title: Folium not plotting correct values on map
body: <p>when I am plotting with Folium US cities with the amount of startups in them, folium does not show correct numbers on the map.  E.g. in San Francisco it should be 4737 startupds, whereas foluim shows lenn than 400 inside the cluser and when I zoon in San Fransico is shows correct number on the label only. So now it seems that there are more startupds at the Eastern Coast. Whereas i suspect that the global cluster should show the accumulative data for the region.</p>
  <p>The full code with the webscrapping data from Startup Blink that I am using in my analysis: posted here at Kaggle: <a href="https://www.kaggle.com/code/olgashevtsova/4-us-startups-webscrapping-startup-blink" rel="nofollow noreferrer">https://www.kaggle.com/code/olgashevtsova/4-us-startups-webscrapping-startup-blink</a></p>
  <p>The piece of code with the cities to map :</p>
  <pre><code>for p in range(1,770):
      url=f'https://www.startupblink.com/startups?page={p}&amp;location=united-states'
      r=requests.get(url)
      us=r.text
      soup=BeautifulSoup(us, 'html.parser')
      
      allbus=soup.find_all('div', class_='sc-2ozyz3-0 jlGOJO entity-card laptop:test')
  
      for bus in allbus:
          business_name=bus.find('a', class_='sc-2ozyz3-3 bPSWdR').text
          city=bus.find('div', class_='sc-2ozyz3-4 iNXPUy').find('a').text
          industry=bus.find_all('div', class_='sc-2ozyz3-4 iNXPUy')[1].find_all('a')[0].text
          industryspec=bus.find_all('div', class_='sc-2ozyz3-4 iNXPUy')[1].find_all('a')[1].text
          description=bus.find('div', class_='sc-2ozyz3-9 gHVzj').text
          description=description.rstrip('\xa0Read more')
          df = df.append({&quot;Business_name&quot;: business_name, &quot;City&quot;: city, &quot;Industry&quot;: industry, 'Industry Specific': industryspec, 'Description': description}, ignore_index=True)
  df=df.dropna()
  df=df.drop_duplicates()
  df.describe()
  </code></pre>
  <p>To map US cities using Folium, I am concating the original dataframe with the cities lan/lat coordinates dataset</p>
  <pre><code>coord=pd.read_csv('../input/us-cities-coordinates/uscities.csv')
  citiesplot=df.groupby('city').count().rename(columns={'Business_name': 'Number_of_businesses'})
  citiesplot.reset_index(inplace=True)
  citiesplot.value_counts()
  citiesplot=citiesplot.sort_values('Number_of_businesses', ascending=False)
  citiesplot=pd.merge(citiesplot, coord, how='left', on='city')
  citiesplot=citiesplot.loc[:, 'Number_of_businesses':'lng'].drop(columns=['Industry', 'Industry Specific', 'Description', 'state_id', 'county_fips', 'county_name']).dropna()
  
  citiesplot.sort_values('Number_of_businesses', ascending=False)
  citiesplot
  
  </code></pre>
  <p>Output:</p>
  <pre><code>Number_of_businesses    city_ascii  state_name  lat lng
  </code></pre>
  <p>0   4737    San Francisco   California  37.7558 -122.4449
  1   3576    New York    New York    40.6943 -73.9249
  2   1742    Los Angeles California  34.1141 -118.4068
  3   1742    Los Angeles Texas   26.4947 -97.7862
  4   1130    Boston  Massachusetts   42.3188 -71.0852
  <a href="https://i.stack.imgur.com/N6F1w.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/N6F1w.png" alt="enter image description here" /></a></p>
  <pre><code>us_map = folium.Map(location=[35, -95], zoom_start=4)
  from folium import plugins
  
  incidents = plugins.MarkerCluster().add_to(us_map)
  
  for lat, lng, label, in zip(citiesplot.lat, citiesplot.lng, citiesplot['Number_of_businesses']):
      folium.Marker(
          location=[lat, lng],
          icon=None,
          popup=label,
      ).add_to(incidents)
  
  us_map
  </code></pre>
  <p>Thank you for your help in advance!</p>