covid19-us
Overview
This package aims to provide a streamlined way to download historical covid data from the United States. We support the historical data sliced by state, county and zip code through three easy-to-use APIs: download_by_state, download_by_county and download_by_zip_code.
Note that for most input variables, we support either a string or a list. For example, 'zip_code_list' can be either 38120 or ['38120', '02472']. If it's the latter case, two result sets will be concatenated and returned as a pandas dataframe.
Free software: MIT license
Features
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Download data by state in the United States
download_by_state()is a function to download daily data from a given state. An example is illustrated as follows. Note that the following functions typically can accept both list type or string type. In other words, ['SC'] and SC can be both understood as South Carolina correctly.
from covid19_us import download_by_state
sc_three_days = download_by_state(state='SC', dates=['2020-12-31', '2021-01-01', '2021-01-02'])
sc_three_days[['state', 'date', 'cases', 'deaths']]| Â | state | date | cases | deaths |
| 0 | SC | 2021-01-02 00:00:00 | 5211 | 89 |
| 1 | SC | 2021-01-01 00:00:00 | 0 | 0 |
| 2 | SC | 2020-12-31 00:00:00 | 4032 | 47 |
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Download data by county in the United States
download_by_county()is a function to download daily data from a given county or counties. An example is illustrated as follows. We support both county name and county FIPS, a unique identifier.
from covid19_us import download_by_county
from pandas import date_range
richland_2020 = download_by_county(states='SC', counties='Richland', dates=date_range('2021-02-10', '2021-02-15'))| Â | county | date | deaths | cases | deaths_cumulative | cases_cumulative |
| 888738 | Richland | 2021-02-10 00:00:00 | 5 | 173 | 457 | 37804 |
| 888739 | Richland | 2021-02-11 00:00:00 | 3 | 208 | 460 | 38012 |
| 888740 | Richland | 2021-02-12 00:00:00 | 1 | 239 | 461 | 38251 |
| 888741 | Richland | 2021-02-13 00:00:00 | 2 | 239 | 463 | 38490 |
| 888742 | Richland | 2021-02-14 00:00:00 | 3 | 312 | 466 | 38802 |
| 888743 | Richland | 2021-02-15 00:00:00 | 6 | 164 | 472 | 38966 |
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download data by zip code in the united states
download_by_zip_code()is function to download daily data from a given zip code. Again, this is not exactly count by zip code, but the county total where the zip code resides in.
from covid19_us import download_by_zip_code
tn_new_year = download_by_zip_code(zip_code_list=['38120'], dates=['2021-01-01', '2021-01-02', '2021-01-03'])| Â | county | state | fips | date | deaths_cumulative | cases_cumulative | deaths | cases |
| 953003 | Shelby | TN | 47157 | 2021-01-01 00:00:00 | 903 | 67800 | 0 | 602 |
| 953004 | Shelby | TN | 47157 | 2021-01-02 00:00:00 | 914 | 69798 | 11 | 1998 |
| 953005 | Shelby | TN | 47157 | 2021-01-03 00:00:00 | 925 | 70142 | 11 | 344 |
Credits
- The data source is from the New York Times. The author would also like to express his gratitude for the agency's effort to achieve outstanding journalism.
