@@ -166,15 +166,15 @@ def choropleth(self, geo_data, data=None, columns=None, key_on=None,
166166 passed to `threshold_scale` of length <=6, in order to match the
167167 color brewer range.
168168
169- TopoJSONs can be passed as "geo_path ", but the "topojson" keyword must
169+ TopoJSONs can be passed as "geo_data ", but the "topojson" keyword must
170170 also be passed with the reference to the topojson objects to convert.
171171 See the topojson.feature method in the TopoJSON API reference:
172172 https://github.com/mbostock/topojson/wiki/API-Reference
173173
174174
175175 Parameters
176176 ----------
177- geo_path : string/object
177+ geo_data : string/object
178178 URL, file path, or data (json, dict, geopandas, etc) to your GeoJSON geometries
179179 data: Pandas DataFrame or Series, default None
180180 Data to bind to the GeoJSON.
@@ -222,16 +222,16 @@ def choropleth(self, geo_data, data=None, columns=None, key_on=None,
222222
223223 Examples
224224 --------
225- >>> m.choropleth(geo_path ='us-states.json', line_color='blue',
225+ >>> m.choropleth(geo_data ='us-states.json', line_color='blue',
226226 ... line_weight=3)
227- >>> m.choropleth(geo_path ='geo.json', data=df,
227+ >>> m.choropleth(geo_data ='geo.json', data=df,
228228 ... columns=['Data 1', 'Data 2'],
229229 ... key_on='feature.properties.myvalue',
230230 ... fill_color='PuBu',
231231 ... threshold_scale=[0, 20, 30, 40, 50, 60])
232- >>> m.choropleth(geo_path ='countries.json',
232+ >>> m.choropleth(geo_data ='countries.json',
233233 ... topojson='objects.countries')
234- >>> m.choropleth(geo_path ='geo.json', data=df,
234+ >>> m.choropleth(geo_data ='geo.json', data=df,
235235 ... columns=['Data 1', 'Data 2'],
236236 ... key_on='feature.properties.myvalue',
237237 ... fill_color='PuBu',
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