Pandas select rows by multiple conditions on columns

I would like to reduce my code. So instead of 2 lines I would like to select rows by 3 conditions on 2 columns.
My DataFrame contains Country’s population between 2000 and 2018 by granularity (Total, Female, Male, Urban, Rural)

    Zone        Granularity Year    Value
0   Afghanistan     Total   2000    20779.953
1   Afghanistan     Male    2000    10689.508
2   Afghanistan     Female  2000    10090.449
3   Afghanistan     Rural   2000    15657.474
4   Afghanistan     Urban   2000    4436.282
20909 Zimbabwe      Total   2018    14438.802
20910 Zimbabwe      Male    2018    6879.119
20911 Zimbabwe      Female  2018    7559.693
20912 Zimbabwe      Rural   2018    11465.748
20913 Zimbabwe      Urban   2018    5447.513

I would like all rows of the Year 2017 with granularity Total AND Urban.
I tried something like this below but not working but each condition working well in separate code.

df.loc[(df['Granularity'].isin(['Total', 'Urban'])) & (df['Year'] == '2017')]

Thanks for tips to help

>Solution :

Very likely, you’re using the wrong type for the year. I imagine these are integers.

You should try:

df.loc[(df['Granularity'].isin(['Total', 'Urban'])) & df['Year'].eq(2017)]

output (for the Year 2018 as 2017 is missing from the provided data):

           Zone Granularity  Year      Value
20909  Zimbabwe       Total  2018  14438.802
20913  Zimbabwe       Urban  2018   5447.513