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Automated feature engineering for geospatial data

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**After running the code below on Google Colab:** ``` dist_spell = DistanceToNearest( "hospital", source_table="phcovid.gis_osm_pois_free_1", feature_name="dist_hospital", dburl="bigquery://ml-prototypes", ).cast(df) ``` **The following error occurs:** 2020-03-29 03:15:18.390 | ERROR | __main__::6 - An...

bug

For example, ```python mean_price = AggregateOf("hotel", which="price", how="mean") max_price = AggregateOf("hotel", which="price", how="max") min_price = AggregateOf("hotel", which="price", how="min") ```

help wanted
enhancement

Check implementation of `geomancer.backend.cores.DBCore` and `BigQueryCore`

enhancement

#### Issue Description getting features for columns takes around 25 seconds per column for a data frame of 56,761 rows #### Steps to reproduce the issue ```python df = pd.read_csv('sample.csv')`...

question
performance

Right now, a user can only input one `on` parameter to any of the `Spells`. ``` dist_primary = DistanceToNearest( on="primary", source_table="geospatial.ph_osm.gis_osm_roads_free_1", feature_name="dist_primary") ``` The `on` parameter is equivalent to a...

enhancement

Six different types of buildings: (1) residential, (2) damaged, (3) commercial, (4) industrial, (5) education, (6) health. For each lat-lng and specified radius or bounding box, extract the following features:...

enhancement

Depends on #30 Just follow this tutorial: https://romanvm.pythonanywhere.com/post/using-docker-travis-continuous-integration-25/

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