Export 100 rows to a notebook
You can export this data to a Jupyter or Observable notebook by copying and pasting the following:
Jupyter
Make sure you have Pandas. Import it in a cell like this:
import pandasIf this shows an error you can run
%pip install pandas
in a notebook cell to install it.
Now paste the following into a cell to load the 100 rows into a DataFrame called df
:
df = pandas.read_json( "https://covid-19.datasettes.com/la-times/cdph-vaccination-zipcode-totals.json?date__date=2022-12-27&_shape=array" )
Run df
in a new cell to see the table.
You can export all 1,601 rows using a single streaming CSV export like this:
df = pandas.read_csv( "https://covid-19.datasettes.com/la-times/cdph-vaccination-zipcode-totals.csv?date__date=2022-12-27&_stream=on", dtype={ "rowid": int, "id": int, "fips": int, "population": float, "partially_vaccinated": int, "at_least_one_dose": int, "fully_vaccinated": int, })
Observable
Import the data into a variable called rows
like this:
rows = d3.json( "https://covid-19.datasettes.com/la-times/cdph-vaccination-zipcode-totals.json?date__date=2022-12-27&_shape=array" )
You can export all 1,601 rows using a single streaming CSV export like this:
rows = d3.csv( "https://covid-19.datasettes.com/la-times/cdph-vaccination-zipcode-totals.csv?date__date=2022-12-27&_stream=on", d3.autoType )