Package: bccovideda
bccovidedaAuthors:  Lianna Hovhannisyan, John Lee, Vadim Taskaev, Vanessa YuenThe 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 theCOVID-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")Installationbccovidedacan be installed from PyPI using the following terminal command:$pipinstallbccovidedaPackage Functionsget_data()This function downloads the latest detailed daily case-specific COVID-19 from BCCDC's dedicatedCOVID-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.Usagebccovidedacan be used to download and compute summary statistics, generate exploratory data analysis histogram plots, and plot time series chart data as follows:frombccovideda.get_dataimportget_datafrombccovideda.show_summary_statimportshow_summary_statfrombccovideda.plot_hist_by_condimportplot_hist_by_condfrombccovideda.plot_line_by_dateimportplot_line_by_dateget_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 EcosystemGiven 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 ascovid,covid19pyclient,covid19pandas. In contrast to existing packages,bccovidedaprovides 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.DependenciesPython 3.9 and Python packages:pandas==1.3.5requests==2.27.1altair==4.2.0altair-saver==0.5.0DocumentationDocumentationbccovidedacan be found atRead the DocsContributingInterested 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.ContributorsGroup 25 Contributors:Lianna Hovhannisyan: @liannahJohn Lee: @johnwsleeVadim Taskaev: @vtaskaev1Vanessa Yuen: @imtvwyLicenseThebccovidedaproject 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.Creditsbccovidedawas created withcookiecutterand thepy-pkgs-cookiecuttertemplate.