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.
Day 27 | Uncertainties – Noise | #30DayChartChallenge. Visualization made with R using #ggplot2, #showtext and #dplyr | Source: USA - National Institute for Occupational Safety and Health.
Día 9 | Distribuciones – Divergente | #30DatChartChallenge. | Visualización hecha usando R con los paquetes #ggplot2, #dplyr, #patchwork, #sf, #ggtext, #showtext, #raster, #exactextractr and #SPEI.
Day 26 | Uncertainties – Monochrome | #30DayChartChallenge. Visualization made with R using #vegan, #ggplot2, #showtext, #patchwork and #sf | Source: Barro Colorado Island (BCI) tree census | vegan::BCI.
Día 25 | Incertidumbre – Riesgo | #30DayChartChallenge | Visualización hecha usando R a partir de los paquetes #ggplot2, #dplyr, #scales, #showtext y #sysfonts. | Fuente: Gannet – Virtual Assitant (app.gannet.ai) desarrollado por Data Friendly Space. La respuesta fue generada usando tres fuentes – 1) State of the Climate in Latin America and the Caribbean, 2) Latin America and the Caribbean Regional Overview of Food Security and Nutrition y 3) Anticipatory Action and Response Plan.
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 23 | Timeseries – Log Scale | #30DayChartChallenge. Visualization made with R using #ggplot2, #dplyr, #showtext, #patchwork, #janitor and #scales. | Source: Our World in Data
Day 22 | Timeseries – Stars | #30DayChartChallenge. Visualization made with R using #ggplot2, #dplyr, #showtext, #lubridate and #cranlogs. | Source: cranlogs R Package.