docs: add Geolocation category intro

The Geolocation category page had no intro, so its meta description fell back to generic text and readers got no guidance on which library to pick.

Co-Authored-By: Claude <noreply@anthropic.com>

website/data/category_intros/geolocation.md

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+Addresses become coordinates with geopy, whose Python geolocation API covers many geocoding services. GeoPandas analyzes map data, and GeoDjango serves it.
+
+How to choose:
+
+- Addresses to coordinates, and coordinates back to addresses: geopy
+- The distance between two points: geopy
+- Geographic data in tables and files, like shapefiles and GeoJSON: GeoPandas
+- Web apps that store and query geographic data: GeoDjango
+- A visitor's country or city from their IP address, in a Django project: GeoDjango
+- Building, encoding, and validating GeoJSON objects by hand: geojson
+
+geopy is [a client for geocoding services, not a service itself](https://geopy.readthedocs.io/en/stable/#geopy-is-not-a-service), and each service has its own terms of use, quotas, and pricing. Every geocoder has a `geocode()` method that turns an address into a location, and most also have `reverse()` for the other way around. For OpenStreetMap's Nominatim, [set a `user_agent` that names your app](https://geopy.readthedocs.io/en/stable/#geopy.geocoders.Nominatim) and follow [its usage policy](https://operations.osmfoundation.org/policies/nominatim/). The policy bans heavy use, auto-complete, and systematic queries. It also asks you to cache results and show attribution, and it discourages bulk geocoding. To geocode a DataFrame, [wrap the call in `RateLimiter`](https://geopy.readthedocs.io/en/stable/#usage-with-pandas), which adds delays between requests and retries failed ones. Check first that your service allows bulk requests at all. For distances, `geopy.distance.distance` [computes the geodesic distance](https://geopy.readthedocs.io/en/stable/#module-geopy.distance) between two points.
+
+GeoPandas adds geometry columns to pandas, so you can [do in Python what would otherwise take a spatial database such as PostGIS](https://geopandas.org/en/stable/). Load a shapefile, GeoJSON, or GeoPackage with `read_file()`, which [detects the file type and returns a GeoDataFrame](https://geopandas.org/en/stable/getting_started/introduction.html), and write it back with `to_file()`. For a table of latitudes and longitudes, [build the points with `points_from_xy()`](https://geopandas.org/en/stable/gallery/create_geopandas_from_pandas.html) and set `crs="EPSG:4326"`. To geocode a column of addresses, GeoPandas [calls geopy for you](https://geopandas.org/en/stable/docs/user_guide/geocoding.html), so the geocoding service's terms still apply.
+
+GeoDjango is [a contrib module that ships with Django](https://docs.djangoproject.com/en/stable/ref/contrib/gis/tutorial/). It adds model fields for geometries, spatial queries to the ORM, and geometry editing to the admin. Its tutorial assumes you already know Django. Run it on PostGIS, which its docs recommend as [the most mature and feature-rich open source spatial database](https://docs.djangoproject.com/en/stable/ref/contrib/gis/install/#spatial-database). To load a shapefile, [`ogrinspect` writes the model and a `LayerMapping` imports the rows](https://docs.djangoproject.com/en/stable/ref/contrib/gis/tutorial/#importing-spatial-data). For IP geolocation, [GeoIP2](https://docs.djangoproject.com/en/stable/ref/contrib/gis/geoip2/) looks up a country or city in a MaxMind or DB-IP database file you download.
+
+geojson has [a class for every object in the GeoJSON spec](https://github.com/jazzband/geojson), and `geojson.dumps()` and `geojson.loads()` [wrap the standard json functions](https://github.com/jazzband/geojson#geojson-encodingdecoding) to encode and decode them. Check an object with [its `is_valid` property and `errors()` method](https://github.com/jazzband/geojson#validation). To encode your own classes the same way, [give them a `__geo_interface__`](https://github.com/jazzband/geojson#custom-classes), which GeoPandas' `from_features()` [also accepts](https://geopandas.org/en/stable/docs/reference/api/geopandas.GeoDataFrame.from_features.html).
+
+Latitude and longitude are angles, so measure distance and area in a projected coordinate system, in meters or feet. In GeoPandas, you [always need one](https://geopandas.org/en/stable/getting_started/introduction.html#Projections) for those operations, so reproject with `to_crs()` first. GeoDjango calls choosing a geometry field's SRID [an important decision](https://docs.djangoproject.com/en/stable/ref/contrib/gis/model-api/#selecting-an-srid), since projected systems ease distance calculations. geopy's `distance` works on an ellipsoidal model of the earth, so it takes latitudes and longitudes as they are.