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/economist_excess_deaths.json?country=Netherlands&year=2021&_shape=array" )
Run df
in a new cell to see the table.
You can export all 104 rows using a single streaming CSV export like this:
df = pandas.read_csv( "https://covid-19.datasettes.com/covid/economist_excess_deaths.csv?country=Netherlands&year=2021&_stream=on", dtype={ "rowid": int, "region_code": int, "days": int, "year": int, "week": int, "population": int, "total_deaths": int, "covid_deaths": int, "expected_deaths": float, "excess_deaths": float, "non_covid_deaths": int, "covid_deaths_per_100k": float, "excess_deaths_per_100k": float, "excess_deaths_pct_change": float, })
Observable
Import the data into a variable called rows
like this:
rows = d3.json( "https://covid-19.datasettes.com/covid/economist_excess_deaths.json?country=Netherlands&year=2021&_shape=array" )
You can export all 104 rows using a single streaming CSV export like this:
rows = d3.csv( "https://covid-19.datasettes.com/covid/economist_excess_deaths.csv?country=Netherlands&year=2021&_stream=on", d3.autoType )