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146 results for “klauswiese”
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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)
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#Day11 | Distributions – Physiscal | #30DayChartChallenge | Density Distribution of Temperatures in Central America, source: World Bank Climate Portal. Built with #RStats using #ggplot2, #tidyverse and #ggridges.
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Pädagogikprofessor Klaus Zierer sieht eine Gefahr im unreflektierten Medienkonsum außerhalb der Schulen. Dieser müsse deshalb in Schulen thematisiert werden.
Medienbildung in Schulen: Experte plädiert für stärkeren Blick auf Handynutzung -
Día 1 | Comparaciones – Fracciones | #30DayChartChallenge. La visualización fue creada usando R basado en los paquetes #ggplot2, #dplyr, #scales, #ggtext, #patchwork, #showtext, #sf, #rnaturalearth, #rnaturalearthdata y #ggrepel. Fuente HDX - https://data.humdata.org/dataset/cod-ps-hnd
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#Día3 | Comparación– Mosaico | #30DayChartChallenge. Focos de calor detectados para los paises de América Central. Un gráfico con valores absolutos y otro con valores relativos. Creada usando R con #ggplot2, #treemapify, #dplyr, #scales, #readr y #stringr.
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Día 1 | Comparaciones – Part-to-Whole | #30DayChartChallenge. Distribución del área construida en Centroamérica según ESA WorldCover, donde el tamaño refleja los km² de suelo urbanizado por país. El gráfico fue creada usando R con los paquetes #ggplot2, #treemapify, #scales y #showtext.
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Day 23 | Timeseries – Log Scale | #30DayChartChallenge. Visualization made with R using #ggplot2, #dplyr, #showtext, #patchwork, #janitor and #scales. | Source: Our World in Data
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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
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Día 8 | Distribuciones – Histograma | #30DayChartChallenge. | Visualización hecha usando R con los paquetes #ggplot2, #dplyr, #patchwork, #sf, #ggtext, #showtext, #raster, #exactextractr, #ggscale y #scales.
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Day 28 | Uncertainties – Inclusion | #30DayChartChallenge. Visualization made with R using #ggplot2, #dplyr, #ggtext and #showtext | Source: Google Trends.
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Day 19 | Timeseries – Smooth | #30DayChartChallenge. Visualization made with R using #ggplot2, #dplyr, #ggtext, #showtext, #patchwork, #sf and #rnaturalearth. | Source: Google Trends
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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
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Day 7 | Distributions– Outliers | #30DayChartChallenge. Visualization made with R using #ggplot2, #tidyverse, #terra, #ggtext, #showtext y #sf. Data source: Sentinel-2 MSI (2019-2024)
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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.
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Día 3| Comparaciones – Círculos | #30DayChartChallenge. La visualización fue creada usando R basado en los paquetes #sf, #terra, #tidyterra, #extarctexactr, #ggplot2, #dplyr, #scales, #ggnewscale ,#ggtext, #patchwork y #showtext. Fuente SRTM y SIGMOF ICF - https://geoportal.icf.gob.hn
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Day 2 | Comparisons – Slope | #30DayChartChallenge. Analysis develop with R using #ggplot2, #tidyverse, #ggpmisc, , #terra, #ggtext, #showtext y #sf. Data source: Sentinel-2 MSI (2019-2024)
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Day 27 | Uncertainties – Noise | #30DayChartChallenge. Visualization made with R using #ggplot2, #showtext and #dplyr | Source: USA - National Institute for Occupational Safety and Health.
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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.
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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.
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Day 22 | Timeseries – Stars | #30DayChartChallenge. Visualization made with R using #ggplot2, #dplyr, #showtext, #lubridate and #cranlogs. | Source: cranlogs R Package.
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Day 24 | Timeseries – ILO Region for Africa | #30DayChartChallenge. Working poverty rate (percentage of employed living below US$2.15 PPP).
Source: https://ilostat.ilo.org/data/africa/
Tools: #R with packages #tidyverse, #ggtext, #showtext and #sf
