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  * [ Input/output ](../io.html)
  * [ General functions ](../general_functions.html) __
    * [ pandas.melt ](pandas.melt.html)
    * [ pandas.pivot ](pandas.pivot.html)
    * [ pandas.pivot_table ](pandas.pivot_table.html)
    * [ pandas.crosstab ](pandas.crosstab.html)
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    * [ pandas.merge_ordered ](pandas.merge_ordered.html)
    * [ pandas.merge_asof ](pandas.merge_asof.html)
    * [ pandas.concat ](pandas.concat.html)
    * [ pandas.get_dummies ](pandas.get_dummies.html)
    * [ pandas.from_dummies ](pandas.from_dummies.html)
    * [ pandas.factorize ](pandas.factorize.html)
    * [ pandas.unique ](pandas.unique.html)
    * [ pandas.lreshape ](pandas.lreshape.html)
    * [ pandas.wide_to_long ](pandas.wide_to_long.html)
    * [ pandas.isna ](pandas.isna.html)
    * [ pandas.isnull ](pandas.isnull.html)
    * pandas.notna 
    * [ pandas.notnull ](pandas.notnull.html)
    * [ pandas.to_numeric ](pandas.to_numeric.html)
    * [ pandas.to_datetime ](pandas.to_datetime.html)
    * [ pandas.to_timedelta ](pandas.to_timedelta.html)
    * [ pandas.date_range ](pandas.date_range.html)
    * [ pandas.bdate_range ](pandas.bdate_range.html)
    * [ pandas.period_range ](pandas.period_range.html)
    * [ pandas.timedelta_range ](pandas.timedelta_range.html)
    * [ pandas.infer_freq ](pandas.infer_freq.html)
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    * [ pandas.api.interchange.from_dataframe ](pandas.api.interchange.from_dataframe.html)
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  * [ Missing values ](../missing_value.html)

  * [ __ ](../../index.html)
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  * [ General functions ](../general_functions.html)
  * pandas.notna 

#  pandas.notna  #

pandas.  notna  (  _ obj  _ )  [ [source]  ](https://github.com/pandas-
dev/pandas/blob/v2.2.2/pandas/core/dtypes/missing.py#L380-L460) #

    

Detect non-missing values for an array-like object.

This function takes a scalar or array-like object and indicates whether values
are valid (not missing, which is ` NaN  ` in numeric arrays, ` None  ` or `
NaN  ` in ob