Pandas Series dt.month | Extract Month Part From DateTime Series

Pandas Series dt.hour | Extract Hour Part from Time Stamp

Last Updated : 07 Feb, 2024

Pandas dt.hour attribute returns a NumPy array containing the hour of the DateTime in the underlying data of the given Series object.

Example

Python3

import pandas as pd
sr = pd.Series(['2012-10-21 09:30', '2019-7-18 12:30', '2008-02-2 10:30',
                '2010-4-22 09:25', '2019-11-8 02:22'])
idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5']

sr.index = idx

sr = pd.to_datetime(sr)
result = sr.dt.hour
print(result)

Output

dt.hour attribute output

Syntax

Syntax: Series.dt.hour

Parameter: None

Returns: NumPy array containing hour values

How to Extract Hour from DateTime Object in Pandas Series

To extract the hour value from the DateTime object in the Pandas Series we use the dt.hour attribute of the Pandas library in Python.

Let us understand it better with an example:

Example:

Use the Series.dt.hour attribute to return the hour of the DateTime in the underlying data of the given Series object.

Python3

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series(pd.date_range('2012-12-12 12:12',
                       periods = 5, freq = 'H'))

# Creating the index
idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5']

# set the index
sr.index = idx

# Print the series
print(sr)

Output :

datetime series created

Now we will use the Series.dt.hour attribute to return the hour of the datetime in the underlying data of the given Series object.

Python3

# return the hour
result = sr.dt.hour

# print the result
print(result)

Output :

extracted hour value from datetime

As we can see in the output, the Series.dt.hour attribute has successfully accessed and returned the hour of the DateTime in the underlying data of the given series object.

Pandas Series dt.month | Extract Month Part From DateTime Series

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