Can I replace the null value of a cell in a dataframe if two conditions are satisfied?

Question

here we are!

Hi guys, I am trying to write a loop where: if the value of a cell in a specific column is 'None' and the value of the next cell is equal to an array of countries, then I change the 'None' value to the value of the next cell, that is the name of country.

I think I'm a bit off on solving this problem.

country_with_province = array(['Australia', 'China', 'France'], dtype=object)

for m in country_with_province:
    if df5.loc[(df5['Province/State'] == None) and (df5['Country/Region'] == m):
        df5.loc[:, "Province"] = df5.Province.fillna(m)

INPUT:

	Date	Province/State	Country/Region	Recovered	Province
0	22/01/2020	None	Afghanistan	0	None
1	22/01/2020	None	Albania	0	None
2	22/01/2020	Tasmania	Australia	0	Tasmania
3	22/01/2020	None	Australia	0	None
4	22/01/2020	Hennan	China	0	Hennan
5	22/01/2020	Gansu	China	0	Gansu
6	22/01/2020	None	China	0	None
7	22/01/2020	Guineal French	France	0	Guineal French
8	22/01/2020	None	France	0	None

OUTPUT:

	Date	Province/State	Country/Region	Recovered	Province
0	22/01/2020	None	Afghanistan	0	None
1	22/01/2020	None	Albania	0	None
2	22/01/2020	Tasmania	Australia	0	Tasmania
3	22/01/2020	None	Australia	0	Australia
4	22/01/2020	Hennan	China	0	Hennan
5	22/01/2020	Gansu	China	0	Gansu
6	22/01/2020	None	China	0	China
7	22/01/2020	Guineal French	France	0	Guineal French
8	22/01/2020	None	France	0	France

I working on aa df with 87552 rows.

Ty guys, I hope you can help me, I tried to search on stack, but I failed!

Answer 1

It seems like your method works fine, so... but you wanted something nicer

sel = df5['Province/State'].isnull() & df5['Country/Region'].isin(country_with_province)
df5.loc[sel, "Province"] = df5.loc[sel, 'Country/Region']