parameters: (self, dropna: bool = True)
return_statement: return Series(counts, index=index).astype("Int64")
docstring: Return a Series containing counts of each unique value.
  
          Parameters
          ----------
          dropna : bool, default True
              Don't include counts of missing values.
  
          Returns
          -------
          counts : Series
  
          See Also
          --------
          Series.value_counts
docstring_summary: Return a Series containing counts of each unique value.
docstring_tokens: Return a Series containing counts of each unique value .
function: def value_counts(self, dropna: bool = True) -> Series:
          """
          Return a Series containing counts of each unique value.
  
          Parameters
          ----------
          dropna : bool, default True
              Don't include counts of missing values.
  
          Returns
          -------
          counts : Series
  
          See Also
          --------
          Series.value_counts
          """
          from pandas import (
              Index,
              Series,
          )
  
          vc = self._data.value_counts()
  
          values = vc.field(0)
          counts = vc.field(1)
          if dropna and self._data.null_count > 0:
              mask = values.is_valid()
              values = values.filter(mask)
              counts = counts.filter(mask)
  
          # No missing values so we can adhere to the interface and return a numpy array.
          counts = np.array(counts)
  
          # Index cannot hold ExtensionArrays yet
          index = Index(type(self)(values)).astype(object)
  
          return Series(counts, index=index).astype("Int64")
function_tokens: def value_counts ( self , dropna : bool = True ) -> Series : from pandas import ( Index , Series , ) vc = self . _data . value_counts ( ) values = vc . field ( 0 ) counts = vc . field ( 1 ) if dropna and self . _data . null_count > 0 : mask = values . is_valid ( ) values = values . filter ( mask ) counts = counts . filter ( mask ) # No missing values so we can adhere to the interface and return a numpy array. counts = np . array ( counts ) # Index cannot hold ExtensionArrays yet index = Index ( type ( self ) ( values ) ) . astype ( object ) return Series ( counts , index = index ) . astype ( "Int64" )