this package provides a streamlined way to download covid data by state
Project description
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
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']]
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 |
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'))
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 |
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'])
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.
History
0.1.0 (2021-03-22)
First release on PyPI.
Project details
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