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library(NCmisc)
library(janitor)
library(tidyverse)
library(patchwork)
library(showtext)
library(ggtextures)
library(png)
library(cowplot)Special thanks to Nicole Rennie for the inspiration for this blog post.1
Load Packages
Convert R Markdowns to R scripts
You can use the knitr::purl function to convert .Rmd files into .R scripts. If you prefer using .R scripts, this step is not necessary. To convert multiple files at once, you can create a function using the code below. Alternatively, if you prefer to convert the files manually, you can simply insert the filename for each .Rmd file one at a time.
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#Convert R Markdown to R script
# knitr::purl("filepath/filename.Rmd")Choose the directory where your converted .R scripts are located. Use the list.files function to create a character vector called all_files that contains the names of all files in the directory specified by file_path that have an “.R” or “.r” file extension.
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file_path <- ("/Users/alexreed/Documents/MEDS/Website/reedalexandria.github.io/posts/2022-12-31-rwrapped/data")
all_files <- list.files(path = file_path, recursive = TRUE, pattern = "\\.[Rr]$")
all_functions <- map(.x = all_files, .f = ~ list.functions.in.file(file.path(file_path, .x)))Select your top five packages
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func_data <- unlist(all_functions) |>
unname() |>
tabyl() |>
as_tibble() |>
rename(func = "unname(unlist(all_functions))") |>
slice_max(n, n = 5, with_ties = FALSE) Find the hex sticker .png for each package
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hex_imgs <- tibble(img = c("https://www.r-project.org/logo/Rlogo.png",
"https://www.r-project.org/logo/Rlogo.png",
"https://ggplot2.tidyverse.org/logo.png",
"https://ggplot2.tidyverse.org/logo.png",
"https://www.r-project.org/logo/Rlogo.png"))Plotting top functions
First, add a font similar to the Spotify font. The font used by Spotify is Spotify Circular.
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font_add("Circular", "/Users/alexreed/Downloads/Circular/CircularStd-Medium.otf")
showtext_auto()Use ggplot2 to create the top function graphic.
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top_functions <- ggplot() +
# add text with the numbers 1 to 5
geom_text(data = data.frame(),
mapping = aes(x = rep(1, 5),
y = 1:5,
label = paste0("#", 1:5)),
colour = "#00008b",
size = 20,
fontface = "bold",
family = "Circular") +
# add text with the names of the functions, and the number of times its used
geom_text(data = func_data,
mapping = aes(x = rep(2.25, 5),
y = 1:5,
label = paste0(func, "(), ", n, " times")),
colour = "#00008b",
hjust = 0,
size = 11,
fontface = "bold",
family = "Circular") +
# add images for each package
geom_textured_rect(data = hex_imgs,
aes(xmin = rep(1.5, 5), xmax = rep(2.1, 5),
ymax = 1:5-0.3, ymin = 1:5+0.3, image = img),
lty = "blank",
fill="transparent",
nrow = 1,
ncol = 1,
img_width = unit(1, "null"),
img_height = unit(1, "null"),
position = "identity") +
# add title using geom_text() instead of labs()
geom_text(data = data.frame(),
aes(x = 2.45, y = 0, label = "My Top Functions"),
colour = "#00008b",
fontface = "bold",
hjust = 0.5,
size = 14,
family = "Circular") +
# set axis limits and reverse y axis
scale_x_continuous(limits = c(0.9, 4)) +
scale_y_reverse(limits = c(5.5, -0.2)) +
# add a caption
labs(caption = "#RStatsWrapped") +
# set the theme
theme_void() +
theme(plot.background = element_rect(fill = "#ADD8E6", colour = "#ADD8E6"),
panel.background = element_rect(fill = "#ADD8E6", colour = "#ADD8E6"),
plot.margin = margin(40, 15, 10, 15),
plot.caption = element_text(colour = "#46214a",
margin = margin(t = 15),
face = "bold",
hjust = 1,
size = 30,
family = "Circular"))
top_functions
Add a geometry shape to the background
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set.seed(123)
curve1 <- tibble(x = 1:100) %>%
mutate(y = 20 + smooth(cumsum(rnorm(100))))
inset1 <- ggplot(data = curve1,
aes(x = x, y = y)) +
geom_area(fill = "#46214a") +
theme_void() +
coord_fixed() +
scale_y_reverse()Using the patchwork package, you can overlay the geometry shape and the function graphic to create a single plot.
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updated <- top_functions + inset_element(inset1, left = -1, right = 1.2, bottom = 0, top = 2.2, align_to = "full") &
theme(plot.background = element_rect(fill = "#ADD8E6", colour = "#ADD8E6"),
panel.background = element_rect(fill = "#ADD8E6", colour = "#ADD8E6"),
plot.margin = margin(40, 7, 5, 7),
plot.caption = element_text(colour = "#46214a",
margin = margin(t = 5),
face = "bold",
hjust = 1,
size = 30))I then created an album cover in Canva. The photo is from a Justin Timberlake concert I attended in Las Vegas, Nevada.
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album <- readPNG("/Users/alexreed/Documents/MEDS/Practice/wrapped/album_cover.png", native = TRUE)Now, combine the graphic and album cover to complete the #RStatsWrapped graphic.
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ggdraw(updated) +
draw_image(album,
scale = 0.35,
halign = 0.5,
valign = 0.99)
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#save final graphic
#ggsave("rwrapped_album.png", width = 2.5, height = 5, units = "in", )Footnotes
Nicola Rennie. December 3, 2022. nrennie.rbind.io/blog/2022-12-03-how-to-make-your-own-rstats-wrapped↩︎
Citation
BibTeX citation:
@online{reed2022,
author = {Alex Reed},
title = {R {Stats} {Wrapped}},
date = {2022-12-31},
url = {https://reedalexandria.github.io/2022-12-31-rwrapped},
langid = {en}
}
For attribution, please cite this work as:
Alex Reed. 2022. “R Stats Wrapped.” December 31, 2022. https://reedalexandria.github.io/2022-12-31-rwrapped.