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    * [ pandas.Series.cat.add_categories ](pandas.Series.cat.add_categories.html)
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    * [ pandas.Series.sparse.npoints ](pandas.Series.sparse.npoints.html)
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    * [ pandas.Series.list.flatten ](pandas.Series.list.flatten.html)
    * [ pandas.Series.list.len ](pandas.Series.list.len.html)
    * [ pandas.Series.list.__getitem__ ](pandas.Series.list.__getitem__.html)
    * [ pandas.Series.struct.dtypes ](pandas.Series.struct.dtypes.html)
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    * [ pandas.Series.to_latex ](pandas.Series.to_latex.html)
    * [ pandas.Series.to_markdown ](pandas.Series.to_markdown.html)
  * [ DataFrame ](../frame.html)
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  * [ Options and settings ](../options.html)
  * [ Extensions ](../extensions.html)
  * [ Testing ](../testing.html)
  * [ Missing values ](../missing_value.html)

  * [ __ ](../../index.html)
  * [ API reference ](../index.html)
  * [ Series ](../series.html)
  * pandas.Serie... 

#  pandas.Series.dt.nanosecond  #

Series.dt.  nanosecond  [ [source]  ](https://github.com/pandas-
dev/pandas/blob/v2.2.2/pandas/core/accessor.py#L95-L96) #

    

The nanoseconds of the datetime.

Examples

    
    
    >>> datetime_series = pd.Series(
    ...     pd.date_range("2000-01-01", periods=3, freq="ns")
    ... )
    >>> d