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Looking at the two datasets above, it appears that the GEOID column from va_tract and the state, county, and tract columns combined from va_df could serve as the unique key for joining these two dataframes together. To solve this problem, we can join the two dataframes together via a field or column that is common to both dataframes, which is referred to as a key. Performing Dataframe Operations # Create new column from old columns to get combined FIPS code # We have a potential problem: We have the census data, and we have the shapefile of census tracts that correspond with that data, but they are stored in two separate variables ( va_df and va_tract respectively)! That makes it a bit difficult to map since these two separate datasets aren’t connected to each other. This number matches with the number of census records that we have on file. Remote Sensing Coordinate Reference Systems Window Operations with Rasterio and GeoWombatĥ - Accessing OSM & Census Data in Python Point Density Measures - Counts & Kernel Density Proximity Analysis - Buffers, Nearest Neighbor Raster Coordinate Reference Systems (CRS) Vector Coordinate Reference Systems (CRS) Manipulating Spatial Objects: Points, Lines, Polygons in PythonĢ - Nature of Coordinate Systems in Python Working with Spatial Vector Data using GeoPandas Geospatial Environment Installation Guide PyGIS - Open Source Spatial Programming & Remote Sensing