Export 100 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 100 rows into a DataFrame called df
:
df = pandas.read_json("https://covid-19.datasettes.com/covid/johns_hopkins_csse_daily_reports.json?_shape=array")
Run df
in a new cell to see the table.
You can export all 1,317,910 rows using a single streaming CSV export like this:
df = pandas.read_csv("https://covid-19.datasettes.com/covid/johns_hopkins_csse_daily_reports.csv?_stream=on", dtype={ "rowid": int, "confirmed": int, "deaths": int, "recovered": int, "active": int, })
Observable
Import d3 by running this in a cell:
d3 = require("d3@5")
Now import the data into a variable called rows
like this:
rows = d3.json("https://covid-19.datasettes.com/covid/johns_hopkins_csse_daily_reports.json?_shape=array")
You can export all 1,317,910 rows using a single streaming CSV export like this:
rows = d3.csv("https://covid-19.datasettes.com/covid/johns_hopkins_csse_daily_reports.csv?_stream=on")
This could lose type information, since every column in a CSV import will be treated as text.