cudf.unstack#

cudf.unstack(df, level, fill_value=None)#

Pivot one or more levels of the (necessarily hierarchical) index labels.

Pivots the specified levels of the index labels of df to the innermost levels of the columns labels of the result.

  • If the index of df has multiple levels, returns a Dataframe with specified level of the index pivoted to the column levels.

  • If the index of df has single level, returns a Series with all column levels pivoted to the index levels.

Parameters
dfDataFrame
levellevel name or index, list-like

Integer, name or list of such, specifying one or more levels of the index to pivot

fill_value

Non-functional argument provided for compatibility with Pandas.

Returns
Series or DataFrame

Examples

>>> df = cudf.DataFrame()
>>> df['a'] = [1, 1, 1, 2, 2]
>>> df['b'] = [1, 2, 3, 1, 2]
>>> df['c'] = [5, 6, 7, 8, 9]
>>> df['d'] = ['a', 'b', 'a', 'd', 'e']
>>> df = df.set_index(['a', 'b', 'd'])
>>> df
       c
a b d
1 1 a  5
  2 b  6
  3 a  7
2 1 d  8
  2 e  9

Unstacking level ā€˜aā€™:

>>> df.unstack('a')
        c
a       1     2
b d
1 a     5  <NA>
  d  <NA>     8
2 b     6  <NA>
  e  <NA>     9
3 a     7  <NA>

Unstacking level ā€˜dā€™ :

>>> df.unstack('d')
        c
d       a     b     d     e
a b
1 1     5  <NA>  <NA>  <NA>
  2  <NA>     6  <NA>  <NA>
  3     7  <NA>  <NA>  <NA>
2 1  <NA>  <NA>     8  <NA>
  2  <NA>  <NA>  <NA>     9

Unstacking multiple levels:

>>> df.unstack(['b', 'd'])
      c
b     1           2           3
d     a     d     b     e     a
a
1     5  <NA>     6  <NA>     7
2  <NA>     8  <NA>     9  <NA>

Unstacking single level index dataframe:

>>> df = cudf.DataFrame({('c', 1): [1, 2, 3], ('c', 2):[9, 8, 7]})
>>> df.unstack()
c  1  0    1
      1    2
      2    3
   2  0    9
      1    8
      2    7
dtype: int64