Error: float() argument must be a string or a number, not 'Polygon' when trying to find points in polygons
I have a list of named polygons:
import pandas as pd
import geopandas as gp
from shapely.geometry import Polygon
from shapely.geometry import Point
import matplotlib.path as mpltPath
df = gp.GeoDataFrame([['a', Polygon([(1, 0), (1, 1), (2,2), (1,2)])],
['b', Polygon([(1, 1), (2,2), (3,1)])]],
columns = ['name','geometry'])
df = gp.GeoDataFrame(df, geometry = 'geometry')
and a list of points:
points = gp.GeoDataFrame( [['box', Point(1.5, 1.75)],
['cone', Point(3.0,2.0)],
['triangle', Point(2.5,1.25)]],
columns=['id', 'geometry'],
geometry='geometry')
I am trying to find out what points are in what polygons and add a column to the point dataframe with 'True' or 'False'
I've previously been shown the methods here which show some ways of quickly doing this and have got the script:
point = points['geometry']
path = mpltPath.Path(df['geometry'])
points['inside'] = path.contains_points(point)
but I get the error: float() argument must be a string or a number, not 'Polygon'
How do I fix this?
Alternatively I have been trying this method:
points['inside'] =
for geo1 in df['geometry']:
for geo2 in points['geometry']:
if geo1.contains(geo2):
points['inside'].append('True')
however here I also get an error: Length of values des not match length of index
Any help with either of these would be greatly appreciated!
python python-3.x pandas matplotlib
asked Nov 21 '18 at 14:17
tom91tom91
16611
add a comment |
I have a list of named polygons:
import pandas as pd
import geopandas as gp
from shapely.geometry import Polygon
from shapely.geometry import Point
import matplotlib.path as mpltPath
df = gp.GeoDataFrame([['a', Polygon([(1, 0), (1, 1), (2,2), (1,2)])],
['b', Polygon([(1, 1), (2,2), (3,1)])]],
columns = ['name','geometry'])
df = gp.GeoDataFrame(df, geometry = 'geometry')
and a list of points:
points = gp.GeoDataFrame( [['box', Point(1.5, 1.75)],
['cone', Point(3.0,2.0)],
['triangle', Point(2.5,1.25)]],
columns=['id', 'geometry'],
geometry='geometry')
I am trying to find out what points are in what polygons and add a column to the point dataframe with 'True' or 'False'
I've previously been shown the methods here which show some ways of quickly doing this and have got the script:
point = points['geometry']
path = mpltPath.Path(df['geometry'])
points['inside'] = path.contains_points(point)
but I get the error: float() argument must be a string or a number, not 'Polygon'
How do I fix this?
Alternatively I have been trying this method:
points['inside'] =
for geo1 in df['geometry']:
for geo2 in points['geometry']:
if geo1.contains(geo2):
points['inside'].append('True')
however here I also get an error: Length of values des not match length of index
Any help with either of these would be greatly appreciated!
python python-3.x pandas matplotlib
asked Nov 21 '18 at 14:17
tom91tom91
16611
add a comment |
I have a list of named polygons:
import pandas as pd
import geopandas as gp
from shapely.geometry import Polygon
from shapely.geometry import Point
import matplotlib.path as mpltPath
df = gp.GeoDataFrame([['a', Polygon([(1, 0), (1, 1), (2,2), (1,2)])],
['b', Polygon([(1, 1), (2,2), (3,1)])]],
columns = ['name','geometry'])
df = gp.GeoDataFrame(df, geometry = 'geometry')
and a list of points:
points = gp.GeoDataFrame( [['box', Point(1.5, 1.75)],
['cone', Point(3.0,2.0)],
['triangle', Point(2.5,1.25)]],
columns=['id', 'geometry'],
geometry='geometry')
I am trying to find out what points are in what polygons and add a column to the point dataframe with 'True' or 'False'
I've previously been shown the methods here which show some ways of quickly doing this and have got the script:
point = points['geometry']
path = mpltPath.Path(df['geometry'])
points['inside'] = path.contains_points(point)
but I get the error: float() argument must be a string or a number, not 'Polygon'
How do I fix this?
