flatten geometry series (3D to 2D) in geopandas dataframe

geopandas_convert_geometry_3D_2D.py

# Often when reading in a ShapeFile from Basemap, you'll get: "ValueError: readshapefile can only handle 2D shape types"
# A trick can be to convert your geometry in your GeoPandas Dataframe and restoring the new flattened 2D geometry
# series back into a shapefile and try again.

# edit from http://stackoverflow.com/questions/33417764/basemap-readshapefile-valueerror  

from shapely.geometry import Polygon, MultiPolygon, shape, Point
import geopandas as gp
def convert_3D_2D(geometry):
    '''
    Takes a GeoSeries of 3D Multi/Polygons (has_z) and returns a list of 2D Multi/Polygons
    '''
    new_geo = []
    for p in geometry:
        if p.has_z:
            if p.geom_type == 'Polygon':
                lines = [xy[:2] for xy in list(p.exterior.coords)]
                new_p = Polygon(lines)
                new_geo.append(new_p)
            elif p.geom_type == 'MultiPolygon':
                new_multi_p = []
                for ap in p:
                    lines = [xy[:2] for xy in list(ap.exterior.coords)]
                    new_p = Polygon(lines)
                    new_multi_p.append(new_p)
                new_geo.append(MultiPolygon(new_multi_p))
    return new_geo

geodf_2d = gp.GeoDataFrame.from_file(shp_file) # plug_in your shapefile
geodf_2d.geometry = convert_3D_2D(geodf_2d.geometry) # new geodf with 2D geometry series

# geodf_2d.to_file(path + shapefile.shp, driver = 'ESRI Shapefile') will sore a shapefile with 2D shape types

Thanks for this snippet, it helped me a lot!

If you're using shapely, here's another helpful hack to convert a geometry object from 3D to 2D:

geom = shapely.wkb.loads(
        shapely.wkb.dumps(geom, output_dimension=2))

@koshy1123 Thanks for the hack. It looks much cleaner

@koshy1123 Thanks too! Is also quite fast 😀

shapely.wkb.loads(shapely.wkb.dumps(geom, output_dimension=2)) is cleaner, but I think convert_3D_2D(geometry) is much faster if I am not mistaken

I think https://gis.stackexchange.com/questions/67210/convert-3d-wkt-to-2d-shapely-geometry/220374 may be fastest

amazing function thanks a lot

You saved my project. Thanks a lot!!!

Really helped me out - thank you :)

Thanks above, output_dimensions=2 ftw!

import geopandas as gpd
from shapely import wkb

_drop_z = lambda geom: wkb.loads(wkb.dumps(geom, output_dimension=2))
df.geometry = df.geometry.transform(_drop_z)

%timeit drop_z(df.geometry)                # 42.9 s ± 270 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
%timeit drop_z_pygeos(df.geometry)         # 568 ms ± 12.7 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
%timeit drop_z_convert_3D_2D(df.geometry)  # 43.6 s ± 541 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

detail

• The convert_3D_2D above only works for (Multi)Polygons.
• drop_z_convert_3D_2D is a rewrite of convert_3D_2D for all shapely geometry objects.
• drop_z_pygeos requires pygeos to be installed. at least until shapely 2 is released.
• drop_z_shapely_for uses a method suggested: shapely/shapely#709
• drop_z_shapely_transform is to compare between the transform and for method for looping between rows/geoms. I did these to explain why I changed the suggested method. >10% improvement.
• I ran this on LineStrings of UK rivers with 186,255 rows.

import shapely 
import geopandas as gpd

df = gpd.read_file(<Your Data Here>)


def convert_3D_2D(geometry):
  ''' Drop Z coordiates from GeoSeries, returning list if (Multi)Polygons
  Taken from:  https://gist.github.com/rmania/8c88377a5c902dfbc134795a7af538d8

