Reputation: 3707
How can I reset the time part of a pandas timestamp?
I want to reset time part in value of pandas.Timestamp.
I guess I can do it using the following procedure.
Even if my guess is correct, it takes too long to do. Is there a straightforward way to achieve this goal?
In [371]: ts = pd.Timestamp('2014/11/12 13:35')
In [372]: ts
Out[372]: Timestamp('2014-11-12 13:35:00')
In [373]: ts.hour = 0 # <-- this is what I am trying to do.
Upvotes: 24
Views: 50572
Reputation: 563
If you have Timestamp then you can use pandas.Timestamp class to create new one with desired precision:
df['date' = df['date'].transform(lambda x: pd.Timestamp(x.year, x.month, x.day))
hour, minute, second can also be set, parameters not set explicitly get 0 value.
Upvotes: 0
Reputation: 9086
There is also Timestamp.floor
:
>>> ts = pd.Timestamp('2014/11/12 13:35')
>>> ts.floor('D')
Timestamp('2014-11-12 00:00:00')
>>> ts.round('D')
Timestamp('2014-11-13 00:00:00')
But, on my machine, Timestamp.normalize
is almost 30 times faster than floor
, and Timestamp.replace
is even faster than normalize
:
>>> %timeit ts.replace(hour=0, minute=0, second=0)
1.23 µs ± 17.2 ns per loop (mean ± std. dev. of 7 runs, 1,000,000 loops each)
>>> %timeit ts.normalize()
2.18 µs ± 137 ns per loop (mean ± std. dev. of 7 runs, 100,000 loops each)
>>> %timeit ts.floor('D')
62.7 µs ± 631 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)
Upvotes: 2
Reputation: 1
I recommend using:
pd.Timestamp('2014-11-12 13:35')-pd.Timedelta(f"{pd.Timestamp('2014-11-12 13:35').hour} hours")
Upvotes: 0
Reputation: 191
Note that the replace
method does not change the Timestamp, so if you want to keep the modified Timestamp you have to assign:
In [2]: ts = pd.Timestamp('2014/11/12 13:35')
In [3]: ts.replace(hour=0)
Out[3]: Timestamp('2014-11-12 00:35:00')
In [4]: ts
Out[4]: Timestamp('2014-11-12 13:35:00')
Note: ts is not modified in the code above.
In [5]: ts = ts.replace(hour=0)
In [6]: ts
Out[6]: Timestamp('2014-11-12 00:35:00')
Upvotes: 2
Reputation: 4941
pd.Timestamp('2014-11-12 13:35') - pd.offsets.Micro(0, normalize=True) == Timestamp('2014-11-12 00:00:00')
Upvotes: 0
Reputation: 139142
I think you are looking for the replace
method (see docs):
In [18]: ts
Out[18]: Timestamp('2014-11-12 13:35:00')
In [19]: ts.replace(hour=0)
Out[19]: Timestamp('2014-11-12 00:35:00')
This is a method inherited from datetime.datetime
If you want to reset the full time part, you specify all parts in replace
:
In [20]: ts.replace(hour=0, minute=0, second=0)
Out[20]: Timestamp('2014-11-12 00:00:00')
There is also a DatetimeIndex.normalize
method, but this isn't available on the individual Timestamps (I opened an issue for that: https://github.com/pydata/pandas/issues/8794):
In [21]: pd.DatetimeIndex([ts]).normalize()[0]
Out[21]: Timestamp('2014-11-12 00:00:00')
Upvotes: 44
Reputation: 18821
Instead of using datetime.datetime
, use datetime.date
and it will automatically truncate the hour/minute/second for you.
See https://docs.python.org/library/datetime.html#date-objects
Upvotes: 1