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
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 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 - https://data.humdata.org/dataset/cod-ps-hnd.
Honduras - Subnational Population Statistics | Humanitarian Dataset | HDX

Proyecciones de Población del Instituto Nacional de Estadística - INE - por edad y sexo según Departamento y Municipio 2020 REFERENCE YEAR: 2024 These tables are suitable for database or GIS linkage to the [Honduras - Subnational Administrative Boundaries](https://data.humdata.org/dataset/cod-ab-hnd) using the ADM0, ADM1, or ADM2_PCODE fields. Access the Honduras - Subnational Population Statistics dataset to support humanitarian efforts.