user2241910 - 1 year ago 126

Python Question

I have a GeoDataFrame with some polygons (from some County shape files).

`0 POLYGON ((-118.71455 46.822508, -118.67662 46....`

1 POLYGON ((-118.663169 47.043673, -118.66334 47...

2 POLYGON ((-118.484262 46.73667, -118.495995 46...

3 POLYGON ((-118.483051 46.839378, -118.482689 4...

4 POLYGON ((-118.82874 46.77891, -118.822177 46....

5 POLYGON ((-118.606476 46.96391999999999, -118....

I'm trying to do take some intersections of these polygons with some polygons in another GeoDataFrame (same state). The coordinates of the polygons, however, are completely different.

`0 POLYGON ((552346.2856999999 380222.8998000007,...`

1 POLYGON ((529754.7249999996 409135.9135999996,...

2 POLYGON ((552333.0957000004 371726.9315000009,...

3 POLYGON ((542734.0181999998 376530.5831000004,...

4 POLYGON ((552291.6204000004 362052.4251000006,...

They're the same state, and the plots look the same. I'm new to shapefiles, but think if I could "normalize" these polygons (divide all the points in the x dimension by their smallest value, same for the y dimension), then the polygons in the two DataFrames should be comparable.

I've tried:

`df.scale(origin=(1,1))`

and also

`df.scale(xfact=1.0/df.total_bounds[0], yfact=1.0/df.total_bounds[1])`

without any luck. They just return their original values (or close to, values should be between 1 and 2). I could loop through these polygons and unpack their points and divide them, but I am hoping there's a more elegant solution way.

Running the latest dev version of geopandas 0.1.0, python 2.7 (I know...time to move on), OSX.

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Answer Source

You need to reproject or transform one of the geometries to a common coordinate reference system.

See documentation for `GeoSeries.to_crs(crs=None, epsg=None)`

to do this.

The first GeoDataFrame looks like EPSG:4326 (this is a guess, there are other geographic coordinate reference systems). The second is possibly a UTM or State plane projection.

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