df_non_holidays=pd.read_csv("holidays.csv")
print(df_non_holidays["date"])
0 25-06-21
1 28-06-21
2 29-06-21
3 30-06-21
4 01-07-21
5 02-07-21
6 05-07-21
7 06-07-21
8 07-07-21
9 08-07-21
10 09-07-21
11 12-07-21
12 13-07-21
13 14-07-21
14 15-07-21
15 16-07-21
16 19-07-21
17 20-07-21
18 22-07-21
19 23-07-21
20 26-07-21
21 27-07-21
22 28-07-21
23 29-07-21
24 30-07-21
Name: date, dtype: object
df_non_holidays["date"]= pd.to_datetime(df_non_holidays["date"])
0 2021-06-25
1 2021-06-28
2 2021-06-29
3 2021-06-30
4 2021-01-07
5 2021-02-07
6 2021-05-07
7 2021-06-07
8 2021-07-07
9 2021-08-07
10 2021-09-07
11 2021-12-07
12 2021-07-13
13 2021-07-14
14 2021-07-15
15 2021-07-16
16 2021-07-19
17 2021-07-20
18 2021-07-22
19 2021-07-23
20 2021-07-26
21 2021-07-27
22 2021-07-28
23 2021-07-29
24 2021-07-30
Name: date, dtype: datetime64[ns]
after converting , from index no:4 , it is changing in month and date differently.. does anything wrong in approach in converting object into datetime..
please guide me..
You also need to pass the format string, or you can pass dayfirst=True as well if you don't want to pass the format. But passing dayfirst may not always work for all type of datetime string values; however, passing format is always going to work if you pass the right format.
>>> pd.to_datetime(df_non_holidays["date"], format='%d-%m-%y')
0 2021-06-25
1 2021-06-28
2 2021-06-29
3 2021-06-30
4 2021-07-01
5 2021-07-02
6 2021-07-05
7 2021-07-06
8 2021-07-07
9 2021-07-08
10 2021-07-09
11 2021-07-12
12 2021-07-13
13 2021-07-14
14 2021-07-15
15 2021-07-16
16 2021-07-19
17 2021-07-20
18 2021-07-22
19 2021-07-23
20 2021-07-26
21 2021-07-27
22 2021-07-28
23 2021-07-29
24 2021-07-30
Name: date, dtype: datetime64[ns]