Alternatively I have been trying this method:
points['inside'] =
for geo1 in df['geometry']:
for geo2 in points['geometry']:
if geo1.contains(geo2):
points['inside'].append('True')
however here I also get an error: Length of values des not match length of index
Any help with either of these would be greatly appreciated!
python python-3.x pandas matplotlib
asked Nov 21 '18 at 14:17
tom91tom91
16611
I have a list of named polygons:
import pandas as pd
import geopandas as gp
from shapely.geometry import Polygon
from shapely.geometry import Point
import matplotlib.path as mpltPath
df = gp.GeoDataFrame([['a', Polygon([(1, 0), (1, 1), (2,2), (1,2)])],
['b', Polygon([(1, 1), (2,2), (3,1)])]],
columns = ['name','geometry'])
df = gp.GeoDataFrame(df, geometry = 'geometry')
and a list of points:
points = gp.GeoDataFrame( [['box', Point(1.5, 1.75)],
['cone', Point(3.0,2.0)],
['triangle', Point(2.5,1.25)]],
columns=['id', 'geometry'],
geometry='geometry')
I am trying to find out what points are in what polygons and add a column to the point dataframe with 'True' or 'False'
I've previously been shown the methods here which show some ways of quickly doing this and have got the script:
point = points['geometry']
path = mpltPath.Path(df['geometry'])
points['inside'] = path.contains_points(point)
but I get the error: float() argument must be a string or a number, not 'Polygon'
How do I fix this?
Alternatively I have been trying this method:
points['inside'] =
for geo1 in df['geometry']:
for geo2 in points['geometry']:
if geo1.contains(geo2):
points['inside'].append('True')
however here I also get an error: Length of values des not match length of index
Any help with either of these would be greatly appreciated!
python python-3.x pandas matplotlib
python python-3.x pandas matplotlib
asked Nov 21 '18 at 14:17
tom91tom91
16611
asked Nov 21 '18 at 14:17
tom91tom91
16611
asked Nov 21 '18 at 14:17
tom91tom91
16611
asked Nov 21 '18 at 14:17
tom91tom91
16611
asked Nov 21 '18 at 14:17
tom91tom91
16611
16611
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
I didn't get the "true/false column", but this should do the job:
points.apply(lambda row: (row['id'], list(map(lambda e: e[0], list(filter(lambda p: p[1].contains(row['geometry']), df.values))))), axis=1)
For each point you get the polygons that contains it, output:
0 (box, [a])
1 (cone, )
2 (triangle, [b])
dtype: object
answered Nov 21 '18 at 15:18
Federico PucciFederico Pucci
513
Thank you for this. The 'True, False column' would basically be a column that is added to the points dataframe that would have true next to a point if it fell within either polygon a or b. This is because in the actual data set I have 1000s of points to check within 100s of polygons and don't want to be adding a column manually
– tom91
Nov 21 '18 at 15:37
1
Oh, got it. Then this:points['inside'] = points.geometry.map(lambda x: True if reduce(lambda a,b: a+b, list(map(lambda p: p.contains(x), df.geometry.values))) else False)
– Federico Pucci
Nov 21 '18 at 15:49
YES! Thats got it, thank you so much!
– tom91
Nov 21 '18 at 16:07
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
I didn't get the "true/false column", but this should do the job:
points.apply(lambda row: (row['id'], list(map(lambda e: e[0], list(filter(lambda p: p[1].contains(row['geometry']), df.values))))), axis=1)
For each point you get the polygons that contains it, output:
0 (box, [a])
1 (cone, )
2 (triangle, [b])
dtype: object
answered Nov 21 '18 at 15:18
Federico PucciFederico Pucci
513
Thank you for this. The 'True, False column' would basically be a column that is added to the points dataframe that would have true next to a point if it fell within either polygon a or b. This is because in the actual data set I have 1000s of points to check within 100s of polygons and don't want to be adding a column manually
– tom91
Nov 21 '18 at 15:37
1
Oh, got it. Then this:points['inside'] = points.geometry.map(lambda x: True if reduce(lambda a,b: a+b, list(map(lambda p: p.contains(x), df.geometry.values))) else False)
– Federico Pucci
Nov 21 '18 at 15:49
YES! Thats got it, thank you so much!
