| editor_options | ||||
|---|---|---|---|---|
|
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.
The data this week comes from Eurocontrol. A brief article covers this data at ec.europa.eu. Hattip to Data is Plural.
# 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('2022-07-12')
tuesdata <- tidytuesdayR::tt_load(2022, week = 28)
flights <- tuesdata$flights
# Or read in the data manually
flights <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-07-12/flights.csv')
| Column name | Data Source | Label | Description | Example |
|---|---|---|---|---|
| YEAR | Network Manager | YEAR | Reference year | 2014 |
| MONTH_NUM | Network Manager | MONTH | Month (numeric) | 1 |
| MONTH_MON | Network Manager | MONTH_MON | Month (3-letter code) | JAN |
| FLT_DATE | Network Manager | DATE_FLT | Date of flight | 01-Jan-2014 |
| APT_ICAO | Network Manager | APT_ICAO | ICAO 4-letter airport designator | EDDM |
| APT_NAME | PRU | APT_NAME | Airport name | Munich |
| STATE_NAME | PRU | STATE_NAME | Name of the country in which the airport is located | Germany |
| FLT_DEP_1 | Network Manager | Departures - (NM) | Number of IFR departures | 278 |
| FLT_ARR_1 | Network Manager | IFR arrivals - (NM) | Number of IFR arrivals | 241 |
| FLT_TOT_1 | Network Manager | IFR flights (arr + dep) - (NM) | Number total IFR movements | 519 |
| FLT_DEP_IFR_2 | Airport Operator | IFR departures - (APT) | Number of IFR departures | 278 |
| FLT_ARR_IFR_2 | Airport Operator | IFR arrivals - (APT) | Number of IFR arrivals | 241 |
| FLT_TOT_IFR_2 | Airport Operator | IFR flights (arr + dep) - (APT) | Number total IFR movements | 519 |