Geography Examples Weekly: What It Actually Is and How to Use It
Geography Examples Weekly is a curated collection of geography-focused datasets and example files that people in geospatial analysis, GIS work, and spatial data science use for practice, testing, and reference. You'll typically find shapefiles, GeoJSONs, CSV coordinate dumps, and sometimes raster examples organized by theme or difficulty. The main value is that someone already did the work of finding clean, non-broken files that actually load properly in QGIS, ArcGIS, or whatever tool you're using. The download process is straightforward. Head to their GitHub repository or the linked archive, grab the zip file for whichever category you need, and extract it. Don't skip checking the README inside each folder because some of these datasets have specific coordinate reference systems that aren't obvious from the filenames alone. I once imported a shapefile thinking it was in WGS84 when it was actually in EPSG:32633, which made my entire map look stretched and wrong until I caught it. Once extracted, most files open directly in QGIS without issues. For ArcGIS users, you might need to reproject a few of them depending on your project CRS. The GeoJSON files tend to be the most portable across platforms. If you're working in Python with geopandas, just read them straight in with no preprocessing needed in most cases.
Common Pitfalls People Run Into
The biggest problem I see is when people assume every example file has clean topology. A lot of these are built for visualization practice, not production use, so you'll find sliver polygons, overlapping boundaries, and the occasional null geometry that will make your spatial join fail silently. Before you run any analysis, always check the geometry validity first. In QGIS there's a Vector menu option for checking geometry. In PostGIS, ST_IsValid catches most issues upfront. Another issue is coordinate system ambiguity. Some files don't embed a CRS properly, and QGIS will sometimes just assign it WGS84 by default even when that's wrong. When you notice features appearing in the ocean off the coast of Africa, that's your cue to inspect the actual projection metadata before doing any area calculations. The workaround is to open the .prj file if one exists, or use the CRS selector in QGIS to manually set the correct one based on the documentation provided with the dataset.
What Beginners Miss
Most people treat these examples as something to just load and move on from. They don't realize you can use the collection to test how your pipeline handles real edge cases like multipart polygons, mixed geometry types in a single layer, or datasets with hundreds of thousands of vertices. That last one matters if you're building anything that processes spatial data at scale because a query that works fine on a 500-record boundary dataset will stall completely when you throw a national-level shapefile with complex coastlines at it. I'd also recommend running a quick attribute count comparison after loading each file. Some of the example datasets have more attributes than they seem to on the surface, and that extra metadata can bloat your processing time if you're not selecting only the fields you actually need. One user told me their geopandas merge went from 45 seconds down to 3 seconds just by dropping unused columns before the join.
Get the Full Details
Downsides and Limitations
The collection isn't comprehensive and it hasn't been updated consistently. Some of the older folders contain datasets that were pulled from sources that are no longer publicly available, which means certain links in the documentation might be dead. There's also no standardized naming convention across different contributor submissions, so you'll spend time figuring out what each file actually contains rather than just knowing from the name. If you need consistently maintained, versioned datasets with formal documentation, you're better off going with USGS Earth Explorer for elevation data, Eurostat for European statistics, or the Natural Earth database for general purpose world boundaries. Geography Examples Weekly fills a different niche. It's useful when you want varied, practice-ready files for learning or testing your tools rather than needing authoritative data for a published report.
Getting the Most Out of It
Start by downloading the full collection and spending ten minutes skimming the folder structure. Take notes on which categories overlap so you know where to look next time. Keep a copy of the README files somewhere accessible because the metadata descriptions inside them are often the only place where coordinate systems and data sources are documented. Don't treat this as a one-time download. Check back periodically because new examples get added and broken ones get replaced, though the update cadence is inconsistent so don't rely on it for time-sensitive work.
