d = ({
    'Date' : ['1/2/18','1/2/18','1/2/18','1/2/18','1/2/18','1/2/18'],
    'Val_A' : [1,1,2,2,1,1],
    'Val_B' : ['X','X','X','X','Y','Y'],
    })

df = pd.DataFrame(data=d)

df1 = pd.pivot_table(df, index=['Date'],values=['Val_A','Val_B'],aggfunc= 'count')

Val_A  Val_B
    Date
    1/2/18      6      6

Val_X
    Date
    1/2/18      3

pd.pivot_table(df.drop_duplicates(), index=['Date'],values=['Val_B'],aggfunc= 'count')

        Val_B
Date
1/2/18  3

df1 = pd.pivot_table(df.drop_duplicates(), index=['Date'],values=['Val_A','Val_B'],aggfunc= 'count')

df.drop_duplicates()

     Date  Val_A Val_B
0  1/2/18      1     X
2  1/2/18      2     X
4  2/2/18      1     Y
6  2/2/18      2     Y

df.groupby(['Date', 'Val_A', 'Val_B']).size().reset_index()

     Date  Val_A Val_B  0
0  1/2/18      1     X  2
1  1/2/18      1     Y  2
2  1/2/18      2     X  2

g = df.groupby(['Date', 'Val_A', 'Val_B'])

len(g)

# Out
3

df.drop_duplicates().groupby('Date').Val_A.count().reset_index(name='Val_x')


Out[1996]:
     Date  Val_x
0  1/2/18      3