GeoPandas AttributeError – Troubleshooting ‘NoneType’ Object Has No Attribute ‘Bounds’

geopandaspythonspatial-join

I have the following geodataframes, corresponding to a regular grid:

        id   grid_id    geometry
0       48         0    (POLYGON ((2.052457758079306 41.42493869117656...
1       49         1    (POLYGON ((2.052470852112577 41.42403805731954...
2       215        2    (POLYGON ((2.053641274433816 41.42584917461342...
3       216        3    (POLYGON ((2.053654352531821 41.42494854059127...
4       217        4    (POLYGON ((2.053667430035439 41.42404790642426...

and a points geodataframe:

    id_act  geometry
0   4001    POINT (2.183026563657264 41.37459702541483)
1   4003    POINT (2.183012216695291 41.37471411724238)
2   4003    POINT (2.183128113845906 41.37472901746361)
3   3002    POINT (2.182820482338962 41.37482095671629)
4   4003    POINT (2.182945418252172 41.37482221760939)

I'm merging the two dataframes through a spatial join:

BCN_id_grid = gpd.sjoin(gdf, grid, how="inner", op='intersects')

but it returns the following AttributeError:

AttributeError: 'NoneType' object has no attribute 'bounds'

the point is that when I call the function:

grid.bounds

it yields:

        minx         miny       maxx         maxy
0   2.052458    41.424038   2.053667    41.424949
1   2.052471    41.423137   2.053681    41.424048
2   2.053641    41.424949   2.054851    41.425859
3   2.053654    41.424048   2.054864    41.424958
4   2.053667    41.423147   2.054877    41.424058
5   2.053681    41.422247   2.054890    41.423157

calling both type(gdf.geomtry[0]) or type(grid.geomtry[0]) gives:

shapely.geometry.point.Point
shapely.geometry.multipolygon.MultiPolygon

respectively.

Does anyone know where is the mistake?

Best Answer

I've solved trying points.bounds that yields the same attribute error message:

'NoneType' object has no attribute 'bounds'

So that means that the mistake was in the points geodataframe.

I ran the following script to slice the valid geometries:

points_fix = points.loc[points.is_valid]

It discards just about 1,000 points out of the original geodataframe, composed by more than 78,000 features, which works statistically for my purpose.

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