uses consistent style

geocompx · Oct 12, 2023 · 599a456 · 599a456
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diff --git a/01-spatial-data.qmd b/01-spatial-data.qmd
@@ -17,7 +17,7 @@ The **geopandas** ecosystem provides a comprehensive approach for working with v
 This is not the case for raster data, however: there are several partially overlapping packages for working with raster data, each with its own advantages and disadvantages.
 In this book we focus on the most prominent one:
 
-- **rasterio**---a spatial-oriented package, focused on "simple" raster formats (such as GeoTIFF), representing a raster using a combination of a **numpy** array, and a metadata object (`dict`) specifying the spatial referencing of the array
+- **rasterio** is a spatial-oriented package, focused on "simple" raster formats (such as GeoTIFF), representing a raster using a combination of a **numpy** array, and a metadata object (`dict`) specifying the spatial referencing of the array
 
 Another raster-related package worth mentioning is **xarray**.
 It is a general-purpose package for working with labeled arrays, thus advantageous for processing "complex" raster format (such as NetCDF), representing a raster using its own native classes, namely `xarray.Dataset` and `xarray.DataArray`.