Tootfinder

I did not know about ggplot_build() before. It can come in handy in situations where you want to access computed metrics of a #ggplot. https://ggplot2.tidyverse.org/reference/ggplot_build.html…

Build ggplot for rendering. — ggplot_build
build_ggplot() takes the plot object, and performs all steps necessary to produce an object that can be rendered. This function outputs two pieces: a list of data frames (one for each layer), and a panel object, which contain all information about axis limits, breaks etc. The ggplot_build() function is vestigial and build_ggplot() should be used instead.

You dont like the default color palett of #ggplot? You can change it: https://stackoverflow.com/questions/10504724/change-the-default-colour-palette-in-ggplot

Change the default colour palette in ggplot
I have written a function that returns a vector of color names: custom.colors <- function(n) { palette <- c("dodgerblue1", "skyblue4", "chocolate1", "seagreen4", "bisque3", ...

Beautiful palettes based on art for R and python: #rstats #ggplot

Examples of creative data visualizations, mostly ggplot: #ggplot #dataviz

r-charts.com provides example code for a variety of chart types, both in base R and ggplot: #rstats #ggplot…

R CHARTS | A collection of charts and graphs made with the R programming language
Over 1400 graphs with reproducible code divided in 8 big categories and over 50 chart types, in addition of tools to choose and create colors and color palettes

{ggchicklet}: library for rounded Segmented Column Charts: #ggplot #rstats

GitHub - hrbrmstr/ggchicklet: 🀫 Create Chicklet (Rounded Segmented Column) Charts
🀫 Create Chicklet (Rounded Segmented Column) Charts - hrbrmstr/ggchicklet

r-graph-gallery.com provides example code for a variety of chart types, both in base R and ggplot: #rstats #ggplot

The R Graph Gallery – Help and inspiration for R charts
The R graph gallery displays hundreds of charts made with R, always providing the reproducible code.

Make interactive ggplots with {ggiraph}: #ggplot #dataviz

Enrich your ggplots with extra panels along the x and y axis: #ggplot #dataviz