使用plotly.express绘制Choropleth Map仅显示图例，地图及交互控件异常求助

Hey there! Let's work through this choropleth map issue together— I’ve dealt with similar headaches before, so here are actionable fixes you can try right away:

• Verify Your GeoJSON Data Integrity
  First up, make sure your GeoJSON is valid and properly structured. You can use Python's geojson library to validate it locally. Double-check that the property key you’re using to index (like 'id' or a district name) matches exactly between your GeoJSON's properties field and your DataFrame column— even a tiny typo (capitalization, extra spaces) will break the map rendering. If your GeoJSON is huge, try trimming it down to just a few features to rule out loading issues from oversized data.

• Check Your Plotly Rendering Environment
  If you’re running this in a Jupyter Notebook, the built-in renderer can sometimes act up. Try switching to browser rendering by adding this line before fig.show():

  import plotly.io as pio
  pio.renderers.default = 'browser'
  

  For standalone scripts, ensure fig.show() is actually executing and isn’t blocked by other code (like an unclosed file handle or infinite loop).

• Audit Your Choropleth Parameter Setup

  • Confirm you’re passing the parsed GeoJSON dictionary to the geojson parameter, not just a file path. If you’re loading from a file, use json.load(open('your_geo_file.geojson')) to read it into a Python dict first.
  • Match locationmode to your indexing method: if you’re using a property from the GeoJSON, set locationmode='geojson-properties' and ensure locations points to the corresponding DataFrame column, while featureidkey matches the exact property name in your GeoJSON (e.g., featureidkey="properties.district").
  • Make sure your z parameter (the numerical column driving the color scale) has no missing or invalid values (like NaNs)— empty values can prevent the map from rendering even if the legend shows up.

• Update Dependencies Beyond Plotly
  Even with the latest Plotly, outdated dependencies like pandas, numpy, or geojson can cause compatibility glitches. Run these commands to refresh them:

  pip install --upgrade numpy pandas geojson
  

• Test with a Minimal Working Example
  Rule out code-specific issues by running Plotly’s official minimal choropleth example first:

  import plotly.express as px
  df = px.data.election()
  geojson = px.data.election_geojson()
  fig = px.choropleth(df, geojson=geojson, color="Bergeron",
                      locations="district", featureidkey="properties.district",
                      projection="mercator")
  fig.update_geos(fitbounds="locations", visible=False)
  fig.show()
  

  If this works perfectly, the problem lies in your custom data/GeoJSON pairing. Start swapping in your data piece by piece to pinpoint where the mismatch happens.

内容的提问来源于stack exchange，提问作者Almog Woldenberg