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Box office reports produce a CSV in which the Purchase Date appears as "May 31, 2019 at 10:43:00 PM". This is problematic for excel analysis because the standard date fields supported by excel. The complete list of these formats are
# Examples date and time formats.date_formats= (
'dd/mm/yy',
'mm/dd/yy',
'dd m yy',
'd mm yy',
'd mmm yy',
'd mmmm yy',
'd mmmm yyy',
'd mmmm yyyy',
'dd/mm/yy hh:mm',
'dd/mm/yy hh:mm:ss',
'dd/mm/yy hh:mm:ss.000',
'hh:mm',
'hh:mm:ss',
'hh:mm:ss.000',
)
The current format is not convertible to any of these formats without writing custom excel code first to convert date fields and hence impedes analysis. Since both analysis requires date, time and day of week, the reports should contain three columns "Date" and "Time", "Day of Week", with the following formats "dd/mm/yyyy", "hh:mm", "Monday/Tuesday..."
Having these fields separately allows separate feature analysis of both date, time and week day.
The text was updated successfully, but these errors were encountered:
Box office reports produce a CSV in which the Purchase Date appears as "May 31, 2019 at 10:43:00 PM". This is problematic for excel analysis because the standard date fields supported by excel. The complete list of these formats are
The current format is not convertible to any of these formats without writing custom excel code first to convert date fields and hence impedes analysis. Since both analysis requires date, time and day of week, the reports should contain three columns "Date" and "Time", "Day of Week", with the following formats "dd/mm/yyyy", "hh:mm", "Monday/Tuesday..."
Having these fields separately allows separate feature analysis of both date, time and week day.
The text was updated successfully, but these errors were encountered: