Here are the data: clike here.
The code to look at the data about coronavirus in Italy are here:
import pandas as pd def check(what, url): df = pd.read_csv(url, error_bad_lines=False) print(what) print(df.loc[df["Country/Region"]=="Italy"]) check("Confirmed", "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Confirmed.csv") check("Recovered", "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Recovered.csv") check("Deaths", "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Deaths.csv")
The output (at 26/02/2020) is this.
Confirmed Province/State Country/Region Lat ... 2/23/20 2/24/20 2/25/20 60 NaN Italy 41.8719 ... 155 229 322 [1 rows x 39 columns] Recovered Province/State Country/Region Lat ... 2/23/20 2/24/20 2/25/20 60 NaN Italy 41.8719 ... 2 1 1 [1 rows x 39 columns] Deaths Province/State Country/Region Lat ... 2/23/20 2/24/20 2/25/20 60 NaN Italy 41.8719 ... 3 7 10 [1 rows x 39 columns] >>>
More clear view of the data
import pandas as pd from datetime import datetime yesterday = str(datetime.today().day-1) month = str(datetime.today().month) print(f"{yesterday}/{month}") def check(what, day): url = f"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-{what}.csv" df = pd.read_csv(url, error_bad_lines=False) print(what, end=" ") result = df.loc[df["Country/Region"]=="Italy"][f"{month}/{day}/20"] print(list(result)) what = "Confirmed", "Recovered", "Deaths" for w in what: check(w, yesterday)
output
25/2 Confirmed [322] Recovered [1] Deaths [10]
Check the Jupyter notebook with the code for coronavirus
Check the my jupyter lab notebook with this code
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