pd_dt_2.py

from itertools import product
import pandas as pd
import numpy as np

col_names = ["Day", "Month", "Year"]

df = pd.DataFrame(list(product([10, 11, 12], [8, 9], [2018, 2019])),
                   columns=col_names)

df['data'] = np.random.randn(len(df))

df = df.sort_values(['Year', 'Month'], ascending=[True, True])

df.insert(loc=0, column="date", value=pd.to_datetime(df[col_names]))
df = df.drop(col_names, axis=1).squeeze()

print(df)

"""
         date      data
0  2018-08-10 -0.328973
4  2018-08-11 -0.670790
8  2018-08-12 -1.360565
2  2018-09-10 -0.401973
6  2018-09-11 -1.238754
10 2018-09-12  0.957695
1  2019-08-10  0.571126
5  2019-08-11 -1.320735
9  2019-08-12  0.196036
3  2019-09-10 -1.717800
7  2019-09-11  0.074606
11 2019-09-12 -0.643198
"""