COVID-ontario

Visualization and tracking of COVID data releases from the Ontario Ministry of Health and Long-term Care (MOHLTC) available here from the 2019 Novel Coronavirus page: https://www.ontario.ca/page/2019-novel-coronavirus

@author mylesmharrison (myles at mylesharrison dot com)

Notes on the data

This also relies on data gathered by the MIDAS Network, available here: https://github.com/midas-network/COVID-19/tree/master/data/cases/canada/ontario_situation_updates

Historical changelog

2020-03-30 Changeover from regular case statuses to iPHIS format

Excel format

excel/2019-novel-coronavirus-MOHLTC-updates.xlsx:
These updates were saved manually by myself for the 10:30 and 17:30 updates from 2020/03/23 - 2020/03/29
Data prior to 03/23 was backfilled from the data from the same source saved by MIDAS
After changes in reporting on 2020/03/30, saved only daily

csv

csv/midas_processed/case_statuses_2020-03-xx.csv:
These are consolidated and processed files of the MIDAS data via python (currently in jupyter only)

csv/2019-novel-coronavirus_2020mmyy_hhmmss.csv: These files are single-line extracts from the HTML done via the python scraper/data extraction script

HTML

Archived via python scraper with data update frequency beginning on 2020/03/28

Web Scraping

The web scraper requires the geckodriver executable to be in a directory in your PATH

Usage:

1. Scrape page and save both HTML and csv

   python py/MOHLTC_covid19_scrape.py

2. Extract from previously saved HTML

   python py/MOHLTC_covid19_scrape.py --fromfile html/2019-novelcoronavirus_20200329_104219.html

TO DO

• Add python scraper using pd.read_html()
• Split python scaper into separate python file and automate csv generation
• 2020-03-30 Update scaper to account for schema change (iPHIS)
• Test automation of web scraper
• Create .py file for batch plot generation / update
• Organize csv output and MIDAS data
• Tableau dashboarding