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/la-times.json?p0=California+City&p1=30778&p2=2022-12-28&sql=select+rowid%2C+date%2C+code%2C+name%2C+city%2C+county%2C+fips%2C+zipcode%2C+x%2C+y%2C+confirmed_cases%2C+new_confirmed_cases%2C+deaths%2C+new_deaths+from+%5Bcdcr-prison-totals%5D+where+%22city%22+%3D+%3Ap0+and+(date+%3C+%3Ap2+or+date+is+null+or+(date+%3D+%3Ap2+and+rowid+%3E+%3Ap1))+order+by+date+desc%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/la-times.json?p0=California+City&p1=30778&p2=2022-12-28&sql=select+rowid%2C+date%2C+code%2C+name%2C+city%2C+county%2C+fips%2C+zipcode%2C+x%2C+y%2C+confirmed_cases%2C+new_confirmed_cases%2C+deaths%2C+new_deaths+from+%5Bcdcr-prison-totals%5D+where+%22city%22+%3D+%3Ap0+and+(date+%3C+%3Ap2+or+date+is+null+or+(date+%3D+%3Ap2+and+rowid+%3E+%3Ap1))+order+by+date+desc%2C+rowid+limit+101&_shape=array" )