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Covid period

As explained in The Well-Grounded Data Analyst

A COVID period is a time classification distinguishing conditions before, during, or after COVID-19 lockdowns.

A COVID period classifies observations as pre-COVID, during COVID, or post-lockdowns so analysts can compare conditions across the pandemic timeline. For monthly admissions, this turns a vague question about recovery into a date-based analytical task. section 5.4.3

Build the classification by:

  • Ordering the labels categorically, then checking their counts and missing values before analysis. section 5.4.3

Cinema admissions

Classify dates before 1 March 2020 as pre-COVID, dates through 1 July 2021 as during COVID, and later dates as post-lockdowns; then compare monthly admissions and inspect whether post-lockdown levels approach earlier values.

How The Well-Grounded Data Analyst covers it

How deep it goes
Explains date conversion, cutoff assignment, categorical ordering, validation, visualization, and summary statistics, but not causal inference.
Examples
Uses monthly cinema admissions, genre releases, gross revenue, and distributor market share as classified datasets.
What it assumes
Assumes tabular data with month or year fields and teaches date typing, cutoff logic, and missing-label checks through examples.
What you can do after
Apply it via pandas to classify dated records, validate period coverage, and compare metrics across pandemic phases.
How it connects
Connects date columns, cutoff dates, categorical data, groupby aggregation, mean, median, and histograms.
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