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What's the difference between numpy datetime and datetime64 datetime?


Asked by Vivian Meyers on Dec 02, 2021 FAQ



The datetime module's datetime object has microsecond precision (one-millionth of a second). NumPy's datetime64 object allows you to set its precision from hours all the way to attoseconds (10 ^ -18). It's constructor is more flexible and can take a variety of inputs. Pass an integer with a string for the units. See all units here.
Keeping this in consideration,
Starting in NumPy 1.7, there are core array data types which natively support datetime functionality. The data type is called “datetime64”, so named because “datetime” is already taken by the datetime library included in Python.
Indeed, DateTime- components of both the date and the time. On the other hand, the DateTime in python has both the date and time together. Pandas’ alternative is the Timestamp object that encapsulates the date and time together. It is a counterpart for DateTime of python but it is based on the more efficient NumPy.DateTime64 data type.
Moreover,
Python | numpy.datetime64 () method Last Updated : 05 Sep, 2019 With the help of numpy.datetime64 () method, we can get the date in a numpy array in a particular format i.e year-month-day by using numpy.datetime64 () method. Syntax : numpy.datetime64 (date)
Thereof,
As we can see in the output, the Timestamp.to_datetime64 () function has returned a numpy.datetime64 object for the given Timestamp object with ‘ns’ precision. Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.