Group by and find top n value_counts pandas

Question

I have a dataframe of taxi data with two columns that looks like this:

Neighborhood    Borough        Time
Midtown         Manhattan      X
Melrose         B         


        

Answer 1

I think you can use nlargest - you can change 1 to 5:

s = df['Neighborhood'].groupby(df['Borough']).value_counts()
print s
Borough                      
Bronx          Melrose            7
Manhattan      Midtown           12
               Lincoln Square     2
Staten Island  Grant City        11
dtype: int64

print s.groupby(level=[0,1]).nlargest(1)
Bronx          Bronx          Melrose        7
Manhattan      Manhattan      Midtown       12
Staten Island  Staten Island  Grant City    11
dtype: int64

additional columns were getting created, specified level info