folium：使用底图和 pandas 创建等值线图 map

Question

I am using folium to create a choropleth map of Los Angeles showing "frequency"(mydata) based on zipcode. I am following the documentation. However, I'm not sure what to write for key_on and always shows ValueError: Cannot render objects with any missing geometries. I am using the zipcode geojson from county of la open data ( https://data.lacounty.gov/Geospatial/ZIP-Codes/65v5-jw9f ). My csv file look like this:

zipcode_frequency.csv

According to tutorial of Choropleth maps( https://python-visualization.github.io/folium/quickstart.html#GeoJSON/TopoJSON-Overlays ), I wrote:

m = folium.Map([34.2012,-118.4662], zoom_start=10)
folium.GeoJson('ZIP Codes.geojson').add_to(m)
m
zipcode_data = pd.read_csv('zipcode_frequency.csv')

frequency.head()

m = folium.Map([34.2012,-118.4662], zoom_start=10)

folium.Choropleth(
    geo_data=folium.GeoJson('ZIP Codes.geojson'),
    name="choropleth",
    data=zipcode_data,
    columns=["zipcode", "occurance frequency"],
    fill_color='YlGn',
    fill_opacity=0.7,
    line_opacity=0.2,
    legend_name="frequency"
).add_to(m)

Answer 1

There are two issues that are not displayed: first, the zip code must be a string, not a number. The reason is that the zip code in the geojson file is a string; the second is that the connection key, in this geojson file, is under properties, so key_on='properties.zipcode' . There are some places on the map where the colors are not displayed, but if all the data is available, it will show up fine.

import folium
import pandas as pd
import numpy as np
import io
import json

data = '''
zipcode "occurance frequency"
90027 34
90731 30
90011 28
90042 23
90033 22
90031 21
91342 18
90044 18
90026 18
91331 17
90012 17
91402 15
90065 15
90037 15
90032 15
90018 15
90016 15
91352 14
91601 12
'''

zipcode_data = pd.read_csv(io.StringIO(data), delim_whitespace=True)
zipcode_data['zipcode'] = zipcode_data['zipcode'].astype(str)

file_path = "./data/ZIP_Codes.geojson"

with open(file_path, 'r') as j:
     geo_json = json.loads(j.read())

m = folium.Map([34.2012,-118.4662], zoom_start=9)

folium.Choropleth(
    geo_data=geo_json,
    name="choropleth",
    data=zipcode_data,
    columns=["zipcode", "occurance frequency"],
    key_on='properties.zipcode',
    fill_color='YlGn',
    fill_opacity=0.7,
    line_opacity=0.2,
    legend_name="frequency"
).add_to(m)
m