I have a multiindexed pandas.Dataframe which is something like this:
BAZ PAL
Foo Bar
124 1 A B
2 C D
134 1 E
You need to unstack your existing index level Foo
, stack your desired column 'Coo', and then rearrange the index levels. After swapping your index levels, you probably want to sort it. As a final touch, you may want to drop the column name of all the values (val
).
df = (pd.DataFrame({'Foo': [124, 124, 134, 134] * 2,
'Bar': [1, 2, 1, 2] * 2,
'Coo': ['BAZ'] * 4 + ['PAL'] * 4,
'val': list('ACEGBDFH')})
.set_index(['Foo', 'Bar', 'Coo'])
.unstack('Coo'))
>>> df
val
Coo BAZ PAL
Foo Bar
124 1 A B
2 C D
134 1 E F
2 G H
df = df.unstack('Foo').stack('Coo')
df.index = df.index.swaplevel(0, 1)
>>> df
val
Foo 124 134
Coo Bar
BAZ 1 A E
PAL 1 B F
BAZ 2 C G
PAL 2 D H
df.sort_index(inplace=True)
>>> df
val
Foo 124 134
Coo Bar
BAZ 1 A E
2 C G
PAL 1 B F
2 D H
df.columns = df.columns.droplevel()
>>> df
Foo 124 134
Coo Bar
BAZ 1 A E
2 C G
PAL 1 B F
2 D H