why date format keep changing?-CodePudding

I am been struggling to understand this date format in pandas. Basically I'd like to remove hour:min:second so I can only keep year-month-day format.

here is the output:


df.index
atetimeIndex(['2021-07-01', '2021-07-02', '2021-07-03', '2021-07-04',
               '2021-07-05', '2021-07-06', '2021-07-07', '2021-07-08',
               '2021-07-09', '2021-07-10',
               ...
               '2021-12-23', '2021-12-24', '2021-12-25', '2021-12-26',
               '2021-12-27', '2021-12-28', '2021-12-29', '2021-12-30',
               '2021-12-31', '2022-01-01'],
              dtype='datetime64[ns]', name='Date', length=185, freq=None)

from the above, you can see date format is year-month-day.

now when I use for loop to loop over index, the individual date becomes year-month-day hour:minut:second


for index_date,date in enumerate(df.index):
    print(date)
2021-07-01 00:00:00
2021-07-02 00:00:00
2021-07-03 00:00:00
2021-07-04 00:00:00
2021-07-05 00:00:00
2021-07-06 00:00:00

why the date format is not year-month-day? Thanks for your help

Here is the detailed screenshot

CodePudding user response：

When you use df.index, you use the string representation of the pd.DatetimeIndex class whereas you use print(date) you use the string representation of the pd.Timedelta class.

>>> type(df.index)
pandas.core.indexes.datetimes.DatetimeIndex

>>> type(df.index[0])  # same as date in your loop
pandas._libs.tslibs.timestamps.Timestamp

Possible workaround for your loop:

#                                   HERE ---v
for index_date, date in enumerate(df.index.date):
    print(date)

# Output
2021-07-01
2021-07-02
2021-07-03
2021-07-04
2021-07-05
2021-07-06
...