How to join point with polygon in geopandas-CodePudding

I have the polygon combination of lat-long1,lat2-long2 ..... and point like Lat - Long .

I have used GeoPandas library to get the result if there is any point is exist within polygon.

Sample Data of Polygon saved in csv file:

POLYGON((28.56056 77.36535,28.564635293716776 77.3675137204626,28.56871055311656 77.36967760850214,28.572785778190855 77.3718416641586,28.576860968931193 77.37400588747194,28.580936125329096 77.3761702784821,28.585011247376094 77.37833483722912,28.58908633506372 77.38049956375293,28.593161388383457 77.38266445809356,28.59723640732686 77.38482952029099,28.60131139188541 77.38699475038526,28.605386342050664 77.38916014841635,28.60946125781409 77.39132571442434,28.613536139167238 77.39349144844923,28.61761098610158 77.39565735053108,28.62168579860863 77.39782342070995,28.62576057667991 77.39998965902589,28.62983532030691 77.402156065519,28.633910029481108 77.40432264022931,28.637984704194054 77.40648938319696,28.642059344437207 77.408656294462,28.64068221074683 77.41187044231611,28.63920739580329 77.41502778244606,28.63763670052024 77.41812446187686,28.635972042808007 77.42115670220443,28.634215455216115 77.42412080422613,28.63236908243526 77.42701315247152,28.630435178662026 77.42983021962735,28.628416104829583 77.43256857085188,28.626314325707924 77.43522486797251,28.624132406877322 77.437795873562,28.621873011578572 77.44027845488824,28.619538897444272 77.4426695877325,28.617132913115164 77.44496636007166,28.614657994745563 77.44716597562005,28.612117162402576 77.44926575722634,28.609513516363293 77.45126315012166,28.606850233314923 77.45315572501488,28.604130562462267 77.45494118103147,28.60135782154758 77.45661734849246,28.598535392787774 77.45818219153013,28.595666718733966 77.45963381053753,28.592755298058414 77.46097044444889,28.589804681274302 77.46219047284835,28.586818466393503 77.46329241790465,28.583800294527727 77.46427494612952,28.58075384543836 77.46513686995802,28.57768283304089 77.46587714914885,28.574591000868892 77.4664948920035,28.571482117503592 77.46698935640259,28.568359971974488 77.46735995065883,28.565228369136484 77.46760623418534,28.56209112502966 77.4677279179792,28.558952062226695 77.4677248649196,28.55581500517431 77.46759708988064,28.552683775533943 77.46734475965891,28.552683775533943 77.46734475965891,28.553079397193876 77.4622453846313,28.553474828308865 77.45714597129259,28.55387006887434 77.4520465196603,28.554265118885752 77.44694702975198,28.554659978338513 77.4418475015852,28.555054647228083 77.43674793517746,28.555449125549913 77.43164833054634,28.555843413299442 77.42654868770937,28.55623751047213 77.42144900668411,28.556631417063407 77.41634928748812,28.55702513306874 77.41124953013893,28.55741865848359 77.40614973465412,28.557811993303396 77.40104990105122,28.55820513752363 77.39595002934782,28.558598091139757 77.39085011956145,28.558990854147225 77.38575017170969,28.559383426541523 77.3806501858101,28.559775808318093 77.37555016188024,28.560167999472434 77.37045009993768,28.56056 77.36535))

and second dataset is for LAT and LONG as 28.56282, 77.36824 respectively saved in csv file .

I have used below Python code to join both data set based on condition if point exist within polygon. like below

import pandas as pd
import shapely.geometry
from shapely.geometry import Point
import geopandas as gpd
site_df = pd.read_csv (r'lat_long_file.csv') # load lat and long file
site_df['geometry'] = pd.DataFrame(site_df).apply(lambda x: Point(x.LAT,x.LONG), axis='columns') # convert lat and long to point

gdf = gpd.GeoDataFrame(site_df, geometry = site_df.geometry,crs='EPSG:4326') #creating geo pandas data frame for point

from shapely import wkt
polygon_df = pd.read_csv (r'polygon_csv_file') #reading polygon sample raw string file
polygon_df['geometry'] = pd.DataFrame(polygon_df).apply(lambda row: shapely.wkt.loads(row.polygon), axis='columns') #converting string polygon to geometory

gd_polygon = gpd.GeoDataFrame(polygon_df, geometry = polygon_df.geometry,crs='EPSG:4326') #create geopandas dataframe


import shapely.speedups
shapely.speedups.enable() # this makes some spatial queries run faster

join_data = gpd.sjoin(gdf, gd_polygon, how="inner", op="within") //actual join condition

But that query does not retun anything . But point is exist within polygon. as we can see in below diagram

Green Location marker is point Lat and long which is exist within polygon.

CodePudding user response：

your sample data is unusable as it's an image
have sourced a polygon - a county boundary in UK
constructed a geopandas data frame of a point that is within this county
have used plotly to demonstrate visually the data
have used your code fragment gpd.sjoin(gdf, gd_polygon, how="inner", op="within") to do spatial join and it correctly joins point to polygon

import requests, json
import geopandas as gpd
import plotly.express as px
import shapely.geometry

# fmt: off
# get a polygon and construct a point
res = requests.get("https://opendata.arcgis.com/datasets/69dc11c7386943b4ad8893c45648b1e1_0.geojson")
gd_polygon = gpd.GeoDataFrame.from_features(res.json()).loc[lambda d: d["LAD20NM"].str.contains("Hereford")]
gdf = gpd.GeoDataFrame(geometry=gd_polygon.loc[:,["LONG","LAT"]].apply(shapely.geometry.Point, axis=1)).reset_index(drop=True)
# fmt: on

# plot to show point is within polygon
px.scatter_mapbox(gd_polygon, lon="LONG", lat="LAT").update_traces(
    name="gd_polygon"
).add_traces(
    px.scatter_mapbox(gdf, lat=gdf2.geometry.y, lon=gdf2.geometry.x)
    .update_traces(name="gdf", marker_color="red")
    .data
).update_traces(
    showlegend=True
).update_layout(
    mapbox={
        "style": "carto-positron",
        "layers": [
            {"source": json.loads(gd_polygon.geometry.to_json()), "type": "line"}
        ],
    }
).show()

# spatial join, all good :-)
gpd.sjoin(gdf, gd_polygon, how="inner", op="within")

output

spatial join has worked, point is within polygon | | geometry | index_right | OBJECTID | LAD20CD | LAD20NM | LAD20NMW | BNG_E | BNG_N | LONG | LAT | Shape__Area | Shape__Length | |---:|:---------------------------|--------------:|-----------:|:----------|:-------------------------|:-----------|--------:|--------:|---------:|--------:|--------------:|----------------:| | 0 | POINT (-2.73931 52.081539) | 18 | 19 | E06000019 | Herefordshire, County of | | 349434 | 242834 | -2.73931 | 52.0815 | 2.18054e 09 | 285427 |

CodePudding user response：

I would check the axis order - WKT usually interpreted as longitude first, latitude second order, while the point you construct uses latitude:longitude order.

You can try removing the CRS identifier to see if it changes the result.

Also see https://gis.stackexchange.com/questions/376751/shapely-flips-lat-long-coordinate and https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6