covid-19-dataset

US county level COVID-19 case data.

Daily snapshots of US cases by county.

County Data Status

State	Scraper	Validator	Aggergator	Time Series
AK	Y	N	N	N
AL	Y	N	N	N
CA	Y	N	N	N
CO	Y	N	N	N
DE	Y	N	N	N
FL	Y	N	N	N
GA	Y	N	N	N
IA	Y	N	N	N
KS	Y	N	N	N
KY	Y	N	N	N
LA	Y	N	N	N
MD	Y	N	N	N
ME	Y	N	N	N
MI	Y	N	N	N
MO	Y	N	N	N
MN	Y	N	N	N
MT	Y	N	N	N
NJ	Y	N	N	N
NY	Y	N	N	N
OH	Y	N	N	N
PA	Y	N	N	N
TN	Y	N	N	N
TX	Y	N	N	N
VA	Y	N	N	N
WA	Y	N	N	N
WY	Y	N	N	N

Project structure

/data  # county level snapshots by scrape timestamp.
    |
    - {state}_by_county_{scraper_timestamp_in_EDT}.txt # snapshot of scraped results as of timestamp.
/source_page_backup # backup of source pages by scrape timestamp.
    |
    - {state}_county_{scrape_timestamp}.html # backup of source page. Extension depends on data source.
- main.ipynb # triggers crawler
- config.yaml # shared scraper configurations
- {state}_by_county.ipynb # State specific scapers

Scraper Format

Scrapers are simple python scripts or jupyter notebooks that implement a fetch, save, and run method.

fetch()

Returns - DataFrame containing positive cases by county. - Source data - HTML page, etc.

Fetch is responsible for getting and processing a page into a Pandas DataFrame. Fetch must return a DataFrame must contain county and positive_cases columns (additional columns are fine) and a string containing the data source being scraped.

save(df, source)

Params: - df (DataFrame): DataFrame containing county and positive_cases columns (additional columns are fine) - source (str): string containing the data source page that was scraped.

Save handles persisting the Data Frame and source data. df is saved as a pipe delimited text file in the data directory with the scraping timestamp in EDT.

run()

Handles fetch and save in one action. Used in main crawling job.