parse NYT covid data into python dictionaries

covid.py

#!/usr/bin/env python

# run from the NYT data directory:
#   python covid.py

import csv
import pprint


# data structures
by_date = {}
by_state = {}

# use prettyprint so anything we print looks nice
pp = pprint.PrettyPrinter(indent=4)

# Load the data into two maps, one organized by date, the other by state
with open('us-states.csv', newline='') as csvfile:
    # DictReader uses the first row as data labels
    reader = csv.DictReader(csvfile)
    for line in reader:
        no_date =  {k: v for k, v in line.items() if not k.startswith('date')}
        no_state = {k: v for k, v in line.items() if not k.startswith('state')}
        # create the first record or append to an existing one
        if line['date'] in by_date.keys():
            by_date[line['date']].append(no_date)
        else:
            by_date[line['date']] = [no_date]

        # create the first record or append to an existing one
        if line['state'] in by_state.keys():
            by_state[line['state']].append(no_state)
        else:
            by_state[line['state']] = [no_state]

# print data structures to see what's in them
pp.pprint(by_state)
pp.pprint(by_date)

to get all entries for a given date:
pp.pprint(by_date['2020-03-03'])

to get all dates for a given state:
pp.pprint(by_state['California'])