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-j7hipcg4aq-uc.a.run.app/la-times/hhs-hospital-icu-totals.json?_shape=array" )
Run df
in a new cell to see the table.
You can export all 38,919 rows using a single streaming CSV export like this:
df = pandas.read_csv( "https://covid-19-j7hipcg4aq-uc.a.run.app/la-times/hhs-hospital-icu-totals.csv?_stream=on", dtype={ "rowid": int, "ccn": int, "fips": int, "covid_icu_patients_total": float, "available_adult_icu_beds_total": float, "occupied_adult_icu_beds_total": float, "staffed_adult_icu_beds_total": float, "occupied_adult_icu_beds_percent": float, })
Observable
Import the data into a variable called rows
like this:
rows = d3.json( "https://covid-19-j7hipcg4aq-uc.a.run.app/la-times/hhs-hospital-icu-totals.json?_shape=array" )
You can export all 38,919 rows using a single streaming CSV export like this:
rows = d3.csv( "https://covid-19-j7hipcg4aq-uc.a.run.app/la-times/hhs-hospital-icu-totals.csv?_stream=on", d3.autoType )