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

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/cdph-vaccination-state-totals.json?_shape=array"
)

Run df in a new cell to see the table.

You can export all 1,088 rows using a single streaming CSV export like this:

df = pandas.read_csv(
    "https://covid-19-j7hipcg4aq-uc.a.run.app/la-times/cdph-vaccination-state-totals.csv?_stream=on", dtype={
    "rowid": int,
    "doses_administered": int,
    "new_doses_administered": int,
    "pfizer_doses": float,
    "new_pfizer_doses": float,
    "moderna_doses": float,
    "new_moderna_doses": float,
    "jj_doses": float,
    "new_jj_doses": float,
    "partially_vaccinated": float,
    "new_partially_vaccinated": float,
    "at_least_one_dose": float,
    "new_at_least_one_dose": float,
    "fully_vaccinated": float,
    "new_fully_vaccinated": float,
    "partially_vaccinated_percent": float,
    "at_least_one_dose_percent": float,
    "fully_vaccinated_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/cdph-vaccination-state-totals.json?_shape=array"
)

You can export all 1,088 rows using a single streaming CSV export like this:

rows = d3.csv(
  "https://covid-19-j7hipcg4aq-uc.a.run.app/la-times/cdph-vaccination-state-totals.csv?_stream=on",
  d3.autoType
)