Before we get to pandas, it can help to be aware of and understand core Python's date and time functionality. The datetime module provides three distinct data types, date, time, and datetime. Formally, a date is a moment in time consisting of just the year, month, and day. For instance, June 7, 2013 would be a date. A time consists of hours, minutes, seconds, and microseconds (one-millionth of a second) and is unattached to any date. An example of time would be 12 hours and 30 minutes. A datetime consists of both the elements of a date and time together.

On the other hand, pandas has a single object to encapsulate date and time called a Timestamp. It has nanosecond (one-billionth of a second) precision and is derived from NumPy's datetime64 data type. Both Python and pandas each have a timedelta object that is useful when doing date addition/subtraction.