""" Download and use locations """ import os import pandas as pd import WebSearcher as ws # Retrieve and save latest location data data_dir = './location_data' ws.download_locations(data_dir) # Read it back in f = os.listdir(data_dir)[-1] # Last file fp = os.path.join(data_dir, f) # File path locs = pd.read_csv(fp) # Read # locs.info() # # <class 'pandas.core.frame.DataFrame'> # RangeIndex: 102029 entries, 0 to 102028 # Data columns (total 7 columns): # Criteria ID 102029 non-null int64 # Name 102029 non-null object # Canonical Name 102029 non-null object # Parent ID 101788 non-null float64 # Country Code 102013 non-null object # Target Type 102029 non-null object # Status 102029 non-null object # dtypes: float64(1), int64(1), object(5) # memory usage: 5.4+ MB # locs.iloc[0]
