Datetime string needs to be converted to datetime object before matching on pandas column-CodePudding

Looking for clarification. I've seen several comments in SO posts saying emphatically that you can do a greater than less than comparison with a datetime column and a string formatted like a datetime object. I am finding this to be false so I was wondering if anyone could indeed confirm that this is not possible.

Here I have an example:

# between_dates_sales_seed_ae_sales_plan_ramped_date__current_date_interval_1_year____1_1_2000_
dat = '12/1/2000'
# between_dates_sales_seed_capacity_plan_by_rep_ramped_date__current_date_interval_1_year____1_1_2000_ 
ae_long['ramped_date'] = pd.to_datetime(ae_long['ramped_date'], errors='coerce').dt.strftime('%-m/%-d/%Y')
try:
    assert len(ae_long.loc[(ae_long['ramped_date'] > dat)]) == 0
except:
    print(ae_long.loc[(ae_long['ramped_date'] < dat)])

This returns many dates in ramped_date that are clearly greater than dat

            date  salesforce_user_id original_start_date ramped_date  \
3      1/31/2022  0051a000002Gxxxx           5/15/2018  10/31/2018   
14     1/31/2022  0051xxxxxxxxxxxxx          5/11/2019   1/31/2020   
15     1/31/2022  xxxxxxxxxxxxxxxxxxxxx      7/8/2019   1/31/2020   
16     1/31/2022  xxxxxxxxxxxxxxxx           9/16/2019   1/31/2020

Is the only solution to convert dat to a datetime object? Thanks

CodePudding user response：

The comparison between strings is the same thing as the comparison between dates if and only if both your dates are formatted as YYYY-MM-DD, as comparison on strings happens in lexicographic order.

With a MM-DD-YYYY formatting, you get cases such as: 06/01/1999 > 05/01/2022, as 6>5.