将日期转换为整个新列的不同格式

Question

I want to convert the date in a column in a dataframe to a different format. Currently, it has this format: '2019-11-20T01:04:18' . I want it to have this format: 20-11-19 1:04 .

I think I need to develop a loop and generate a new column for the new date format. So essentially, in the loop, I would refer to the initial column and then generate the variable for the new column in the format I want.

Can someone help me out to complete this task?

The following code works for one occasion:

import datetime
d = datetime.datetime.strptime('2019-11-20T01:04:18', '%Y-%m-%dT%H:%M:%S')
print d.strftime('%d-%m-%y %H:%M')

Answer 1

From a previous answer in this site , this should be able to help you, comments give explanation You can read your data into pandas from csv or database or create some test data as shown below for testing.

>>> import pandas as pd
>>> df = pd.DataFrame({'column': {0: '26/1/2016', 1: '26/1/2016'}})
>>> # First convert the column to datetime datatype
>>> df['column'] = pd.to_datetime(df.column)
>>> # Then call the datetime object format() method, set the modifiers you want here
>>> df['column'] = df['column'].dt.strftime('%Y-%m-%dT%H:%M:%S') 

>>> df
                 column
0  2016-01-26T00:00:00
1  2016-01-26T00:00:00

NB. Check to ensure that all your columns have similar date strings

Answer 2

You can either achieve it like this:

from datetime import datetime

df['your_column'] = df['your_column'].apply(lambda x: datetime.strptime(x, '%Y-%m-%dT%H:%M:%S').strftime('%d-%m-%y %H:%M'))