Pandas Series dt.nanosecond | Get Nanoseconds From DateTime Series

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

Example

Python3

import pandas as pd
sr = pd.Series(pd.date_range('2012-12-12 12:12', periods = 5, freq = '5N'))
idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5']
sr.index = idx
result = sr.dt.nanosecond
print(result)

Output

Syntax

Syntax: Series.dt.nanosecond 

Parameter: None 

Returns: NumPy array containing nanosecond values

How to Extract Nanoseconds from DateTime in Pandas Series

To extract nanoseconds from DateTime in the Pandas Series we use the dt.nanosecond attribute of the Pandas library.

Let’s understand it better with an example.

Example:

Use the Series.dt.nanosecond attribute to return the nanosecond 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('2008-2-9 08:20:21',
                       periods = 5, freq = '9N'))

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

# set the index
sr.index = idx

result = sr.dt.nanosecond

# print the result
print(result)

Output :

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