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/covid/la_times_cdph_adult_and_senior_care_facilities.json?county=Santa+Clara&staff_confirmed_cases=13&_shape=array"
)

Run df in a new cell to see the table.

You can export all 105 rows using a single streaming CSV export like this:

df = pandas.read_csv(
    "https://covid-19.datasettes.com/covid/la_times_cdph_adult_and_senior_care_facilities.csv?county=Santa+Clara&staff_confirmed_cases=13&_stream=on", dtype={
    "rowid": int,
    "staff_confirmed_cases": int,
    "patients_confirmed_cases": int,
    "staff_deaths": int,
    "patients_deaths": int,
    "fips": int,
})

Observable

Import the data into a variable called rows like this:

rows = d3.json(
  "https://covid-19.datasettes.com/covid/la_times_cdph_adult_and_senior_care_facilities.json?county=Santa+Clara&staff_confirmed_cases=13&_shape=array"
)

You can export all 105 rows using a single streaming CSV export like this:

rows = d3.csv(
  "https://covid-19.datasettes.com/covid/la_times_cdph_adult_and_senior_care_facilities.csv?county=Santa+Clara&staff_confirmed_cases=13&_stream=on",
  d3.autoType
)