jthomasmock

gen_plot <- function(xvals = c(1,12), yvals = c(1,10), n = 10, 
                   distance = seq(-3,3,length.out =n),
                   seed = NULL, palette = c("red", "blue")){
  
  # adapted from: https://stackoverflow.com/questions/50275195/
  segment.shift <- function(x1,x2,y1,y2, d){
    
    # calculate vector
    v <- c(x2 - x1,y2 - y1)
    

jonspring

# Inspired by Nadieh Bremer's lasso annotations here: https://twitter.com/NadiehBremer/status/1277622602735865856
# h/t Cedric Scherer: https://twitter.com/CedScherer/status/1278351840074240001


library(ggplot2); library(ggforce)

add_lasso_layer <- function(x1, x2, y) {
  width = x2 - x1
  space = width * 0.05
  lasso_points = data.frame(

gkaramanis

library(ggforce)
library(ggplot2)

leaf <- data.frame(
  x = c(1.6, 1.5, 1.8, 1.5, 1.6, 1.3),
  y = c(2, 2, 1.5, 1, 1, 1.5)
)

ggplot(leaf, aes(x, y)) +
  geom_polygon(fill = NA, colour = 'grey') +

andrewheiss

library(tidyverse)

# See https://stackoverflow.com/a/17313561/120898
pts <- function(x) {
  as.numeric(grid::convertUnit(grid::unit(x, "pt"), "mm"))
}

df <- tibble(x = 1:10, y = 1:10)

Torvaney

library(tidyverse)

year <- 2019
start_date <- lubridate::date(str_glue("{year}-01-01"))  # there must be a better way??


month_colours <- c(
  "January"   = "#a5cdff",
  "February"  = "#c9e1ff",
  "March"     = "#b2edb6",

romainfrancois

``` r
library(purrr)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 

zross

• Eurostat, World Bank and others: https://ikashnitsky.github.io/2017/data-acquisition-two/
• Star Wars data: in dplyr, http://dplyr.tidyverse.org/reference/starwars.html
• Baby names data: babynames package, https://cran.r-project.org/web/packages/babynames/index.html
• Movies data: https://cran.r-project.org/web/packages/ggplot2movies/index.html ggplot2movies package
• Game of Thrones screen time: https://github.com/Preetish/GoT_screen_time
• Open Bike Data: https://github.com/ropensci/bikedata
• Tons of data through 538: https://cran.r-project.org/web/packages/fivethirtyeight/vignettes/fivethirtyeight.html
• Public health data England: fingertipsR, https://cran.r-project.org/web/packages/fingertipsR/
• Financial data via Quandl: https://www.quandl.com/tools/r
• Cyclones: https://github.com/ropensci/rrricanesdat

hrbrmstr

library(V8)
library(xml2)
library(httr)
library(rvest)
library(stringi)
library(tidyverse)

get_page <- function(num=1, seed=Sys.Date()) {
  
  GET(

hrbrmstr

library(httr)
library(magick)
library(hrbrthemes)
library(ggplot2)

theme_tweet_rc <- function(grid = "XY", style = c("stream", "card"), retina=TRUE) {
  
  style <- match.arg(tolower(style), c("stream", "card"))
  
  switch(

davidofwatkins

Google Fonts suggests syncing fonts to your computer with a tool called SkyFonts. However, if you're running MacOS and want to keep your machine updated with all Google Fonts without any extra software, you can do this with Git, thanks to the Google Fonts Repo.

To do this, run the following in your terminal:

cd ~/Library/Fonts/
git clone --depth 1 https://github.com/google/fonts.git google-fonts

Done! In the future, you can download new fonts by running: