can't compare datetime.datetime to datetime.date
Question:
I have the following code and am getting the above error. Since I’m new to python I’m having trouble understanding the syntax here and how I can fix the error:
if not start or date < start: start = date
Answers:
Your variables start and date are of different type I guess. One is a datetime and one is a date. You may have to show more code in order to get decent help.
But look at this: http://docs.python.org/library/datetime.html#available-types
It tells you that datetime.datetime has attributes like day, month and year, just like datetime.date.
There is a datetime.date() method for converting from a datetime to a date.
To do the opposite conversion, you could use this function datetime.datetime(d.year, d.month, d.day)
You can use the datetime.datetime.combine method to compare the date object to datetime object, then compare the converted object with the other datetime object.
import datetime
dt1 = datetime.datetime(2011, 03, 03, 11, 12)
day = datetime.date(2011, 03, 02)
dt2 = datetime.datetime.combine(day, datetime.time(0, 0))
print dt1 > dt2
Assuming start is a datetime, Use it like this:
if not start or date < start.date(): start = date
I don’t think there is a need to convert date to datetime in python, as you can just do the opposite and compare.
Or else you have other methods to create a new datetime by using the date to convert and time at 00:00.
This problem arises when you are trying to compare a date field (DateField) and a datetime field (DateTimeField).
The solution would be check where you defined the fields in your models and ensure that the types are uniform.
I would suggest you replace all DateField with DateTimeField.
I was receiving the above error while using pandas, however, because the date_column was the string I wasted a lot of time without realizing I was formatting the wrong thing:
# didnt work
df[(df.date_column > parse_datestr('2018-01-01'))]
# works
df['date_column'] = pd.to_datetime(df['date_column'])
df[(df.date_column > '2018-01-01') & (df.date_column < '2018-02-28')]
Wow, question and answers are too old, it needs update. Converting datetime.datetime object to datetime.date object is just easy:
somestringtext = '7.04.2021'
datetime_datetime_object = datetime.strptime(somestringtext, '%d.%m.%Y')
### returns datetime.datetime(2021, 4, 7, 0, 0)
datetime_date_object = datetime.date(datetime_datetime_object)
And datetime object is not same as date object, you cant compare
datetime_datetime_object == datetime_date_object
### returns False
unless you convert them to same format:
datetime.date(datetime_datetime_object) == datetime_date_object
### returns True
I solved it using .date() function available with datetime object. Here is how:
date_object = datetime_object.date()
and then you can compare it with any datetime.date object. Hope this helps.
I have the following code and am getting the above error. Since I’m new to python I’m having trouble understanding the syntax here and how I can fix the error:
if not start or date < start: start = date
Your variables start and date are of different type I guess. One is a datetime and one is a date. You may have to show more code in order to get decent help.
But look at this: http://docs.python.org/library/datetime.html#available-types
It tells you that datetime.datetime has attributes like day, month and year, just like datetime.date.
There is a datetime.date() method for converting from a datetime to a date.
To do the opposite conversion, you could use this function datetime.datetime(d.year, d.month, d.day)
You can use the datetime.datetime.combine method to compare the date object to datetime object, then compare the converted object with the other datetime object.
import datetime
dt1 = datetime.datetime(2011, 03, 03, 11, 12)
day = datetime.date(2011, 03, 02)
dt2 = datetime.datetime.combine(day, datetime.time(0, 0))
print dt1 > dt2
Assuming start is a datetime, Use it like this:
if not start or date < start.date(): start = date
I don’t think there is a need to convert date to datetime in python, as you can just do the opposite and compare.
Or else you have other methods to create a new datetime by using the date to convert and time at 00:00.
This problem arises when you are trying to compare a date field (DateField) and a datetime field (DateTimeField).
The solution would be check where you defined the fields in your models and ensure that the types are uniform.
I would suggest you replace all DateField with DateTimeField.
I was receiving the above error while using pandas, however, because the date_column was the string I wasted a lot of time without realizing I was formatting the wrong thing:
# didnt work
df[(df.date_column > parse_datestr('2018-01-01'))]
# works
df['date_column'] = pd.to_datetime(df['date_column'])
df[(df.date_column > '2018-01-01') & (df.date_column < '2018-02-28')]
Wow, question and answers are too old, it needs update. Converting datetime.datetime object to datetime.date object is just easy:
somestringtext = '7.04.2021'
datetime_datetime_object = datetime.strptime(somestringtext, '%d.%m.%Y')
### returns datetime.datetime(2021, 4, 7, 0, 0)
datetime_date_object = datetime.date(datetime_datetime_object)
And datetime object is not same as date object, you cant compare
datetime_datetime_object == datetime_date_object
### returns False
unless you convert them to same format:
datetime.date(datetime_datetime_object) == datetime_date_object
### returns True
I solved it using .date() function available with datetime object. Here is how:
date_object = datetime_object.date()
and then you can compare it with any datetime.date object. Hope this helps.