geowrangler
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thinkingmachines
🌏 A python package for wrangling geospatial datasets
For reference, global indices computed for PH, MM, and TL after recode processing for water, toilet, and floor. https://colab.research.google.com/drive/1oA9OxL9_qMeylaCi3WA1NSSDtwky3a16?usp=sharing
- [ ] `poetry version prerelease` - [ ] `poetry publish build` - [ ] Auto update changelog - [ ] Auto gh release
Based on discussion #140 - [ ] Add warning in code - [ ] Add documentation for projecting to ESPG:3857 or custom crs before using grid generation
TODO (before implementation) * Current things not working - source links ([being worked on here](https://github.com/fastai/nbdev/issues/692)) - colab button ([being worked on here](https://github.com/quarto-dev/quarto-cli/issues/1224)) * Migration stuff specific to geowrangler: - update...
This will improve the doc site aesthetics (see [new nbdev](https://nbdev.fast.ai)) * replaces jekyll w/ quarto for site generation * removes need for custom nbdev (since black formatting is already implemented...
Allow ookla download to accept a date range request and aggregate stats for all the downloaded stats
This would be better if it accepted a date range - e.g. start = pd.to_datetime('2019-01-01') end = pd.to_datetime('2022-08-01') speeds = ookla.get_ookla_data(start,end) (Resulting dataframe would be a single aggregated dataframe of...
enhancement request: add asset index computation result as additional column to original data frame https://github.com/thinkingmachines/geowrangler/blob/master/geowrangler/dhs.py#L144
Right now, the `create_raster_zonal_stats` method of the raster zonal stats module only support single bands per call. Being able to handle multiple bands might be a nice enhancement to minimize...
### Discussed in https://github.com/thinkingmachines/geowrangler/discussions/109 We can use the [gist provided here](https://gist.github.com/butchtm/3eff004bae150ea1b1d2dfeffdb5de17) to implement the conversion of the quadkey to its geometry so it can be used by the raster zonal...
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🌏 A python package for wrangling geospatial datasets