Name	Name	Last commit message	Last commit date
parent directory ..
contribution_data_all_states.csv	contribution_data_all_states.csv
corp_by_politician.csv	corp_by_politician.csv
donors.csv	donors.csv
fortune_agg.csv	fortune_agg.csv
fortune_aggregates.csv	fortune_aggregates.csv
pic1.png	pic1.png
pic2.png	pic2.png
pride_aggregates.csv	pride_aggregates.csv
pride_sponsors.csv	pride_sponsors.csv
readme.md	readme.md
static_list.csv	static_list.csv

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.

Pride Donations

The data this week comes from Data For Progress.

Each year, hundreds of corporations around the country participate in Pride, an annual celebration of the LGBTQ+ community's history and progress. They present themselves as LGBTQ+ allies, but new research from Data for Progress finds that in between their yearly parade appearances, dozens of these corporations are giving to state politicians behind some of the most bigoted and harmful policies in over a decade.

Activists and allies wishing to hold these politicians accountable for bigotry can begin by holding their corporate backers accountable. In a new project series, Data for Progress has compiled a set of resources for activists, employees, community leaders, and lawmakers to push back on these policies and the prejudice powering them. We provide research tying the political giving of specific Fortune 500 companies to anti-LGBTQ+ politicians in six states, polling showing that such giving hurts the brands' favorability, and upcoming policy memos to understand the issue and to take action.

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('2022-06-07')
tuesdata <- tidytuesdayR::tt_load(2022, week = 23)

donations <- tuesdata$pride_aggregates

# Or read in the data manually

pride_aggregates <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-06-07/pride_aggregates.csv')
fortune_aggregates <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-06-07/fortune_aggregates.csv')
static_list <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-06-07/static_list.csv')
pride_sponsors <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-06-07/pride_sponsors.csv')
corp_by_politician <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-06-07/corp_by_politician.csv')
donors <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-06-07/donors.csv')

Data Dictionary

`pride_aggregates.csv`

Pride sponsors who have donated to Anti-LGBTQ Campaigns

variable	class	description
Company	character	Company
Total Contributed	double	Total Contributed to anti-LBGTQ politicians
# of Politicians Contributed to	double	# of politicians contributed, anti-LBGTQ
# of States Where Contributions Made	double	# of states where contributions were made to anti-LBGTQ

`fortune_aggregates.csv`

Fortune 500, Pride sponsors who have donated to Anti-LGBTQ Campaigns

variable	class	description
Company	character	Company name
Total Contributed	double	Total contributed to anti-LBGTQ politicians
# of Politicians Contributed to	double	# of politicians contributed to
# of States Where Contributions Made	double	# of states where contributions made to anti-LBGTQ

`static_list.csv`

Overview of company, pride sponsors, HRC Business pledge

variable	class	description
Company	character	Company
Pride?	logical	Donated to pride
HRC Business Pledge	character	HRC Business pledge
Amount Contributed Across States	double	Amount contributed across states to anti-LBGTQ politicians
# of Politicians Contributed to	double	# of politicians contributed
# of States Where Contributions Made	double	# of states

`pride_sponsors.csv`

variable	class	description
Company	character	Company
Pride Event Sponsored	character	Event sponsored
Sponsorship Amount, where available	character	Sponsorship amount level
Year	double	Year
Source	character	Source
True donor value	character	True donor name/value

`corp_by_politician.csv`

variable	class	description
Politician	character	Politician
SUM of Amount	double	Sum of amount in USD to anti-LBGTQ
Title	character	Title of politician
State	character	State

`donors.csv`

variable	class	description
Donor Name	character	variable
"True" Donor - Pride Sponsor Match Only	character	variable
"True" Donor - Fortune Match Only	logical	variable
Pride and Sponsor Match?	character	variable
Donor Name - Combined	character	variable

`contribution_data_all_states.csv`

variable	class	description
Company	character	Company
Pride and Sponsor Match?	character	Pride and Sponsorship Match
Pride?	logical	Pride event sponsor
HRC Business Pledge	character	HRC Busines pledge
Donor Name	character	Donor name
Politician	character	Politician
State	character	state
Amount	double	Amount in USD
Date	double	Date
Citation	logical	Citation
Donor Type	character	Donor Type
Comments	logical	Comments
ARCHIVE - Company Manually Determined (May Not Match Pride Sponsors List)	logical	Archive

Cleaning Script

library(httr)
library(tidyverse)

# overall URL
orig_url <- "https://www.dataforprogress.org/accountable-allies"

# direct link to the iFrame that builds the table
iframe_url <- "https://dfp-accountable-allies.netlify.app/fortune"

# Found the link to the GoogleSheets
par_url <- "https://sheets.googleapis.com/v4/spreadsheets/1Bj8YMaqxYrh2PxVhI1M1kLSbIMSN7vTpR2OZxg1DoXw"

