Amazon Last Mile Dataset

An example of how we use a Python dictionary in a real-world scenario.

Source: https://registry.opendata.aws/amazon-last-mile-challenges/

Documentation: https://github.com/MIT-CAVE/rc-cli/blob/main/templates/data_structures.md

Challenge:

find the volume of one package in the dataset

Let's explore the dataset

# Python program to read json file import json # Opening JSON file f = open('new_package_data.json') # returns JSON object as a dictionary data = json.load(f) # Closing file f.close()

data.keys()

data['RouteID_15baae2d-bf07-4967-956a-173d4036613f']

data['RouteID_15baae2d-bf07-4967-956a-173d4036613f']['AU']

data['RouteID_15baae2d-bf07-4967-956a-173d4036613f']['AU']['PackageID_180d6ed8-e08c-4a2a-972c-b0d6f1bd68ed']

data['RouteID_15baae2d-bf07-4967-956a-173d4036613f']['AU']['PackageID_180d6ed8-e08c-4a2a-972c-b0d6f1bd68ed']['dimensions']

d = data['RouteID_15baae2d-bf07-4967-956a-173d4036613f']['AU']['PackageID_180d6ed8-e08c-4a2a-972c-b0d6f1bd68ed']['dimensions']['depth_cm'] print(d)

h = data['RouteID_15baae2d-bf07-4967-956a-173d4036613f']['AU']['PackageID_180d6ed8-e08c-4a2a-972c-b0d6f1bd68ed']['dimensions']['height_cm'] print(h)

w = data['RouteID_15baae2d-bf07-4967-956a-173d4036613f']['AU']['PackageID_180d6ed8-e08c-4a2a-972c-b0d6f1bd68ed']['dimensions']['width_cm'] print(w)

print('A package has dimensions of %s cubic centemeters' %(d*w*h))