  Takes a GeoSeries of 3D Multi/Polygons (has_z) and returns a list of 2D Multi/Polygons
  '''
  new_geo = []
  for p in geometry:
    if p.has_z:
      if p.geom_type == 'Polygon':
        lines = [xy[:2] for xy in list(p.exterior.coords)]
        new_p = Polygon(lines)
        new_geo.append(new_p)
      elif p.geom_type == 'MultiPolygon':
        new_multi_p = []
        for ap in p:
          lines = [xy[:2] for xy in list(ap.exterior.coords)]
          new_p = Polygon(lines)
          new_multi_p.append(new_p)
        new_geo.append(MultiPolygon(new_multi_p))
  return new_geo


def drop_z_shapelywkb(ds):
  ''' Drop Z coordinates from GeoSeries, returns GeoSeries
  Using this method:  https://gist.github.com/rmania/8c88377a5c902dfbc134795a7af538d8?permalink_comment_id=2893099#gistcomment-2893099
  '''
  _drop_z_wkb = lambda geom:  shapely.wkb.loads(shapely.wkb.dumps(geom, output_dimension=2))
  return ds.transform(_drop_z_wkb)


def drop_z_pygeos(ds):
  ''' Drop Z coordinates from GeoSeries, returns GeoSeries
  Requires pygeos to be installed, and such I've added `import pygeos` to check.
  '''
  import pygeos
  return gpd.GeoSeries.from_wkb(ds.to_wkb(output_dimension=2))


def drop_z_convert_3D_2D(ds):
  ''' Drop Z coordinates from GeoSeries, returns GeoSeries
  A rewrite of convert_3D_2D but to fit the form of these other drop_z... functions.
  '''
  _get_coords = lambda g:  (
    g.coords
    if not g.geom_type == 'Polygon' else  # isinstance(g, Polygon)?
    g.exterior.coords
  )
  _drop_z = lambda geom:  type(geom)(
    (_drop_z(g) for g in geom.geoms)  # nest for iterables
    if hasattr(geom, '__iter__') else
    (coord[:2] for coord in _get_coords(geom))  # keep x,y
  )
  return gpd.GeoSeries(_drop_z(geom) for geom in ds)


_drop_z_shapely = lambda geom:  shapely.ops.transform(lambda *args: args[:2], geom)


def drop_z_shapely_for(ds):
  ''' Drop Z coordinates from GeoSeries, returns GeoSeries
  Using this method: https://github.com/shapely/shapely/issues/709#issuecomment-799977173
  '''
  return gpd.GeoSeries(_drop_z_shapely(geom) for geom in ds)


def drop_z_shapely_transform(ds):
  ''' Drop Z coordinates from GeoSeries, returns GeoSeries
  Same as drop_z_shapely_for but using the pandas transform operation instead.
  '''
  return ds.transform(lambda geom: _drop_z_shapely(geom))



a = convert_3D_2D(df.geometry)             # [] (empty list because I have only LineStrings)
b = drop_z_shapelywkb(df.geometry)         # GeoSeries, 2D geoms
c = drop_z_pygeos(df.geometry)             # GeoSeries, 2D geoms
d = drop_z_convert_3D_2D(df.geometry)      # GeoSeries, 2D geoms
e = drop_z_shapely_for(df.geometry)        # GeoSeries, 2D geoms
f = drop_z_shapely_transform(df.geometry)  # GeoSeries, 2D geoms
print( all([
  gpd.GeoSeries.all(b==c),
  gpd.GeoSeries.all(c==d),
  gpd.GeoSeries.all(d==e),
  gpd.GeoSeries.all(e==f),
  gpd.GeoSeries.all(f==b),
]) )  # True



%timeit convert_3D_2D(df.geometry)             # 19.7 s ± 430 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
%timeit drop_z_shapelywkb(df.geometry)         # 42.9 s ± 270 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
%timeit drop_z_pygeos(df.geometry)             # 568 ms ± 12.7 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
%timeit drop_z_convert_3D_2D(df.geometry)      # 43.6 s ± 541 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
%timeit drop_z_shapely_for(df.geometry)        # 45.6 s ± 310 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
%timeit drop_z_shapely_transform(df.geometry)  # 37.7 s ± 722 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

Thanks! it helped me get 2D Polygons from the KML file from Google Earth.

Thanks so much! This really helped me getting 2D polygons from Google Earth pro!