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wtf is covid-19-data?

chriskiehl/covid-19-data — explained in plain English

Analysis updated 2026-08-03 · repo last pushed 2022-01-12

Audience · dataComplexity · 1/5DormantSetup · easy

TL;DR

A comprehensive collection of COVID-19 case and death data for the United States, tracked daily since January 2020 at national, state, and county levels in simple spreadsheet files.

Mindmap

mindmap
  root((repo))
    What it does
      Daily case counts
      Death tracking
      County and state data
    Data types
      Historical finalized files
      Live updated files
      Specialized datasets
    Use cases
      Build case maps
      Compare state policies
      Health dashboards
    Audience
      Journalists
      Researchers
      Public health officials

Code map

Detail Auto

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Why would anyone build with this?

REASON 1

Build an interactive map showing how COVID-19 cases spread through specific counties over time.

REASON 2

Compare death rates between states with different pandemic policies.

REASON 3

Pull live and historical numbers into a health trends dashboard.

REASON 4

Use pre-computed rolling averages to create stable charts of case trends.

What's in the stack?

CSV

How it stacks up

chriskiehl/covid-19-data00kaku/gallery-slider-block04amanrajj/netwatch
Stars0
LanguageJavaScriptRust
Last pushed2022-01-122021-05-19
MaintenanceDormantDormant
Setup difficultyeasyeasymoderate
Complexity1/52/53/5
Audiencedatageneralops devops

Figures from each repo's GitHub metadata at analysis time.

How do you spin it up?

Difficulty · easy Time to first run · 5min

No setup required, just download or open the CSV files directly in any spreadsheet program or data analysis tool.

Wtf does this do

This repository contains a comprehensive record of Covid-19 cases and deaths across the United States, tracked since the start of the pandemic. Originally maintained by The New York Times, it provides daily cumulative counts at the national, state, and county levels, along with specialized datasets covering prisons, college campuses, mask use surveys, and excess deaths. The data comes in simple spreadsheet-like files (CSV format) that anyone can open or analyze. There are two main categories: historical files with finalized end-of-day counts for every day since January 2020, and live files updated multiple times daily with current-day numbers that may be partial. The live files also break down cases into confirmed (lab-tested) and probable (diagnosed by symptoms and exposure). County and state records include FIPS codes, which are standard geographic identifiers that make it easy to combine this data with maps or population datasets. Researchers, journalists, public health officials, and data analysts would use this data. A journalist could build an interactive map showing how cases spread through specific counties over time. A researcher could compare death rates between states with different policies. A founder building a health dashboard could pull these numbers to display trends. The pre-computed rolling averages are especially useful for anyone making charts or graphics, since the raw daily numbers can swing wildly due to reporting quirks. What stands out is the human effort behind the data. Dozens of journalists compiled it by monitoring press conferences, analyzing government releases, and contacting local health officials across more than 50 states and territories. The README documents the messy reality of American public health reporting, where states changed methodologies mid-pandemic, sometimes reported numbers differently, and occasionally moved cases between counties without explanation. The team made judgment calls, like counting patients where they were treated rather than where they lived, and revising historical entries when better information arrived.

Yoink these prompts

Prompt 1
Load the us.csv file from this repo and create a line chart showing cumulative COVID-19 cases over time using Python and pandas.
Prompt 2
Using the us-states.csv dataset, compare the death rates per capita for New York and Florida and generate a bar chart visualization.
Prompt 3
Write a Python script that joins the county-level COVID-19 data with a population dataset using FIPS codes to calculate cases per 100,000 people.
Prompt 4
Use the rolling averages data from this repo to build a smooth area chart showing the 7-day average of new COVID-19 cases by state.

Frequently asked questions

wtf is covid-19-data?

A comprehensive collection of COVID-19 case and death data for the United States, tracked daily since January 2020 at national, state, and county levels in simple spreadsheet files.

Is covid-19-data actively maintained?

Dormant — no commits in 2+ years (last push 2022-01-12).

How hard is covid-19-data to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is covid-19-data for?

Mainly data.

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