I am filtering a dataframe by dates to produce two seperate versions:
- Data from only today's date
- Data from the last two years
However, when I try to filter on the date, it seems to miss dates that are within the last two years.
date_format = '%m-%d-%Y' # desired date format
today = dt.now().strftime(date_format) # today's date. Will always result in today's date
today = dt.strptime(today, date_format).date() # converting 'today' into a datetime object
today = today.strftime(date_format)
two_years = today - relativedelta(years=2) # date is today's date minus two years.
two_years = two_years.strftime(date_format)
# normalizing the format of the date column to the desired format
df_data['date'] = pd.to_datetime(df_data['date'], errors='coerce').dt.strftime(date_format)
df_today = df_data[df_data['date'] == today]
df_two_year = df_data[df_data['date'] >= two_years]
Which results in:
all dates ['07-17-2020' '07-15-2020' '08-01-2019' '03-25-2015']
today df ['07-17-2020']
two year df ['07-17-2020' '08-01-2019']
The 07-15-2020 date is missing from the two year, even though 08-01-2019 is captured.
you don't need to convert anything to string, simply work with datetime dtype. Ex:
What you get from the comparison operations (adjust them as needed...) are boolean masks - you can use them nicely to filter the df.