DataFrame.pivot

函数定义

DataFrame.pivot(index=None, columns=None, values=None)

Return reshaped DataFrame organized by given index / column values.

• Reshape data (produce a “pivot” table) based on column values. Uses unique values from specified index / columns to form axes of the resulting DataFrame.

• This function does not support data aggregation, multiple values will result in a MultiIndex in the columns.

函数参数

• index: str or object or a list of str, optional
  Column to use to make new frame’s index. If None, uses existing index.

• columns: str or object or a list of str
  Column to use to make new frame’s columns.

• values: str, object or a list of the previous, optional
  Column(s) to use for populating new frame’s values. If not specified, all remaining columns will be used and the result will have hierarchically indexed columns.

• Returns: DataFrame
  Returns reshaped DataFrame.

• Raises: ValueError:
  When there are any index, columns combinations with multiple values. DataFrame.pivot_table when you need to aggregate.

例子

df = pd.DataFrame({'foo': ['one', 'one', 'one', 'two', 'two',
                           'two'],
                   'bar': ['A', 'B', 'C', 'A', 'B', 'C'],
                   'baz': [1, 2, 3, 4, 5, 6],
                   'zoo': ['x', 'y', 'z', 'q', 'w', 't']})
df
    foo   bar  baz  zoo
0   one   A    1    x
1   one   B    2    y
2   one   C    3    z
3   two   A    4    q
4   two   B    5    w
5   two   C    6    t

df.pivot(index='foo', columns='bar', values='baz')
bar  A   B   C
foo
one  1   2   3
two  4   5   6

df.pivot(index='foo', columns='bar')['baz']
bar  A   B   C
foo
one  1   2   3
two  4   5   6

df.pivot(index='foo', columns='bar', values=['baz', 'zoo'])
      baz       zoo
bar   A  B  C   A  B  C
foo
one   1  2  3   x  y  z
two   4  5  6   q  w  t

You could also assign a list of column names or a list of index names.

df = pd.DataFrame({
       "lev1": [1, 1, 1, 2, 2, 2],
       "lev2": [1, 1, 2, 1, 1, 2],
       "lev3": [1, 2, 1, 2, 1, 2],
       "lev4": [1, 2, 3, 4, 5, 6],
       "values": [0, 1, 2, 3, 4, 5]})
df
    lev1 lev2 lev3 lev4 values
0   1    1    1    1    0
1   1    1    2    2    1
2   1    2    1    3    2
3   2    1    2    4    3
4   2    1    1    5    4
5   2    2    2    6    5

df.pivot(index="lev1", columns=["lev2", "lev3"],values="values")
lev2    1         2
lev3    1    2    1    2
lev1
1     0.0  1.0  2.0  NaN
2     4.0  3.0  NaN  5.0

df.pivot(index=["lev1", "lev2"], columns=["lev3"],values="values")
      lev3    1    2
lev1  lev2
   1     1  0.0  1.0
         2  2.0  NaN
   2     1  4.0  3.0
         2  NaN  5.0

A ValueError is raised if there are any duplicates.

df = pd.DataFrame({"foo": ['one', 'one', 'two', 'two'],
                   "bar": ['A', 'A', 'B', 'C'],
                   "baz": [1, 2, 3, 4]})
df
   foo bar  baz
0  one   A    1
1  one   A    2
2  two   B    3
3  two   C    4

Notice that the first two rows are the same for our index and columns arguments.

df.pivot(index='foo', columns='bar', values='baz')
Traceback (most recent call last):
   ...
ValueError: Index contains duplicate entries, cannot reshape