# pandas.core.groupby.GroupBy.nth

`GroupBy.``nth`(n, dropna=None)

  Take the nth row from each group if n is an int, or a subset of rows if n is a list of ints.

  If dropna, will take the nth non-null row, dropna is either Truthy (if a Series) or ‘all’, ‘any’ (if a DataFrame); this is equivalent to calling dropna(how=dropna) before the groupby.

  Parameters:

  n : int or list of ints

  > a single nth value for the row or a list of nth values

  dropna : None or str, optional

  > apply the specified dropna operation before counting which row is the nth row. Needs to be None, ‘any’ or ‘all’

  Examples

      >>> df = DataFrame([[1, np.nan], [1, 4], [5, 6]], columns=['A', 'B'])
      >>> g = df.groupby('A')
      >>> g.nth(0)
         A   B
      0  1 NaN
      2  5   6
      >>> g.nth(1)
         A  B
      1  1  4
      >>> g.nth(-1)
         A  B
      1  1  4
      2  5  6
      >>> g.nth(0, dropna='any')
         B
      A
      1  4
      5  6
      >>> g.nth(1, dropna='any')  # NaNs denote group exhausted when using dropna
          B
      A
      1 NaN
      5 NaN