For day 1 of #30DayMapChallenge, I made a map about ospreys with data from Feederwatch, a program for counting birds in November-April. Ospreys are abundant in North America, but they winter in the southern U.S. states (and farther south).
[#]rstats #dataviz
Code: https://github.com/bardolater/30DayMapChallenge/blob/main/2024/01_Points.r
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For day 2 of #30DayMapChallenge, my spouse forbade me from making a map in #rstats of crashes on highways, so looked around for something new and shapefiles of Canadian rail lines. (However, there were fewer shapefiles than provinces and territories...) I am a big fan of packages like {usmap} that simplify map making, so I was happy to discover {canadianmaps}.
Code: https://github.com/bardolater/30DayMapChallenge/blob/main/2024/02_Lines.r
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For day 3 of #30DayMapChallenge, I used data within the {tigris} package about statistical areas of native peoples. Polygons are perhaps the easiest type of shape...
Code: https://github.com/bardolater/30DayMapChallenge/blob/main/2024/03_Polygons.R
[#]rstats #dataviz
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Day 4 of #30DayMapChallenge: Hex Map
This is a simple map of median household income in the USA from the 2022 American Community Survey. No going to a website to download something--I pull in the Census data directly with the {tigris} 📦 in #rstats. (I had to find a shapefile online for the base map, however...) #dataviz
Code: https://github.com/bardolater/30DayMapChallenge/blob/main/2024/04_Hex.r
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Catching up on day 5 of #30DayMapChallenge with a quick #stats map of the Appalachian Trail. I hope to hike it some day.
Code: https://github.com/bardolater/30DayMapChallenge/blob/main/2024/05_Route.r
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