Día 7 – Accesibilidad #30DayMapChallenge. ¿Qué tan cerca estas de un Coco Baleadas?. Herramientas: R con los paquetes sf, osrm, ggplot2, ggspatial, dplyr, ggimage, RcolorBrewer, osmdata y grid.

Día 9 - Analogo, #30DayMapChallenge. De México a Ecuador, me faltan Belice y Honduras. Se aceptan regalos :)

Día 8 – Urbano #30DayMapChallenge Urbes más importantes de América Central. Fuente: Open Street Maps. Herramienta: R usando los paquetes sf, ggplot2, osmdata, dplyr, showtext y ggtext

Day 5 – Earth #30DayMapChallenge. Shortest Distance from Each Country on Earth to Honduras. Tools: R using packages sf, ggplot2, dplyr, rnaturalearth, rnaturalearthdata, geosphere, showtext and grid.

Sure thing, my code is kind of a mess. So, let me comment on it and I will put it in github to share with you.

Día 4 – Mis Datos #30DayMapChallenge. Catasetum integerrimum en Tegucigalpa, Honduras. Herramientas: R con los paquetes sf, ggplot2, osmdata, dplyr, showtext, ggtext, ggimage, grid y cowplot.

Día 3 – Polígonos #30DayMapChallenge. Densidad Poblacional Por Departamentos Honduras 2025. Fuente WorldPop. Herramientas: R con los paquetes raster, tidyverse, sf, exactextractr, ggtext, showtext elevatr, ggnewscale, units, patchwork y ggspatial.

Día 2 – Líneas #30DayMapChallenge, Distribución de Elevaciones Parque Nacional Pico Bonito Honduras. Herramientas: R con los paquetes sf, exactextractr, ggplot2, ggnewscale, ggtext, dplyr, terra, showtext, scales, patchwork, ggspatial, metR, rnaturalearth y rnaturalearthdata.

Día 1 – Puntos #30DayMapChallenge Puntos de ocurrencia de Chimancé (Pan troglodytes) según datos de GBIF. Herramientas: R con los paquetes rgbi, rnaturalearth rnaturalearthdata, sf, ggplot2, dplyr, ggspatial, showtext y grid

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.

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.

Day 21 | Timeseries – Fossils| #30DayChartChallenge. Visualization made with R using #ggplot2, #dplyr, #showtext, #ggrepel and #janitor. | Source: Our World in Data

Day 20 | Timeseries – Urbanization | #30DayChartChallenge. Visualization made with R using #ggplot2, #sf, #dplyr, #scales, #grid, #ggshadow, #extrafont and #cowplot. | Source: Worldometers

Day 12 | Distributions – Data Day – Data.gov | #30DayChartChallenge. Visualization made with R using #sf, #tigris, #ggthemes, #patchwork, #tidyverse, #ggtext and #showtext . | Source: data.gov - catalog.data.gov/dataset/biod...

Day 15 | Relationships – Complicated | #30DayChartChallenge. Visualization made with R using #tidyverse, #ggtext and #showtext . | Source: google trends trends.google.com/trends/explo...

Día 11 | Distribuciones – “Stripes” | #30DayChartChallenge. La visualización fue creada usando R basado en los paquetes: #ggplot2, #dplyr, #sf, #lubridate, #ggtext, #showtext, #RcolorBrewer, #rnaturalearth y #cowplot. Fuente: CHIRPS.

Day 10 | Distributions / Multi – Modal | #30DayChartChallenge. Visualization made with R using #ggplot2, #tidyverse, #cowplot, #stars, #raster, #ggspatial and #sf. Data source: Sentinel-2 MSI (2024)

Day 7 | Distributions– Outliers | #30DayChartChallenge. Visualization made with R using #ggplot2, #tidyverse, #terra, #ggtext, #showtext y #sf. Data source: Sentinel-2 MSI (2019-2024)

Day 6 | Comparisons – Florence Nightingale (theme day) | #30DayChartChallenge. Visualization made with R using #tidyverse, #ggtext and #showtext. Data source: HDX - data.humdata.org/dataset/cod-....

Day 5 | Comparisons – Ranking | #30DayChartChallenge. Visualization develop with R using #ggplot2, #dplyr, #ggtext, #showtext, #glue and #ggimage. Data source: Opta Analyst.

Día 4 | Comparaciones – Grande o Pequeño | #30DayChartChallenge. La visualización fue creada usando R basado en los paquetes: #ggplot2, #dplyr, #treemapify. Fuente: Sistema de Educación Superior - UNAH – 2023.