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Adding Multiindex support to dataframe pivot function(Fixes #21425) #21467

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2 changes: 1 addition & 1 deletion doc/source/whatsnew/v0.23.2.txt
Original file line number Diff line number Diff line change
Expand Up @@ -66,7 +66,7 @@ Bug Fixes

**Reshaping**

-
- Bug in: DataFrame.pivot() function where error was raised when multiple columns are set as index
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Can you move this to the 0.24.0.txt file? And you can mention it in the Enhancements section

(as this is an new feature, not really a bug fix, I think, as it was just not yet implemented)

-

**Categorical**
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12 changes: 11 additions & 1 deletion pandas/core/reshape/reshape.py
Original file line number Diff line number Diff line change
Expand Up @@ -392,12 +392,22 @@ def pivot(self, index=None, columns=None, values=None):
cols = [columns] if index is None else [index, columns]
append = index is None
indexed = self.set_index(cols, append=append)
# adding the support for multi-index in pivot function
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this comment is not really needed I think

# assuming that for multi-index, index parameter for pivot function is list
else:
if index is None:
index = self.index
index = MultiIndex.from_arrays([index, self[columns]])
# added this case to handle multi-index
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can you make a comment that reflects what is here (not added)

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Done

elif isinstance(index, list):
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use is_list_like instead here

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Sure. I will do it.

indexes = []
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can you make this a list-comprehension

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sure!

for i in index:
indexes.append(self[i])
indexes.append(self[columns])
index = MultiIndex.from_arrays(indexes)
else:
index = self[index]
index = MultiIndex.from_arrays([index, self[columns]])
index = MultiIndex.from_arrays([index, self[columns]])

if is_list_like(values) and not isinstance(values, tuple):
# Exclude tuple because it is seen as a single column name
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17 changes: 17 additions & 0 deletions pandas/tests/reshape/test_pivot.py
Original file line number Diff line number Diff line change
Expand Up @@ -283,6 +283,23 @@ def test_pivot_multi_functions(self):
expected = concat([means, stds], keys=['mean', 'std'], axis=1)
tm.assert_frame_equal(result, expected)

# adding the test case for multiple columns as index (#21425)
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please move this comment to the first line of the test function

def test_pivot_multiple_columns_as_index(self):
df = DataFrame({'lev1': [1, 1, 1, 1, 2, 2, 2, 2],
'lev2': [1, 1, 2, 2, 1, 1, 2, 2],
'lev3': [1, 2, 1, 2, 1, 2, 1, 2],
'values': [0, 1, 2, 3, 4, 5, 6, 7]})
result = df.pivot(index=['lev1', 'lev2'],
columns='lev3',
values='values')
exp_index = pd.MultiIndex.from_product([[1, 2], [1, 2]],
names=['lev1', 'lev2'])
exp_columns = Index([1, 2], name='lev3')
expected = DataFrame([[0, 1], [2, 3], [4, 5], [6, 7]],
exp_index,
exp_columns)
tm.assert_frame_equal(result, expected)
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Can you add an example where the values argument is not mentioned? eg df.pivot(index=['lev1', 'lev2'], columns='lev3')
(I think this will not yet work, but should work)


def test_pivot_index_with_nan(self):
# GH 3588
nan = np.nan
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