我试图在shapefile的多边形中找到一个点。
我需要编写一个循环,它可以遍历多边形并返回该点所在的多边形的索引。
如何编写循环以找出该点所在的多边形?
这是我到目前为止所写的内容:
import pandas as pd
import pylab as pl
import os
import zipfile
import geopandas as gp
import shapely
%pylab inline
# Read in the shapefile
ct_shape = gp.read_file(path)
# Segmented the file so it only contains Brooklyn data & set projection
ct_latlon = ct_shape[ct_shape.BoroName == 'Brooklyn']
ct_latlon = ct_latlon.to_crs({'init': 'epsg:4326'})
ct_latlon.head()
# Dataframe image
[Head of the dataframe image][1]: https://i.stack.imgur.com/xAl6m.png
# Created a point that I need to look for within the shapefile
CUSP = shapely.geometry.Point(40.693217, -73.986403)
输出可能是这样的:'3001100'(正确多边形的BCTCB2010)
答案 0 :(得分:1)
我在一行代码中解决了这个问题。没有必要的循环。
发布可能感兴趣的其他人:
# Setting the coordinates for the point
CUSP = shapely.geometry.Point((-73.986403, 40.693217,)) # Longitude & Latitude
# Printing a list of the coords to ensure iterable
list(CUSP.coords)
# Searching for the geometry that intersects the point. Returning the index for the appropriate polygon.
index = ct_latlon[ct_latlon.geometry.intersects(CUSP)].BCTCB2010.values[0]
答案 1 :(得分:0)
我会使用GeoDataFrame sjoin
。
下面是一个简短的示例,我有一个城市对应巴黎坐标,我会尝试将其与国家/地区GeoDataFrame中的国家/地区匹配。
import geopandas as gpd
from shapely.geometry.point import Point
# load a countries GeoDataFrame given in GeoPandas
countries = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))\
.rename(columns={"name":"country_name"})
#making a GeoDataFrame with your city
paris = Point( 2.35, 48.85)
cities = gpd.GeoDataFrame([{"city" : "Paris", "geometry":paris} ])
In [33]: cities
Out[33]:
city geometry
0 Paris POINT (2.35 48.85)
#now we left_join cities and countries GeoDataFrames with the operator "within"
merging = gpd.sjoin(cities, countries, how="left", op="within")
In [34]: merging
Out[34]:
city geometry index_right continent gdp_md_est iso_a3 \
0 Paris POINT (2.35 48.85) 55 Europe 2128000.0 FRA
country_name pop_est
0 France 64057792.0
我们发现在法国Point
GeoDataFrame的索引55处的国家/地区多边形中找到了巴黎countries
:
In [32]: countries.loc[55]
Out[32]:
continent Europe
gdp_md_est 2.128e+06
geometry (POLYGON ((-52.55642473001839 2.50470530843705...
iso_a3 FRA
country_name France
pop_est 6.40578e+07
Name: 55, dtype: object
因此,如果你有一个点列表而不是一个点,你只需要创建一个更大的cities
GeoDataFrame。
答案 2 :(得分:0)
除了您接受的答案之外,还有一些可能感兴趣的东西:您还可以利用geopandas的内置Rtree空间索引来快速交叉/查询。
spatial_index = gdf.sindex
possible_matches_index = list(spatial_index.intersection(polygon.bounds))
possible_matches = gdf.iloc[possible_matches_index]
precise_matches = possible_matches[possible_matches.intersects(polygon)]
来自this tutorial。该示例返回哪些点与单个多边形相交,但您可以轻松地将其调整为具有多个多边形的单个点的示例。