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    * [ pandas.PeriodIndex.to_timestamp ](pandas.PeriodIndex.to_timestamp.html)
    * [ pandas.PeriodIndex.from_fields ](pandas.PeriodIndex.from_fields.html)
    * [ pandas.PeriodIndex.from_ordinals ](pandas.PeriodIndex.from_ordinals.html)
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  * [ __ ](../../index.html)
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  * [ Index objects ](../indexing.html)
  * pandas.Index.nunique 

#  pandas.Index.nunique  #

Index.  nunique  (  _ dropna  =  True  _ )  [ [source]
](https://github.com/pandas-
dev/pandas/blob/v2.2.2/pandas/core/base.py#L1028-L1066) #

    

Return number of unique elements in the object.

Excludes NA values by default.

Parameters  :

    

**dropna** bool, default True

    

Donât include NaN in the count.

Returns  :

    

int

    

See also

[ ` DataFrame.nunique  `
](pandas.DataFrame.nunique.html#pandas.DataFrame.nunique
"pandas.DataFrame.nunique")

    

Method nunique for DataFrame.

[ ` Series.count  ` ](pandas.Series.count.html#pandas.Series.count
"pandas.Series.count")

    

Count non-NA/null observations in the Series.

Examples

    
    
    >>> s = pd.Series([1, 3, 5, 7, 7])
    >>> s
    0    1
    1    3
    2    5
    3    7
    4    7
    dtype: int64
    
    
    
    >>> s.nunique()
    4
    

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page") [ next  pandas.Index.value_counts  __ ](pandas.Index.value_counts.html
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__ On this page

  * ` Index.nunique()  `

[ __ Show Source ](../../_sources/reference/api/pa