dropping rows where date aligns with max value of another column in pandas

Question

I have a DataFrame named au from which I want to drop the rows where date aligns with observations where bal==bal.max() . For example, if bal==bal.max() is associated with 2009-08-01 , then I want to drop all other observations for which date=='2009-08-01' . Below is what I've tried but both attempts result in ValueError: Series lengths must match to compare

au = au[au.date != au.date[au.bal==au.bal.max()]]
au = au[au.date != au.date[au.bal==au.bal.max()].values]

Answer 1

Using idxmax and @jezrael's setup

setup

au = pd.DataFrame({'bal':[1,2,3,4],
                   'date':['2009-08-01','2009-08-01','2009-08-02', '2009-08-02'],
                   'C':[7,8,9,1]})

solution

dmax = au.date.loc[au.bal.idxmax()]
au[au.date != dmax]

   C  bal        date
0  7    1  2009-08-01
1  8    2  2009-08-01

Answer 2

I think you need get scalar from one item Series by item or values with selected firts value by [0]:

au = pd.DataFrame({'bal':[1,2,3,4],
                   'date':['2009-08-01','2009-08-01','2009-08-02', '2009-08-02'],
                   'C':[7,8,9,1]})

print (au)
   C  bal        date
0  7    1  2009-08-01
1  8    2  2009-08-01
2  9    3  2009-08-02
3  1    4  2009-08-02


print (au[au.date != au.loc[au.bal==au.bal.max(), 'date'].item()])
   C  bal        date
0  7    1  2009-08-01
1  8    2  2009-08-01

Solution with idxmax - create Series with date first:

print (au.set_index('date').bal.idxmax())
2009-08-02

au = au[au.date != au.set_index('date').bal.idxmax()]
print (au)
   C  bal        date
0  7    1  2009-08-01
1  8    2  2009-08-01