Geocode a DataFrame

This example illustrates how simply use the Geocoding Data Service

Note: You'll need CARTO Account credentials to reproduce this example.



In [13]:

    
from cartoframes.auth import set_default_credentials

set_default_credentials('creds.json')



In [14]:

    
import pandas

df = pandas.DataFrame([['Gran Vía 46', 'Madrid'], ['Ebro 1', 'Sevilla']], columns=['address','city'])
df









    Out[14]:







  
    
      
      address
      city
    
  
  
    
      0
      Gran Vía 46
      Madrid
    
    
      1
      Ebro 1
      Sevilla



In [15]:

    
from cartoframes.data.services import Geocoding

gc = Geocoding()
gdf, metadata = gc.geocode(df, street='address', city='city', country={'value': 'Spain'})









    



Success! Data geocoded correctly



In [16]:

    
gdf









    Out[16]:







  
    
      
      the_geom
      address
      city
      gc_status_rel
      carto_geocode_hash
    
  
  
    
      0
      POINT (-3.70588 40.42049)
      Gran Vía 46
      Madrid
      0.84
      95e4f39284efeab8e759aaa547d84567
    
    
      1
      POINT (-5.98312 37.35547)
      Ebro 1
      Sevilla
      0.70
      66940c4beeb395e1b628587ac772763a



In [17]:

    
metadata









    Out[17]:





{'total_rows': 2,
 'required_quota': 2,
 'previously_geocoded': 0,
 'previously_failed': 0,
 'records_with_geometry': 0,
 'final_records_with_geometry': 2,
 'geocoded_increment': 2,
 'successfully_geocoded': 2,
 'failed_geocodings': 0}



In [18]:

    
from cartoframes.viz import Layer

Layer(gdf)

	the_geom	address	city	gc_status_rel	carto_geocode_hash
0	POINT (-3.70588 40.42049)	Gran Vía 46	Madrid	0.84	95e4f39284efeab8e759aaa547d84567
1	POINT (-5.98312 37.35547)	Ebro 1	Sevilla	0.70	66940c4beeb395e1b628587ac772763a