如何在熊猫数据框中选择地理区域内的对象

Question

我正在尝试从pandas数据框中选择区域内的对象，该数据框中包含项目ID和纬度对的列表。是否有选择方法？ 我认为这类似于该SO问题，但使用PANDAS而不是SQL

Selecting geographical points within area

这是我的表格保存在 locations.csv

中

ID, LAT, LON
001,35.00,-75.00
002,35.01,-80.00 
...
999,25.76,-64.00

我可以加载数据框，然后选择一个矩形区域：

import pandas as pd
df = pd.read_csv('locations.csv', delimiter=',')
lat_max = 32.323496
lat_min = 25.712767
lon_max = -72.863358
lon_min = -74.729456
small_df = df[df['LAT'] > lat_min][df['LAT'] < lat_max][df['LON'] < lon_max][df['LON'] > lon_min]

如何选择不规则区域内的对象？

如何构造数据框选择命令？

我可以构建一个lambda函数，该函数将在该区域内为LAT和LON生成True值，但是我不确定如何将其与pandas数据框一起使用。

Answer 1

下面的工作代码执行的在区域内选择点的过程始于创建2个地理数据框。第一个包含多边形，第二个包含与第一个关联的所有点spatial join。使用空间连接运算符within可以选择位于多边形内的点。操作的结果也是一个地理数据框，它仅包含落在多边形区域内的所需点。

locations.csv的内容； 6行，带列标题。 注意：第一行中没有空格。

ID,LAT,LON
1, 15.1, 10.0
2, 15.2, 15.1
3, 15.3, 20.2
4, 15.4, 25.3
5, 15.5, 30.4

代码：

import pandas as pd
import geopandas as gpd
from shapely import wkt
from shapely.geometry import Point, Polygon
from shapely.wkt import loads

# Create a geo-dataframe `polygon_df` having 1 row of polygon
# This polygon will be used to select points in a geodataframe
d = {'poly_id':[1], 'wkt':['POLYGON ((30 10, 40 40, 20 40, 10 20, 30 10))']}
df = pd.DataFrame( data=d )
geometry = [loads(pgon) for pgon in df.wkt]
polygon_df = gpd.GeoDataFrame(df, \
                   crs={'init': 'epsg:4326'}, \
                   geometry=geometry)

# One can plot this polygon with the command:
# polygon_df.plot()

# Read the file with `pandas`
locs = pd.read_csv('locations.csv', sep=',')

# Making it a geo-dataframe with new name: `geo_locs`
geo_locs = gpd.GeoDataFrame(locs, crs={'init': 'epsg:4326'})
locs_geom = [Point(xy) for xy in zip(geo_locs.LON, geo_locs.LAT)]
geo_locs['wkt'] = geo_locs.apply( lambda x: Point(x.LON, x.LAT), axis=1 )
geo_locs = gpd.GeoDataFrame(geo_locs, crs={'init': 'epsg:4326'}, \
    geometry=geo_locs['wkt'])

# Do a spatial join of `point` within `polygon`, get the result in `pts_in_poly` GeodataFrame.
pts_in_poly = gpd.sjoin(geo_locs, polygon_df, op='within', how='inner')

# Print the ID of the points that fall within the polygon.
print(pts_in_poly.ID)

# The output will be:
#2    3
#3    4
#4    5
#Name: ID, dtype: int64

# Plot the polygon and all the points.
ax1 = polygon_df.plot(color='lightgray', zorder=1)
geo_locs.plot(ax=ax1, zorder=5, color="red")

输出图：

在图中，ID为3、4和5的点落在多边形内。