For each iteration in the loop, latitude and longitude values are stored as pairs in the ‘origin’ and ‘destination’ variables, respectively. The For Loop is used in conjunction with the Pairwise helper function to iterate through the rows. This is important in order to maintain the same index length as the data frame when we assign the list to a new ‘Distance’ column in the data frame. Note that the first value in the list is zero. This will make things easier to iterate through consecutive rows concurrently.Īn empty list item is created to store the calculated distances. The pairwise function is using a helper function from the itertools package, called tee. Since the CSV file is already loaded into the data frame, we can loop through the latitude and longitude values of each row using a function I initialized as Pairwise. Use your Google Maps API key to connect to the Google maps API #Perform request to use the Google Maps API web service API_key = 'AIzaS圜iF10X_example' #enter Google Maps API key gmaps = googlemaps.Client(key=API_key) 4. ',') type if necessary df = pd.read_csv( 'go_track_trackspoints.csv ') 3. #Read CSV file into data frame named 'df' #change seperator (sep e.g. In this step, we load the CSV file into a data frame. Import pandas as pd import googlemaps from itertools import tee 2.
itertools - helps to iterate through rows in the data set.googlemaps - API for distance matrix calculations.pandas - data analysis tool that helps us to manipulate data used to create a data frame with columns.
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