如何创建从熊猫数据框到大叶地图的位置标记

Question

I am trying to take a pandas dataframe that has the longitude and latitude for the zip codes (US postal code system) with the highest per capita income.

The dataframe I'm working from has 7 columns (zip , lat, lng, rank, designation, population, per capital income).

I then create a base map to use from folium centered roughly on the US.

lati = 37.09024
longi =  -95.712891
map_usa = folium.Map(location=[lati, longi], zoom_start = 10)
map_usa

This map outputs fine.

I then am attempting to run a loop to go through the data frame to plot the individual rows, but run into an error. Code and error message is below.

for i in df_zip_top_income.iterrows():
lat = df_zip_top_income.at[i, 'lat']
lng = df_zip_top_income.at[i, 'lng']
town = df_zip_top_income.at[i, 'designation']

folium.Marker (location=[lat,lng], popup = town, icon = folium.Icon(color='blue')).add_to(map_usa)

> > --------------------------------------------------------------------------- ValueError                                Traceback (most recent call
> last) <ipython-input-59-9099f5db86dd> in <module>
>       1 for i in df_zip_top_income.iterrows():
> ----> 2     lat = df_zip_top_income.at[i, 'lat']
>       3     lng = df_zip_top_income.at[i, 'lng']
>       4     town = df_zip_top_income.at[i, 'designation']
>       5 
> 
> /opt/conda/envs/Python-3.7-main/lib/python3.7/site-packages/pandas/core/indexing.py
> in __getitem__(self, key)    2176                 raise
> ValueError("Invalid call for scalar access (getting)!")    2177 
> -> 2178         key = self._convert_key(key)    2179         return self.obj._get_value(*key, takeable=self._takeable)    2180 
> 
> /opt/conda/envs/Python-3.7-main/lib/python3.7/site-packages/pandas/core/indexing.py
> in _convert_key(self, key, is_setter)    2212                 if not
> is_integer(i):    2213                     raise ValueError(
> -> 2214                         "At based indexing on an integer index "    2215                         "can only have integer indexers"   
> 2216                     )
> 
> ValueError: At based indexing on an integer index can only have
> integer indexers

It seems to be an issue with dataypes, but I'm not sure at this point how to most effectively resolve.

df_zip_top_income.dtypes
zip              int64
lat            float64
lng            float64
rank           float64
designation     object
population     float64
per_cap_inc    float64
dtype: object

Thanks in advance, and please let me know if further information is needed.

Answer 1

iterrows returns a tuple with an index on the first position and a Series on the second. You cannot use it to index your dataframe. Instead do:

for index, series in df_zip_top_income.iterrows():
    lat = series['lat']
    lng = series['lng']
    town = series['designation']