Add some swag to your ggplots, with fontawesome symbols and colors: https://nrennie.rbind.io/blog/adding-social-media-icons-ggplot2/ #rstats #ggplot #fontawesome #ggtext
Adding social media icons to charts with {ggplot2} – Nicola Rennie

Adding social media icons to your data visualisation is a great, concise way to put your name on your work, and make it easy for people to find your profile from your work. This blog post explains how to add social media icons to {ggplot2} charts.

Nicola Rennie
Add some swag to your ggplots, with fontawesome symbols and colors: https://nrennie.rbind.io/blog/adding-social-media-icons-ggplot2/ #rstats #ggplot #fontawesome #ggtext
Adding social media icons to charts with {ggplot2} – Nicola Rennie

Adding social media icons to your data visualisation is a great, concise way to put your name on your work, and make it easy for people to find your profile from your work. This blog post explains how to add social media icons to {ggplot2} charts.

Nicola Rennie
Add some swag to your ggplots, with fontawesome symbols and colors: https://nrennie.rbind.io/blog/adding-social-media-icons-ggplot2/ #rstats #ggplot #fontawesome #ggtext
Adding social media icons to charts with {ggplot2} – Nicola Rennie

Adding social media icons to your data visualisation is a great, concise way to put your name on your work, and make it easy for people to find your profile from your work. This blog post explains how to add social media icons to {ggplot2} charts.

Nicola Rennie
Día 8 | Distribuciones – Histograma | #30DayChartChallenge. | Visualización hecha usando R con los paquetes #ggplot2, #dplyr, #patchwork, #sf, #ggtext, #showtext, #raster, #exactextractr, #ggscale y #scales.
Day 28 | Uncertainties – Inclusion | #30DayChartChallenge. Visualization made with R using #ggplot2, #dplyr, #ggtext and #showtext | Source: Google Trends.
Día 9 | Distribuciones – Divergente | #30DatChartChallenge. | Visualización hecha usando R con los paquetes #ggplot2, #dplyr, #patchwork, #sf, #ggtext, #showtext, #raster, #exactextractr and #SPEI.
Day 24 | Timeseries – Data Day – WHO | #30DayChartChallenge. Visualization made with R using #ggplot2, #dplyr, #showtext, #patchwork, #ggrepel, #glue, #ggtext, #sf and #rnaturalearth. | Source: WHO.
Day 19 | Timeseries – Smooth | #30DayChartChallenge. Visualization made with R using #ggplot2, #dplyr, #ggtext, #showtext, #patchwork, #sf and #rnaturalearth. | Source: Google Trends
Day 12 | Distributions – Data Day – Data.gov | #30DayChartChallenge. Visualization made with R using #sf, #tigris, #ggthemes, #patchwork, #tidyverse, #ggtext and #showtext . | Source: data.gov - https://catalog.data.gov/dataset/biodiversity-by-county-distribution-of-animals-plants-and-natural-communities
State of New York - Biodiversity by County - Distribution of Animals, Plants and Natural Communities

The NYS Department of Environmental Conservation (DEC) collects and maintains several datasets on the locations, distribution and status of species of plants and animals....

Day 15 | Relationships – Complicated | #30DayChartChallenge. Visualization made with R using #tidyverse, #ggtext and #showtext . | Source: google trends https://trends.google.com/trends/explore?date=all&q=Avril%20Lavigne%20Complicated&hl=en