Find Polygon Coordinates from Shapefile using Python Geopandas

Question

ERROR:

TypeError: 'LineString' object is not iterable

I am trying to find the bottom right corner of the Polygon in this .shp file. This .shp file is a square but other files may be a rectangle/triangle.

I want to use Geopandas and apparently I can obtain this using the read_file() method. I am quite new to SHPs and I have the .shx, .dpf files however when I enter just the .shp in this method, I am not able to loop through the polygon coordinates.

Here is my code - I want to capture the bottom right corner in a variable, currently all_cords will capture all of them, so I need to find a way to get over this error and then capture the bottom right corner,

import geopandas as gpd
import numpy as np
shapepath = r"FieldAlyticsCanada_WesternSales_AlexOlson_CouttsAgro2022_CouttsAgro_7-29-23.shp"
 
df = gpd.read_file(shapepath)
g = [i for i in df.geometry]

all_coords = []
for b in g[0].boundary:  # error happens here
    coords = np.dstack(b.coords.xy).tolist()
    all_coords.append(*coords)

print(all_coords)

You're way overcomplicating the beauty of geopandas. Try printing out some things like: df.boundary, df.x, df.y, df.bounds to get a feel for what it's doing. Loops are basically never the best option when it comes to pandas, at worst you can use .apply() for scenarios where a built in function doesn't cut it. — BeRT2me
– BeRT2me, Commented May 4, 2022 at 9:21

Rob Raymond · Accepted Answer · 2022-05-17 14:05:13Z

You can use much simpler concepts

bounds provides tuple (minx, miny, maxx, maxy)
shapely.ops.nearest_points() can be used to find nearest point to maxx, miny point

import geopandas as gpd
import numpy as np
import shapely.geometry
import shapely.ops
import pandas as pd

shapepath = (
    r"FieldAlyticsCanada_WesternSales_AlexOlson_CouttsAgro2022_CouttsAgro_7-29-23.shp"
)
shapepath = gpd.datasets.get_path("naturalearth_lowres")


df = gpd.read_file(shapepath)

# find point closest to bottom right corner of geometry (minx, maxy)
df["nearest"] = df["geometry"].apply(
    lambda g: shapely.ops.nearest_points(
        g,
        shapely.geometry.Point(
            g.bounds[2], g.bounds[1]
        ),
    )[0]
)

# visualize outcome...
gdfn = gpd.GeoDataFrame(df["name"], geometry=df["nearest"], crs=df.crs)
m = df.drop(columns=["nearest"]).explore()
gdfn.explore(m=m, color="red")

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