bccovideda

Authors: Lianna Hovhannisyan, John Lee, Vadim Taskaev, Vanessa Yuen

The British Columbia Center for Disease Control (BCCDC) manages a range of provincial programs and clinics that contribute to public health and help control the spread of disease in BC. It administers and distributes the latest daily data on COVID-19 in British Columbia, which it provides in csv format along case-, lab- and regional-specific features as well as in comprehensive ArcGIS format via the COVID-19 webpage (under "Download the data"). This package leverages daily case-specific COVID-19 data, allowing users to conveniently download the latest case data, and - per specified date range interval - compute several key statistics, visualize time series progression along age-related and regional parameters, and generate exploratory data analysis in the form of histogram figures supporting on-demand analysis. COVID-19 case detail parameters extracted using this package:

• Reported_Date (in YYYY-MM-DD format)
• HA (provincial health region, e.g., "Vancouver Coast Health")
• Sex (M or F)
• Age_Group (reported along 10-yr age group bins, e.g., "60-69")
• Classification_Reported (diagnosis origin, e.g., "Lab-diagnosed")

Installation

bccovideda can be installed from PyPI using the following terminal command:

$ pip install bccovideda

Package Functions

• get_data()

  • This function downloads the latest detailed daily case-specific COVID-19 from BCCDC's dedicated COVID-19 homepage. It returns a dataframe containing the extracted raw data.

• show_summary_stat()

  • This function computes summary statistics from the available case-specific parameters, such as age-related and regional aggregate metrics. It returns a dataframe listing key identified summary statistics specified per the time interval queried.

• plot_line_by_date()

  • This function returns a line chart plot of daily case counts, based on parameters and grouping selected by the user, per the time interval queried.

• plot_hist_by_cond()

  • This function returns a histogram plot based on parameters and grouping selected by the user, per the time interval queried, allowing for on-demand exploratory data analysis.

Usage

bccovideda can be used to download and compute summary statistics, generate exploratory data analysis histogram plots, and plot time series chart data as follows:

from bccovideda.get_data import get_data
from bccovideda.show_summary_stat import show_summary_stat
from bccovideda.plot_hist_by_cond import plot_hist_by_cond
from bccovideda.plot_line_by_date import plot_line_by_date

get_data()

show_summary_stat("2022-01-01", "2022-01-13")

plot_hist_by_cond("2021-01-01", "2021-01-30", "Age")

plot_line_by_date("2021-01-01", "2021-01-30")

Role within Python Ecosystem

Given the relatively adequate accessibility of latest aggregate COVID-19 data combined with its persistent impact on socio-economics since early 2020, there are a number of rather comprehensive Python packages that perform similar data extract and exploratory data analysis functions, such as covid, covid19pyclient, covid19pandas. In contrast to existing packages, bccovideda provides a simple user interface that focuses on the localized provincial context of British Columbia, utilizing features specific to BCCDC's data administration conventions for generating a quick overview and on-demand analysis of trends and statistics pertaining to age-related and regional case characteristics.

Dependencies

• Python 3.9 and Python packages:

  • pandas==1.3.5
  • requests==2.27.1
  • altair==4.2.0
  • altair-saver==0.5.0

Documentation

Documentation bccovideda can be found at Read the Docs

Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

Contributors

Group 25 Contributors:

• Lianna Hovhannisyan: @liannah
• John Lee: @johnwslee
• Vadim Taskaev: @vtaskaev1
• Vanessa Yuen: @imtvwy

License

The bccovideda project was created by DSCI 524 (Collaborative Software Development) Group 25 within the Master of Data Science program at the University of British Columbia (2021-2022). It is licensed under the terms of the MIT license.

Credits

bccovideda was created with cookiecutter and the py-pkgs-cookiecutter template.