parameters: (self)
return_statement: return _iAtIndexer("iat", self)
docstring: Access a single value for a row/column pair by integer position.
  
          Similar to ``iloc``, in that both provide integer-based lookups. Use
          ``iat`` if you only need to get or set a single value in a DataFrame
          or Series.
  
          Raises
          ------
          IndexError
              When integer position is out of bounds.
  
          See Also
          --------
          DataFrame.at : Access a single value for a row/column label pair.
          DataFrame.loc : Access a group of rows and columns by label(s).
          DataFrame.iloc : Access a group of rows and columns by integer position(s).
  
          Examples
          --------
          >>> df = pd.DataFrame([[0, 2, 3], [0, 4, 1], [10, 20, 30]],
          ...                   columns=['A', 'B', 'C'])
          >>> df
              A   B   C
          0   0   2   3
          1   0   4   1
          2  10  20  30
  
          Get value at specified row/column pair
  
          >>> df.iat[1, 2]
          1
  
          Set value at specified row/column pair
  
          >>> df.iat[1, 2] = 10
          >>> df.iat[1, 2]
          10
  
          Get value within a series
  
          >>> df.loc[0].iat[1]
          2
docstring_summary: Access a single value for a row/column pair by integer position.
docstring_tokens: Access a single value for a row / column pair by integer position .
function: def iat(self) -> _iAtIndexer:
          """
          Access a single value for a row/column pair by integer position.
  
          Similar to ``iloc``, in that both provide integer-based lookups. Use
          ``iat`` if you only need to get or set a single value in a DataFrame
          or Series.
  
          Raises
          ------
          IndexError
              When integer position is out of bounds.
  
          See Also
          --------
          DataFrame.at : Access a single value for a row/column label pair.
          DataFrame.loc : Access a group of rows and columns by label(s).
          DataFrame.iloc : Access a group of rows and columns by integer position(s).
  
          Examples
          --------
          >>> df = pd.DataFrame([[0, 2, 3], [0, 4, 1], [10, 20, 30]],
          ...                   columns=['A', 'B', 'C'])
          >>> df
              A   B   C
          0   0   2   3
          1   0   4   1
          2  10  20  30
  
          Get value at specified row/column pair
  
          >>> df.iat[1, 2]
          1
  
          Set value at specified row/column pair
  
          >>> df.iat[1, 2] = 10
          >>> df.iat[1, 2]
          10
  
          Get value within a series
  
          >>> df.loc[0].iat[1]
          2
          """
          return _iAtIndexer("iat", self)
function_tokens: def iat ( self ) -> _iAtIndexer : return _iAtIndexer ( "iat" , self )