastodon}{space2}@frankhaenel @fosstodon.org{space2}
	{space2}{link}{space}{space2}www.frankhaenel.de<br>
	{data}{space2} taylor R package from W. Jake Thompson")

# Data Manipulation and Visualization
df <- taylor_album_songs %>%
     select(album_name,danceability,energy,speechiness,acousticness,instrumentalness,valence) %>%
     pivot_longer(
         cols = !album_name,
         names_to = "score",
         values_to = "value"
     ) %>%
     group_by(album_name,score) %>%
     summarise(mean = mean(value)) %>%
         na.omit()

## `summarise()` has grouped output by 'album_name'. You can override using the
## `.groups` argument.

df %>%
     ggplot(aes(x=score,y=mean,fill=score)) +
     geom_bar(stat="identity") +
     ylim(-0.2,0.8) +
     coord_polar(start = 0) +
     facet_wrap(~album_name,nrow(2)) +
         scale_fill_taylor(palette = "lover", guide = "none") +
         theme_minimal() +
         theme(
                strip.text = element_text(size = 8),
                plot.margin = margin(20, 20, 20, 20),
                axis.text = element_blank(),
                axis.title = element_blank(),
                panel.grid = element_blank(),
                plot.title = element_markdown(size = 26, hjust = 0.5, lineheight = 1.3, family = "pica", color = col1),
                plot.subtitle = element_markdown(size = 22, hjust = 0.5, lineheight = 1.3, family = "pica", color = col1),
                plot.caption = element_markdown(size = 12, hjust = 0.5, lineheight = 1.3, family = "pica", color = col2)
        ) +
        labs(title=t,subtitle=s,caption=cap)

An artistic polar bar chart comparing audio metrics in Taylor Swift's albums, featuring danceability, energy, and other attributes. The chart showcases a unique color palette and symbol-enhanced labels.

R Code Documentation

This R code is designed to generate a visualization using ggplot2 to explore and compare various audio metrics in Taylor Swift's albums. The code uses different libraries and custom fonts to create an aesthetic and informative chart.

Libraries Used

tidyverse: Used for data manipulation and visualization.
tidytuesdayR: Enables access to TidyTuesday datasets.
showtext: Facilitates working with fonts in plots.
glue: Used for text formatting.
ggtext: Enhances text formatting in ggplot2.
tayloRswift: (Custom library, if available) Provides additional functionality related to Taylor Swift data.

Load Data

The code loads data from the TidyTuesday dataset for the year 2023 and week 42. It fetches information about Taylor Swift's albums, album songs, and all songs from the dataset.

Load Fonts and Define Colors

Custom fonts are loaded to enhance text appearance, and specific color codes are defined for use in visualizations. These fonts and colors add a unique style to the chart.

Define Symbols

HTML-style code is used to define symbols with specified colors and fonts. These symbols are used in the chart to represent various elements and enhance visual appeal.

Define Title

The title and subtitle for the chart are defined using custom fonts and symbols. These elements contribute to the chart's aesthetics and provide context for the visualization.

Data Manipulation and Visualization

The code performs data manipulation to calculate the mean of specific audio metrics for each album. It then creates a polar bar chart using ggplot2 to visualize and compare these metrics. The chart is designed to be minimalistic and visually appealing.

Additional Information

The chart is accompanied by a caption that includes contact information and references to external resources, further enhancing its informativeness and usability.