title: Trying to plot a choropleth map with folium leads to "Truth value of series is ambiguous" error
body: <p><strong>Problem:</strong> Trying to create a choropleth map using <code>folium</code> leads to the error:    </p>
  
  <pre><code>ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
  </code></pre>
  
  <p>This seems to be an issue involving how the <code>color_fill</code> attribute is interpreted.</p>
  
  <p>Here is the minimal working example of the code:</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  import folium
  import geopandas as gpd
  import os
  
  german_cars_price=pd.read_csv('data/german_cars_price.csv',index_col=0)
  federal_state_borders = gpd.read_file(os.path.join('data', 'federal_state_borders.geojson'))
  
  m = folium.Map(location=[52.5194, 13.4067], tiles='Mapbox Bright', zoom_start=5)
  m.choropleth(geo_data=federal_state_borders, key_on=federal_state_borders.VARNAME_1, data=german_cars_price, columns=['state', 'price'], fill_color='YlGn')
  </code></pre>
  
  <p>It seems fairly likely of course that I am doing something incorrectly, but it is unclear to me based on the documentation. <a href="https://github.com/python-visualization/folium/issues/793" rel="nofollow noreferrer">This is also an issue on GitHub</a>, which contains additional details.</p>
  
  <p><a href="http://python-visualization.github.io/folium/quickstart.html#Choropleth-maps" rel="nofollow noreferrer">The example in the documentation</a> is too sparse, inasmuch as it does not specify the required formats of the data, or show what the structure of the arguments being passed to choropleth() in that call are, to deduce a solution. In particular, what <code>feature</code> is supposed to refer to, in either the example or in <code>folium.py</code>, is beyond me.</p>
  
  <p><strong>Set-up:</strong> To give some idea of the set-up, I have a 2-column pandas DataFrame, called <code>german_cars_price</code>. The first column of this dataframe is labeled <code>state</code> and denotes the relevant German federal state. The second column is labeled <code>price</code> and refers to the average used car sales price in that German federal state from a sample of ads on eBay.</p>
  
  <p>I also have a GeoJSON file, <code>data/federal_state_borders.geojson</code>, which gives the boundaries of the German federal states, and I have imported that into Python using <code>geopandas</code>, to get a (geo) DataFrame called <code>federal_state_borders</code>. The column in this DataFrame identifying the German federal states is called <code>VAR_NAME1</code>. It is a modified version of the geoJSON found <a href="https://github.com/isellsoap/deutschlandGeoJSON" rel="nofollow noreferrer">here</a> (my translations of the names into English are different).</p>