Count of values grouped per month, year - Pandas

Use GroupBy.transform for columns with same size like original DataFrame:

df['Date'] = pd.to_datetime(df['Date'], format= '%d/%m/%y')
y = df['Date'].dt.year
m = df['Date'].dt.month

df['Count_d'] = df.groupby('Date')['Date'].transform('size')
df['Count_m'] = df.groupby([y, m])['Date'].transform('size')
df['Count_y'] = df.groupby(y)['Date'].transform('size')

print(df)
        Date Val  Count_d  Count_m  Count_y
0 2018-01-01   A        2        4        6
1 2018-01-01   B        2        4        6
2 2018-01-02   C        1        4        6
3 2018-01-03   D        1        4        6
4 2018-02-01   A        1        1        6
5 2018-03-01   B        1        1        6
6 2019-01-02   C        1        2        2
7 2019-01-03   D        1        2        2