– tom91
Nov 21 '18 at 16:07
add a comment |
I didn't get the "true/false column", but this should do the job:
points.apply(lambda row: (row['id'], list(map(lambda e: e[0], list(filter(lambda p: p[1].contains(row['geometry']), df.values))))), axis=1)
For each point you get the polygons that contains it, output:
0 (box, [a])
1 (cone, )
2 (triangle, [b])
dtype: object
answered Nov 21 '18 at 15:18
Federico PucciFederico Pucci
513
Thank you for this. The 'True, False column' would basically be a column that is added to the points dataframe that would have true next to a point if it fell within either polygon a or b. This is because in the actual data set I have 1000s of points to check within 100s of polygons and don't want to be adding a column manually
– tom91
Nov 21 '18 at 15:37
1
Oh, got it. Then this:points['inside'] = points.geometry.map(lambda x: True if reduce(lambda a,b: a+b, list(map(lambda p: p.contains(x), df.geometry.values))) else False)
– Federico Pucci
Nov 21 '18 at 15:49
YES! Thats got it, thank you so much!
– tom91
Nov 21 '18 at 16:07
add a comment |
I didn't get the "true/false column", but this should do the job:
points.apply(lambda row: (row['id'], list(map(lambda e: e[0], list(filter(lambda p: p[1].contains(row['geometry']), df.values))))), axis=1)
For each point you get the polygons that contains it, output:
0 (box, [a])
1 (cone, )
2 (triangle, [b])
dtype: object
answered Nov 21 '18 at 15:18
Federico PucciFederico Pucci
513
I didn't get the "true/false column", but this should do the job:
points.apply(lambda row: (row['id'], list(map(lambda e: e[0], list(filter(lambda p: p[1].contains(row['geometry']), df.values))))), axis=1)
For each point you get the polygons that contains it, output:
0 (box, [a])
1 (cone, )
2 (triangle, [b])
dtype: object
answered Nov 21 '18 at 15:18
Federico PucciFederico Pucci
513
answered Nov 21 '18 at 15:18
Federico PucciFederico Pucci
513
answered Nov 21 '18 at 15:18
Federico PucciFederico Pucci
513
answered Nov 21 '18 at 15:18
Federico PucciFederico Pucci
513
513
Thank you for this. The 'True, False column' would basically be a column that is added to the points dataframe that would have true next to a point if it fell within either polygon a or b. This is because in the actual data set I have 1000s of points to check within 100s of polygons and don't want to be adding a column manually
– tom91
Nov 21 '18 at 15:37
1
Oh, got it. Then this:points['inside'] = points.geometry.map(lambda x: True if reduce(lambda a,b: a+b, list(map(lambda p: p.contains(x), df.geometry.values))) else False)
– Federico Pucci
Nov 21 '18 at 15:49
YES! Thats got it, thank you so much!
– tom91
Nov 21 '18 at 16:07
add a comment |
Thank you for this. The 'True, False column' would basically be a column that is added to the points dataframe that would have true next to a point if it fell within either polygon a or b. This is because in the actual data set I have 1000s of points to check within 100s of polygons and don't want to be adding a column manually
– tom91
Nov 21 '18 at 15:37
1
Oh, got it. Then this:points['inside'] = points.geometry.map(lambda x: True if reduce(lambda a,b: a+b, list(map(lambda p: p.contains(x), df.geometry.values))) else False)
– Federico Pucci
Nov 21 '18 at 15:49
YES! Thats got it, thank you so much!
– tom91
Nov 21 '18 at 16:07
Thank you for this. The 'True, False column' would basically be a column that is added to the points dataframe that would have true next to a point if it fell within either polygon a or b. This is because in the actual data set I have 1000s of points to check within 100s of polygons and don't want to be adding a column manually
– tom91
Nov 21 '18 at 15:37
Thank you for this. The 'True, False column' would basically be a column that is added to the points dataframe that would have true next to a point if it fell within either polygon a or b. This is because in the actual data set I have 1000s of points to check within 100s of polygons and don't want to be adding a column manually
– tom91
Nov 21 '18 at 15:37
1
1
Oh, got it. Then this:
points['inside'] = points.geometry.map(lambda x: True if reduce(lambda a,b: a+b, list(map(lambda p: p.contains(x), df.geometry.values))) else False)– Federico Pucci
Nov 21 '18 at 15:49
Oh, got it. Then this:
points['inside'] = points.geometry.map(lambda x: True if reduce(lambda a,b: a+b, list(map(lambda p: p.contains(x), df.geometry.values))) else False)– Federico Pucci
Nov 21 '18 at 15:49
YES! Thats got it, thank you so much!
– tom91
Nov 21 '18 at 16:07
YES! Thats got it, thank you so much!
– tom91
Nov 21 '18 at 16:07
add a comment |
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