[Pandas] Basics of processing date data using dt

About processing date data using dt accessor of Python's Pandas library

Case

After converting from the object to date data with the to_datetime function etc. Change to any date type or extract date data of a specific part

data

First, create time data

import pandas as pd
date_data = pd.DataFrame({'date':
                         ['2020-04-01 01:01:01',
                         '2021-04-02 02:02:02',
                         '2022-04-03 03:03:03',
                         '2023-04-04 04:04:04',
                         '2024-05-05 05:05:05']})
date_data
date
0 2020-04-01 01:01:01
1 2021-04-02 02:02:02
2 2022-04-03 03:03:03
3 2023-04-04 04:04:04
4 2024-05-05 05:05:05

Let's see the type of data

date_data.dtypes
date    object
dtype: object

Currently date_data ['date'] type is object

Let's change this to a data type that can be treated as a date first

date_data['date'] = pd.to_datetime(date_data['date'])
date_data['date']
0   2020-04-01 01:01:01
1   2021-04-02 02:02:02
2   2022-04-03 03:03:03
3   2023-04-04 04:04:04
4   2024-05-05 05:05:05
Name: date, dtype: datetime64[ns]

Date data processing

I want to take only the year, month, day, and seconds

The dt accessor is as follows

Series.dt

pandas.Series.dt
Series.dt()[source]
Accessor object for datetimelike properties of the Series values.

date_data['date'].dt.year
0    2020
1    2021
2    2022
3    2023
4    2024
Name: date, dtype: int64
date_data['date'].dt.month
0    4
1    4
2    4
3    4
4    5
Name: date, dtype: int64
date_data['date'].dt.day
0    1
1    2
2    3
3    4
4    5
Name: date, dtype: int64
date_data['date'].dt.second
0    1
1    2
2    3
3    4
4    5
Name: date, dtype: int64

If you want a specific type such as year / month (ex: 17/01)

There was a function called strftime. "strf" seems to be an abbreviation for "str format"

date_data['date'].dt.strftime("%y/%m")
0    20/04
1    21/04
2    22/04
3    23/04
4    24/05
Name: date, dtype: object

ex:2002/04/01 If you change% y →% Y, it will be 4 digits.

date_data['date'].dt.strftime("%Y/%M/%d")
0    2020/01/01
1    2021/02/02
2    2022/03/03
3    2023/04/04
4    2024/05/05
Name: date, dtype: object

That's all for now.

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