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Export 100 rows to a notebook

Back to the rows

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 pandas
If 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/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.datasettes.com/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.datasettes.com/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.datasettes.com/la-times/hhs-hospital-icu-totals.csv?_stream=on",
  d3.autoType
)
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