as.Series.cat.rename_categories.html)
    * [ pandas.Series.cat.reorder_categories ](pandas.Series.cat.reorder_categories.html)
    * [ pandas.Series.cat.add_categories ](pandas.Series.cat.add_categories.html)
    * [ pandas.Series.cat.remove_categories ](pandas.Series.cat.remove_categories.html)
    * [ pandas.Series.cat.remove_unused_categories ](pandas.Series.cat.remove_unused_categories.html)
    * [ pandas.Series.cat.set_categories ](pandas.Series.cat.set_categories.html)
    * [ pandas.Series.cat.as_ordered ](pandas.Series.cat.as_ordered.html)
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    * [ pandas.Series.sparse.npoints ](pandas.Series.sparse.npoints.html)
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    * [ pandas.Series.sparse.from_coo ](pandas.Series.sparse.from_coo.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)
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    * [ pandas.Series.to_frame ](pandas.Series.to_frame.html)
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    * [ pandas.Series.to_sql ](pandas.Series.to_sql.html)
    * [ pandas.Series.to_json ](pandas.Series.to_json.html)
    * [ pandas.Series.to_string ](pandas.Series.to_string.html)
    * [ pandas.Series.to_clipboard ](pandas.Series.to_clipboard.html)
    * [ pandas.Series.to_latex ](pandas.Series.to_latex.html)
    * [ pandas.Series.to_markdown ](pandas.Series.to_markdown.html)
  * [ DataFrame ](../frame.html)
  * [ pandas arrays, scalars, and data types ](../arrays.html)
  * [ Index objects ](../indexing.html)
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  * [ Resampling ](../resampling.html)
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  * [ Plotting ](../plotting.html)
  * [ 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.nlargest  #

Series.  nlargest  (  _ n  =  5  _ , _ keep  =  'first'  _ )  [ [source]
](https://github.com/pandas-
dev/pandas/blob/v2.2.1/pandas/core/series.py#L4145-L4243) #

    

Return the largest  n  elements.

Parameters  :

    

**n** in