geopandas

Why is this not returning a count of number of points in each neighbourhoods (bounding box)? import geopandas as gpd def radius(points_neighbour, points_center, new_field_name, r): """ :param points_neighbour: :param points_center: :param new_field_name: new field_name attached to points_center :param r: radius around points_center :return: """ sindex = points_neighbour.sindex pts_in_neighbour = [] for i, pt_center in points_center.iterrows(): nearest_index = list(sindex.intersection((pt_center.LATITUDE-r, pt_center.LONGITUDE-r, pt_center.LATITUDE+r, pt_center.LONGITUDE+r))) pts_in_this

Given the following GeoDataFrame: h=pd.DataFrame({'zip':[19152,19047], 'Lat':[40.058841,40.202162], 'Lon':[-75.042164,-74.924594]}) crs='none' geometry = [Point(xy) for xy in zip(h.Lon, h.Lat)] hg = GeoDataFrame(h, crs=crs, geometry=geometry) hg Lat Lon zip geometry 0 40.058841 -75.042164 19152 POINT (-75.042164 40.058841) 1 40.202162 -74.924594 19047 POINT (-74.924594 40.202162) I need to set the CRS as I did with another GeoDataFrame (like this): c=c.to_crs("+init=epsg:3857 +ellps=GRS80 +datum=GGRS87 +units=mi +no_defs") I've tried this: crs={'init': 'epsg:3857'} and this: hg=hg.to_crs("

I have small csv that has 6 coordinates from Birmingham England. I read the csv with pandas then transformed it into GeoPandas DataFrame changing my latitude and longitude columns with Shapely Points. I am now trying to plot my GeoDataframe and all I can see are the points. How do I get the Birmingham map represented as well? A good documentation source on GeoPandas would be strongly appreciated too. from shapely.geometry import Point import geopandas as gpd import pandas as pd df = pd.read_csv('SiteLocation.csv') df['Coordinates'] = list(zip(df.LONG, df.LAT)) df['Coordinates'] = df[

Given the shape file available here : I'd like to plot the specified set of counties below with custom colors; 'blue' for Wayne and Washtenaw counties and 'grey' for the others. import geopandas as gpd import matplotlib.pyplot as plt %matplotlib inline shpfile=<Path to unzipped .shp file referenced and linked above> c=gpd.read_file(shpfile) c=c.loc[c['GEOID'].isin(['26161','26093','26049','26091','26075','26125','26163','26099','26115','26065'])] c.plot() I'd prefer to assign the colors as a column in the data frame first, then invoke them when plotting somehow. Is this possible? UPDATE I've

I'm looking to do the equivalent of the ArcPy Generate Near Table using Geopandas / Shapely. I'm very new to Geopandas and Shapely and have developed a methodology that works, but I'm wondering if there is a more efficient way of doing it. I have two point file datasets - Census Block Centroids and restaurants. I'm looking to find, for each Census Block centroid, the distance to it's closest restaurant. There are no restrictions in terms of same restaurant being the closest restaurant for multiple blocks. The reason this becomes a bit more complicated for me is because the Geopandas Distance