# Extract data from JSON
get_content <- function(url){
  raw_content <- GET(url) |> content()
  
  nm_content <- raw_content$values[1] |> unlist() |> janitor::make_clean_names()
  
  raw_df <- raw_content$values[2:length(raw_content$values)] |>
    tibble(data = _) |>
    mutate(data = map(data, ~set_names(.x, nm = nm_content[1:length(.x)]))) |>
    unnest_wider(data) |>
    readr::type_convert()
  
  raw_df
}


# get individual datasets
fort_agg_url <- "https://sheets.googleapis.com/v4/spreadsheets/1Bj8YMaqxYrh2PxVhI1M1kLSbIMSN7vTpR2OZxg1DoXw/values/Fortune%20Aggregates"

fort_agg_df <- get_content(pride_agg_url)

pride_agg_url <- "https://sheets.googleapis.com/v4/spreadsheets/1Bj8YMaqxYrh2PxVhI1M1kLSbIMSN7vTpR2OZxg1DoXw/values/Pride%20Aggregates"

pride_agg_df <- get_content(pride_agg_url)

static_list_url <- "https://sheets.googleapis.com/v4/spreadsheets/1Bj8YMaqxYrh2PxVhI1M1kLSbIMSN7vTpR2OZxg1DoXw/values/Static%20List"

static_list_df <- get_content(static_list_url)

pride_sponsor_url <- "https://sheets.googleapis.com/v4/spreadsheets/1Bj8YMaqxYrh2PxVhI1M1kLSbIMSN7vTpR2OZxg1DoXw/values/Pride%20Sponsors"

pride_sponsor_df <- get_content(pride_sponsor_url)

pride_sponsor_df |> glimpse()


raw_fort_agg <- GET(fort_agg_url) |> content()

fort_agg_nm <- raw_fort_agg$values[1] |> unlist() |> janitor::make_clean_names()

raw_fort_agg_df <- raw_fort_agg$values[2:length(raw_fort_agg$values)] |>
  tibble(data = _) |>
  mutate(data = map(data, ~set_names(.x, nm = fort_agg_nm))) |>
  unnest_wider(data) |>
  readr::type_convert() |>
  mutate(total_contributed = parse_number(total_contributed))

url_builder <- function(text){
  
  text <- stringr::str_replace_all(text, " ", "%20")
  text <- stringr::str_replace_all(text, "/", "%2F")
  glue::glue("https://sheets.googleapis.com/v4/spreadsheets/1Bj8YMaqxYrh2PxVhI1M1kLSbIMSN7vTpR2OZxg1DoXw/values/{text}")
}

corp_pol_df <- url_builder("Corp by Politician") |>
  get_content()

library(httr)
library(tidyverse)
raw_sheet <- "https://sheets.googleapis.com/v4/spreadsheets/1Bj8YMaqxYrh2PxVhI1M1kLSbIMSN7vTpR2OZxg1DoXw" |>
  GET() |>
  content()

all_sheets <- raw_sheet |>
  tibble(data = _) |>
  unnest_longer(data) |>
  unnest_wider(data) |>
  unnest_wider(properties) |>
  unnest_wider(gridProperties) |>
  janitor::clean_names() |>
  select(sheet_id, title, row_count:column_count)

all_sheets

url_builder <- function(text){
  
  text <- stringr::str_replace_all(text, " ", "%20")
  text <- stringr::str_replace_all(text, "/", "%2F")
  glue::glue("https://sheets.googleapis.com/v4/spreadsheets/1Bj8YMaqxYrh2PxVhI1M1kLSbIMSN7vTpR2OZxg1DoXw/values/{text}")
}

all_sheets |>
  pull(title) |>
  url_builder()

all_sheets |>
  mutate(sheet_url = url_builder(title)) |>
  pull(sheet_url)

https://sheets.googleapis.com/v4/spreadsheets/1Bj8YMaqxYrh2PxVhI1M1kLSbIMSN7vTpR2OZxg1DoXw/values/Fortune%201000%20List/Search%20Keys

all_sheets |>
  slice(11) |>
  pull(title) |>
  url_builder()

###### googlesheets

library(googlesheets4)

gs4_deauth()

# courtesty of Jenny Bryan
ssid <- "1Bj8YMaqxYrh2PxVhI1M1kLSbIMSN7vTpR2OZxg1DoXw"
(ss <- gs4_get(ssid))

read_sheet(ss, "Fortune Aggregates") |> 
  write_csv('2022/2022-06-07/fortune_agg.csv')

read_sheet(ss, "Pride Sponsors")

# grab and clean sheets
sub_sheets <- ss$sheets |> 
  slice(2:6, 12:13) |> 
  select(name) |> 
  mutate(title = paste0(janitor::make_clean_names(name), ".csv")) 

all_df <- sub_sheets |> 
  mutate(data = map(name, ~read_sheet(ss, .x)))

write_df <- function(title, data){
  write_csv(x = data, file =glue::glue("2022/2022-06-07/{title}"))
}

# write out the datasets
all_df |> 
  select(title, data) |> 
  pwalk(write_df)
  
all_df |> 
  pull(data) |> 
  map(create_tidytuesday_dictionary)

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

2022-06-07

2022-06-07

readme.md

Please add alt text to your posts

Chart type

Type of data

Reason for including the chart

Link to data or source

Pride Donations

Get the data here

Data Dictionary

`pride_aggregates.csv`

`fortune_aggregates.csv`

`static_list.csv`

`pride_sponsors.csv`

`corp_by_politician.csv`

`donors.csv`

`contribution_data_all_states.csv`

Cleaning Script

Files

2022-06-07

Directory actions

More options

Directory actions

More options

Latest commit

History

2022-06-07

Folders and files

parent directory

readme.md

Please add alt text to your posts

Chart type

Type of data

Reason for including the chart

Link to data or source

Pride Donations

Get the data here

Data Dictionary

pride_aggregates.csv

fortune_aggregates.csv

static_list.csv

pride_sponsors.csv

corp_by_politician.csv

donors.csv

contribution_data_all_states.csv

Cleaning Script

`pride_aggregates.csv`

`fortune_aggregates.csv`

`static_list.csv`

`pride_sponsors.csv`

`corp_by_politician.csv`

`donors.csv`

`contribution_data_all_states.csv`