Untitled

iso_code = "VEN"

import pandas as pd
from datetime import datetime as dt

df = pd.read_csv("WHO-COVID-19-global-data (2021).csv")

df = df[df["iso_code"] == iso_code]
df["date"] = df["date"].apply(lambda d: dt.strptime(d, "%m/%d/%Y"))

print(f'Maximum total_deaths: {int(df["total_deaths"].max()) if pd.notna(df["total_deaths"].max()) else "NaN"}')
print(f'Maximum icu_beds used: {int(df["icu_patients"].max()) if pd.notna(df["icu_patients"].max()) else "NaN"}')
print(f'Maximum hosp_patients: {int(df["hosp_patients"].max()) if pd.notna(df["hosp_patients"].max()) else "NaN"}')
print(f'Maximum total_vacinations: {int(df["total_vaccinations"].max()) if pd.notna(df["total_vaccinations"].max()) else "NaN"}')
print(f'First date data provided: {(dt.strftime(df["date"].min(), "%#m/%#d/%Y"))}') # for Unix, use format string %-m/%-d/%Y to remove leading zeros