COVID-19 Project

Library used

import glob, seaborn
import pandas as pd, matplotlib.pyplot as plt
import matplotlib.ticker as ticker
from scipy import stats

Code description

analyze_rates.py

Description: Analyzes the rates of new cases of COVID-19 in countries Canada, US, China, Taiwan
- Expect output files in rates_picture folder:
  - Cumulative-Cases-over-Time.png
  - Cases-per-day-over-Time.png
- Expect output:
  - pvalue for Wilcoxon signed-rank test for Canada and US
analyze_flight.py

Description: Analyze relationship between number of flights and COVID-19 Cases
- Expected output files in current folder:
  - newly_added_infection.csv
- Expected output files in flight_and_infection_picture folder:
  - num_flights_arrived_each_day.png
  - new_infections_detected_at_each_day.png
  - analyzed_picture.png
- Expect output: None
analyze_mask_usage.py

Description: Analyze relationship between mask usage and number of COVID-19 infections in United States and mask usage in country (with FIPS code) of United States
- Expected output files in mask_analyze_picture folder:
  - percentage_infected_vs_mask_usage.png
- Expected output:
  - pvalue for Chi-Square Test

Order of execution

Note: No need to pass any arguments, just run the code by

python3 file_name.py

Group member

Henry
Piercson

Source of our datasets

Novel Coronavirus (COVID-19) Cases Data (Jan 22 to August 10):

https://data.humdata.org/dataset/novel-coronavirus-2019-ncov-cases
Flights Data across the world:

https://opensky-network.org/datasets/covid-19/
Country Codes ALPHA-2 & ALPHA-3:

https://www.iban.com/country-codes
Airport Codes:

https://github.com/datasets/airport-codes/blob/master/data/airport-codes.csv
Mask-Wearing Survey Data:

https://github.com/nytimes/covid-19-data/tree/master/mask-use
2019 Population Estimates from the US Census Bureau

https://github.com/kingaa/covid-19-data/blob/master/pop_est_2019.csv