您如何重新投影 geopandas GeoSeries？

Question

EDIT: Answer: you don't.

Original question:

I just noticed, that geopandas GeoDataFrame allows for inplace reprojection:

In [1]: import geopandas as gpd
In [2]: import shapely.geometry as sg
In [3]: data = {'geometry': [sg.Point(9,53), sg.Point(10,53.5)]}

In [4]: gdf = gpd.GeoDataFrame(data, crs='epsg:4326')
In [5]: gdf
Out[5]: 
                    geometry
0   POINT (9.00000 53.00000)
1  POINT (10.00000 53.50000)

In [6]: gdf.to_crs('epsg:3395', inplace=True) #No problem
In [7]: gdf
Out[7]: 
                          geometry
0  POINT (1001875.417 6948849.385)
1  POINT (1113194.908 7041652.839)

...but GeoSeries does not:

In [8]: gs = gpd.GeoSeries(data['geometry'], crs='epsg:4326')
In [9]: gs
Out[9]: 
0     POINT (9.00000 53.00000)
1    POINT (10.00000 53.50000)
dtype: geometry

In [10]: gs.to_crs('epsg:3395', inplace=True) #Problem
TypeError: to_crs() got an unexpected keyword argument 'inplace'

In [11]: gs.to_crs('epsg:3395')
Out[11]: 
0    POINT (1001875.417 6948849.385)
1    POINT (1113194.908 7041652.839)
dtype: geometry

It is complicating things a bit in my app, as I was hoping to write a function that takes GeoDataframes and GeoSeries as *args and do a reprojection on each of them, without needing to return and re-assign the objects to their variables.

It is not a huge deal. I was mainly just wondering, why this is the case, as many other methods (like .dropna() ) do allow an inplace argument in both the GeoDataFrame and the GeoSeries objects. So why not this specific method? Is it an oversight? Or is there a good reason for it that I'm unaware of? Or am I just using it wrong?

Many thanks!

---

PS: it's beyond the scope of this question, for those wondering about the use case: having an in-place version of a method is especially valuable when there are multiple variables pointing to a given object, and so there is a danger of some of these pointing to an 'old' (ie, not reprojected) version of the object, leading to errors down the line. Here is a scenario:

gdf = self._geodataframe = gpd.GeoDataFrame(...) #saving dataframe as class variable
gdf.to_crs(..., inplace=True) # self._geodataframe is also reprojected

gs = self._geoseries = gpd.GeoSeries(...) #saving series as class variable
gs = gs.to_crs(...) #self._geoseries still has the original crs

Answer 1

GeoDataFrame to_crs is using GeoSeries to_crs to do the transformation, while GeoSeries.to_crs() is reprojecting geometries using apply . Apply does not allow in place transformation and no one actually tried to implement in place option for that manually.

This is the part of the code responsible for transformation:

transformer = Transformer.from_crs(self.crs, crs, always_xy=True)
result = self.apply(lambda geom: transform(transformer.transform, geom))
result.__class__ = GeoSeries
result.crs = crs
result._invalidate_sindex()
return result

I believe that there is no reason for not supporting it, but I might be as well wrong. No one probably thought of implementing it :). Feel free to open issue or make a PR on GitHub .