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Please add alt text to your posts

Please add alt text (alternative text) to all of your posted graphics for #TidyTuesday.

Twitter provides guidelines for how to add alt text to your images.

The DataViz Society/Nightingale by way of Amy Cesal has an article on writing good alt text for plots/graphs.

Here’s a simple formula for writing alt text for data visualization:

Chart type

It’s helpful for people with partial sight to know what chart type it is and gives context for understanding the rest of the visual. Example: Line graph

Type of data

What data is included in the chart? The x and y axis labels may help you figure this out. Example: number of bananas sold per day in the last year

Reason for including the chart

Think about why you’re including this visual. What does it show that’s meaningful. There should be a point to every visual and you should tell people what to look for. Example: the winter months have more banana sales

Link to data or source

Don’t include this in your alt text, but it should be included somewhere in the surrounding text. People should be able to click on a link to view the source data or dig further into the visual. This provides transparency about your source and lets people explore the data. Example: Data from the USDA

Penn State has an article on writing alt text descriptions for charts and tables.

Charts, graphs and maps use visuals to convey complex images to users. But since they are images, these media provide serious accessibility issues to colorblind users and users of screen readers. See the examples on this page for details on how to make charts more accessible.

The {rtweet} package includes the ability to post tweets with alt text programatically.

Need a reminder? There are extensions that force you to remember to add Alt Text to Tweets with media.

Spice Up Your Life! Spice girls ensemble. It is the 5 spice girls against a blue circle background

The data in this repo comes from Spotify and Genius. Thank you to the authors of the spotifyr and geniusr packages for making it easy to access data from these platforms!

There are 3 data sets about or related to the Spice Girls:

  • studio_album_tracks: Audio features of each song from the three studio albums by the Spice Girls. From Spotify.
  • related artists: Artists deemed to be similar to the Spice Girls, with info about each artist including their musical genres and follower numbers. Includes a row with details for the Spice Girls, for comparison purposes. From Spotify.
  • lyrics: Lyrics of each song from the three studio albums by the Spice Girls. From Genius.

Credit: Jacquie Tran

Data dictionaries

A data dictionary for each data set is provided here.

Example use

The R code below uses the studio_album_tracks data set to produce summary statistics for selected audio features.


# Load libraries
library(dplyr)

# Read data into R
studio_album_tracks <- readr::read_csv("https://github.com/jacquietran/spice_girls_data/raw/main/data/studio_album_tracks.csv")

# For each album, calculate mean values for danceability, energy, and valence
studio_album_tracks %>%
  group_by(album_name) %>%
  summarise(
    danceability_mean = mean(danceability),
    energy_mean = mean(energy),
    valence_mean = mean(valence)) %>%
  ungroup() %>%
  # Set factor levels of album_name
  mutate(
    album_name = factor(
      album_name, levels = c("Spice", "Spiceworld", "Forever"))) %>%
  arrange(album_name)

Useful packages

Get the data here

# Get the Data

# Read in with tidytuesdayR package 
# Install from CRAN via: install.packages("tidytuesdayR")
# This loads the readme and all the datasets for the week of interest

# Either ISO-8601 date or year/week works!

tuesdata <- tidytuesdayR::tt_load('2021-12-14')
tuesdata <- tidytuesdayR::tt_load(2021, week = 51)

studio_album_tracks <- tuesdata$studio_album_tracks

# Or read in the data manually

studio_album_tracks <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-12-14/studio_album_tracks.csv')

Data Dictionary

lyrics.csv

variable class description
artist_name character Artist name
album_name character Album name
track_number double Track number
song_id double Song ID
song_name character Song Name
line_number double Line Number
section_name character Section name
line character Line
section_artist character Section artist

related_artists.csv

variable class description
artist_id character Artist ID
artist_name character Artist name
genres character Genres
popularity double Popularity
followers_total double Followers total

studio_album_tracks.csv

variable class description
artist_name character Artist name
artist_id character Artist ID
album_id character Album ID
album_release_date double Release date
album_release_year double Year
danceability double Danceability
energy double Energy
key double Key
loudness double Loudness
mode double Mode
speechiness double Speechiness
acousticness double Acousticness
instrumentalness double Instrumentalness
liveness double Liveness
valence double Valence
tempo double Tempo
track_id character Track ID
time_signature double Time signature
duration_ms double Duration in ms
track_name character track name
track_number double Track number
album_name character Album name
key_name character Key name
mode_name character Mode name
key_mode character Key mode

Cleaning Script

See: Jacquie Tran's repo