COVID-19 Data: U.S. coronavirus case tracking repository
Archived NYT dataset of coronavirus cases and deaths across U.S. counties and states (2020-2023).
Learn more about COVID-19 Data
COVID-19 Data is an archived collection of CSV files containing cumulative coronavirus case and death counts at national, state, and county levels throughout the United States. The repository structures data in both historical and live formats, with historical files providing end-of-day final counts and live files containing real-time updates during collection periods. Data includes FIPS codes for geographic standardization and covers both confirmed and probable cases using federal criteria. The repository also contains specialized datasets for prisons, colleges, excess deaths, mask usage surveys, and rolling averages with anomaly detection.
Geographic Granularity
Provides data at three levels - national, state, and county - with standardized FIPS codes for easy integration with mapping and demographic datasets.
Historical Archive
Contains complete time-series data from the pandemic's start in January 2020 through March 2023, serving as a comprehensive historical record of U.S. COVID-19 reporting.
Specialized Datasets
Includes additional data collections for specific contexts like prisons, colleges, excess mortality, and mask usage patterns beyond standard case and death counts.
import pandas as pd
# Load US national-level COVID-19 data
us_data = pd.read_csv('https://raw.githubusercontent.com/nytimes/covid-19-data/master/us.csv')
# Display basic info
print(us_data.head())
print(f"Data range: {us_data['date'].min()} to {us_data['date'].max()}")
print(f"Total cases: {us_data['cases'].iloc[-1]:,}")
print(f"Total deaths: {us_data['deaths'].iloc[-1]:,}")Top in Data Engineering
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