Export 101 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 101 rows into a DataFrame called df
:
df = pandas.read_json( "https://covid-19.datasettes.com/covid.json?p0=2020-05-17&p1=743657&p2=020000277-windsor-healthcare-center-of-oakland&sql=select+rowid%2C+date%2C+id%2C+slug%2C+name%2C+county%2C+staff_confirmed_cases%2C+patients_confirmed_cases%2C+staff_deaths%2C+patients_deaths%2C+fips%2C+staff_confirmed_cases_note%2C+patients_confirmed_cases_note%2C+staff_deaths_note%2C+patients_deaths_note+from+la_times_cdph_skilled_nursing_facilities+where+date(%22date%22)+%3D+%3Ap0+and+(slug+%3E+%3Ap2+or+(slug+%3D+%3Ap2+and+rowid+%3E+%3Ap1))+order+by+slug%2C+rowid+limit+101&_shape=array" )
Run df
in a new cell to see the table.
Observable
Import the data into a variable called rows
like this:
rows = d3.json( "https://covid-19.datasettes.com/covid.json?p0=2020-05-17&p1=743657&p2=020000277-windsor-healthcare-center-of-oakland&sql=select+rowid%2C+date%2C+id%2C+slug%2C+name%2C+county%2C+staff_confirmed_cases%2C+patients_confirmed_cases%2C+staff_deaths%2C+patients_deaths%2C+fips%2C+staff_confirmed_cases_note%2C+patients_confirmed_cases_note%2C+staff_deaths_note%2C+patients_deaths_note+from+la_times_cdph_skilled_nursing_facilities+where+date(%22date%22)+%3D+%3Ap0+and+(slug+%3E+%3Ap2+or+(slug+%3D+%3Ap2+and+rowid+%3E+%3Ap1))+order+by+slug%2C+rowid+limit+101&_shape=array" )