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Load data from a CSV file

These examples illustrate how to load data from a CSV file using the Pandas and GeoPandas libraries.

From latitude and longitude columns





In [1]:



    


from pandas import read_csv
from geopandas import GeoDataFrame, points_from_xy

remote_file_path = 'http://data.sfgov.org/resource/wg3w-h783.csv'

df = read_csv(remote_file_path)

# Clean rows where the `longitude` column is NULL
df = df[df['longitude'].notna()]

gdf = GeoDataFrame(df, geometry=points_from_xy(df['longitude'], df['latitude']))
gdf.head()



    


















    
Out[1]:











  
    

      
      incident_datetime
      incident_date
      incident_time
      incident_year
      incident_day_of_week
      report_datetime
      row_id
      incident_id
      incident_number
      cad_number
      ...
      :@computed_region_qgnn_b9vv
      :@computed_region_26cr_cadq
      :@computed_region_ajp5_b2md
      :@computed_region_nqbw_i6c3
      :@computed_region_2dwj_jsy4
      :@computed_region_h4ep_8xdi
      :@computed_region_y6ts_4iup
      :@computed_region_jg9y_a9du
      :@computed_region_6pnf_4xz7
      geometry
    

  
  
    

      0
      2019-05-01T01:00:00.000
      2019-05-01T00:00:00.000
      01:00
      2019
      Wednesday
      2019-06-12T20:27:00.000
      81097515200
      810975
      190424067
      191634131.0
      ...
      10.0
      7.0
      35.0
      NaN
      NaN
      NaN
      NaN
      NaN
      1.0
      POINT (-122.49963 37.76257)
    

    

      1
      2019-06-22T07:45:00.000
      2019-06-22T00:00:00.000
      07:45
      2019
      Saturday
      2019-06-22T08:05:00.000
      81465564020
      814655
      190450880
      191730737.0
      ...
      1.0
      10.0
      34.0
      1.0
      NaN
      1.0
      NaN
      NaN
      2.0
      POINT (-122.40816 37.78054)
    

    

      2
      2019-06-03T16:16:00.000
      2019-06-03T00:00:00.000
      16:16
      2019
      Monday
      2019-06-03T16:16:00.000
      80769875000
      807698
      190397016
      191533509.0
      ...
      2.0
      9.0
      1.0
      NaN
      NaN
      NaN
      NaN
      NaN
      2.0
      POINT (-122.39075 37.72160)
    

    

      3
      2018-11-16T16:34:00.000
      2018-11-16T00:00:00.000
      16:34
      2018
      Friday
      2018-11-16T16:34:00.000
      73857915041
      738579
      180870806
      183202539.0
      ...
      6.0
      3.0
      6.0
      NaN
      18.0
      NaN
      NaN
      NaN
      2.0
      POINT (-122.40488 37.79486)
    

    

      4
      2019-05-27T02:25:00.000
      2019-05-27T00:00:00.000
      02:25
      2019
      Monday
      2019-05-27T02:55:00.000
      80509204134
      805092
      190378555
      191470256.0
      ...
      4.0
      6.0
      13.0
      NaN
      NaN
      NaN
      NaN
      NaN
      1.0
      POINT (-122.43056 37.79772)
    

  



5 rows × 37 columns



















In [2]:



    


from cartoframes.viz import Layer

Layer(gdf)



    


















    
Out[2]:







  
    
    

      

        

        
        
      
 
    
 
  

  

  

  

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    From a WKT column

    

    

    In [3]:
    

    
    
    

    from cartoframes.utils import decode_geometry

remote_file_path='http://libs.cartocdn.com/cartoframes/files/starbucks_brooklyn_geocoded.csv'

df = read_csv(remote_file_path)

gdf = GeoDataFrame(df, geometry=decode_geometry(df['the_geom']))
gdf.head()

    

    
    

    

    


    


    

    



    

    
    Out[3]:
    




    

    


    
  
    
    
      
      the_geom
      cartodb_id
      field_1
      name
      address
      revenue
      id_store
      geometry
    
    
      
  
    
    
      0
      0101000020E61000005EA27A6B607D52C01956F146E655...
      1
      0
      Franklin Ave & Eastern Pkwy
      341 Eastern Pkwy,Brooklyn, NY 11238
      1321040.772
      A
      POINT (-73.95901 40.67109)
    
    
    
    
      1
      0101000020E6100000B610E4A0847D52C0B532E197FA49...
      2
      1
      607 Brighton Beach Ave
      607 Brighton Beach Avenue,Brooklyn, NY 11235
      1268080.418
      B
      POINT (-73.96122 40.57796)
    
    
    
    
      2
      0101000020E6100000E5B8533A587F52C05726FC523F4F...
      3
      2
      65th St & 18th Ave
      6423 18th Avenue,Brooklyn, NY 11204
      1248133.699
      C
      POINT (-73.98976 40.61912)
    
    
    
    
      3
      0101000020E61000008BA6B393C18152C08D62B9A5D550...
      4
      3
      Bay Ridge Pkwy & 3rd Ave
      7419 3rd Avenue,Brooklyn, NY 11209
      1185702.676
      D
      POINT (-74.02744 40.63152)
    
    
    
    
      4
      0101000020E6100000CEFC6A0E108052C080D4264EEE4B...
      5
      4
      Caesar's Bay Shopping Center
      8973 Bay Parkway,Brooklyn, NY 11214
      1148427.411
      E
      POINT (-74.00098 40.59321)
    
    
      

    

    

    


    


    

    


    

    

    In [4]:
    

    
    
    

    Layer(gdf)

    

    
    

    

    


    


    

    



    

    
    Out[4]:
    




    

  
    
    
    
      
    
        
    
        
        
      
     
    
     
      

  

  
    
  
    
    :
    
    
      
      
    
    
  
    

  
    
    StackTrace
    
      
  
      

      





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      Content source: CartoDB/cartoframes

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