Introduction
Why create maps with R?
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Base knowledge
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GitHub repository and exercise files
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1. Mapping Fundamentals
How to choose a map
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Geo marker and scatter plots
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Geo bubble charts
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Choropleth: Shaded area maps
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Hexbin maps or hexagonally binned choropleth
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Dot density
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Cartograms: Distorted area maps
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2. Processing GIS Data from Excel
Standardize country names with {countrycode}
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Join shapefiles with data in Excel files
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Convert addresses to coordinates with geocoding
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Challenge: Geolocate all US state capitol buildings
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Solution: Geolocate all US state capitol buildings
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3. Working with GIS Data Formats
GIS data formats: Raster or vector
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Vector GIS data: sf and sp
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Work with sf datasets and the tidyverse
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Challenge: Visualizing continent populations
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Solution: Visualizing continent populations
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4. Static Maps with ggplot2
Use geom_sf to visualize geo locations
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ggplot2 choropleth and continuous data
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ggplot2 choropleth and discrete data
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Label maps with ggrepel package
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Zoom into regions with coords_sf()
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Transform CRS with coord_sf()
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Challenge: Label a geobubble chart of Germany's biggest cities
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Solution: Label a geobubble chart of Germany's biggest cities
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Challenge: Visualize state coastline length with choropleth
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Solution: Visualize state coastline length with choropleth
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5. Interactive Maps with Leaflet
The basics of using Leaflet
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Use Leaflet to visualize geo locations
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Add labels and pop-ups to Leaflet maps
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Leaflet choropleth and continuous data
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Leaflet choropleth and discontinuous data
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Set a background color with leaflet.extras
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Challenge: Add pop-up labels to a map of German cities
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Solution: Add pop-up labels to a map of German cities
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Challenge: Interactive choropleth of state coastline length
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Solution: Interactive choropleth of state coastline length
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6. CRS, Projections, and Map Tiles
Base maps and tiles
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What are projections and CRS?
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Geographics vs. projected CRS
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How to choose CRS and use them with {sf}
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Conclusion
What else can you learn about creating maps in R?
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