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Unleashing the power of geospatial data: 20 python libraries transforming location-based services & beyond
Geospatial data refers to information that is linked to a specific place on earth, such as geographic coordinates or addresses.
Geo data is unique in:
- Location Context
- Spatial Relationships
- Coordinate System Reference
- Visual Representation
- Complex Structures
- Data Integration
- Geocoding: Converting address to coordinates
- Spatial Query: Searching for features like proximity to a point.
- Intersection: Finding the overlap between features.
- Buffering: Creating a polygon around a point, line or polygon.
- Union: Combining polygon features into a single one.
- Dissolve: Merging polygon based on a common attribute.
- Overlay: Creating a new layer by combining layers.
- Raster to Vector Conversion
- Distance Measurement: Calculating the feature distance.
- Projection Transformation: Changing projection of a layer.
Valuable in several fields:
- location-based services, like navigation apps.
- Urban planning and land use analysis.
- Environmental monitoring and resource management.
- Crime analysis
Challenges of geospatial data:
- real-time updates
- accessibility
- data visualization
| Title | Description | Link |
|---|---|---|
| Pydeck (⭐ 11K) | WebGL2 powered visualization framework |  |
| Folium (⭐ 6.1K) | Interactive maps | |
| Geopy (⭐ 3.9K) | Geocoding & reverse geocoding | |
| Geopandas (⭐ 3.5K) | Geospatial data in a pandas DataFrame | |
| Shapely (⭐ 3.2K) | Geometric operations | |
| Rasterio (⭐ 1.9K) | Reading/writing raster datasets (satellite imagery) | |
| ArcGIS (⭐ 1.5K) | ArcGIS for Python | |
| PySAL (⭐ 1.1K) | Spatial analysis (spatial statistics & econometrics) | |
| ArcGIS (⭐ 1.5K) | ArcGIS for Python | |
| Fiona (⭐ 1K) | Reading/writing geo data formats (shapefiles, GeoJSON, GPX) | |
| Pyproj (⭐ 840) | Projections & transformations of geospatial data | |
| NetworkX | Analyzing/modeling network data (spatial networks) | |
| Cartopy | Creating maps and plotting geospatial data | |
| Gdal | Working with various geospatial data formats/projections | |
| Gevent | Asynchronous I/O and network operations for large data sets | |
| RTree | Indexing/querying geospatial data | |
| Descartes | Plotting geospatial data in Matplotlib | |
| PyQGIS | Working with QGIS GIS software from Python | |
| OSMnx | Working with OpenStreetMap data (downloading, analyzing, visualizing) | |
| Geojson | Working with GeoJSON data format | |
| Geohash | Encoding/decoding geo data to ASCII string format. | |
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