Pandas supports the use of datetime objects for representing date and time. You can create datetime objects directly or by converting strings into datetime format using pd.to_datetime().

a. Creating a Timestamp from a String

You can convert a string representation of a date into a Timestamp object.

date_str = '2024-11-30'
timestamp = pd.to_datetime(date_str)
print(f"Timestamp: {timestamp}")

Output:

Timestamp: 2024-11-30 00:00:00

Here, pd.to_datetime() converts the date string into a Pandas Timestamp object. The time is set to midnight by default.

b. Creating Timestamps with Specific Time

You can also create a timestamp with specific time values:

date_str = '2024-11-30 14:30:00'
timestamp_with_time = pd.to_datetime(date_str)
print(f"Timestamp with Time: {timestamp_with_time}")

Output:

Timestamp with Time: 2024-11-30 14:30:00

c. Creating DateTimeIndex

For handling a series of time-based data, you can create a DatetimeIndex. This is useful when you need to index data by dates.

date_range = pd.date_range('2024-11-01', periods=5, freq='D')
print("DatetimeIndex:")
print(date_range)

Output:

DatetimeIndex(['2024-11-01', '2024-11-02', '2024-11-03', '2024-11-04', '2024-11-05'],
              dtype='datetime64[ns]', freq='D')

Here, pd.date_range() generates a DatetimeIndex of 5 days starting from ‘2024-11-01’.