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ENH: Add optional argument keep_index to dataframe melt method #17459

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ENH: Add optional argument keep_index to dataframe melt method #17459

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8 changes: 6 additions & 2 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4367,6 +4367,10 @@ def unstack(self, level=-1, fill_value=None):
Name to use for the 'value' column.
col_level : int or string, optional
If columns are a MultiIndex then use this level to melt.
keep_index : boolean, optional, default False
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this is commonly called index=False everywhere else.

add a versionadded

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So better to just name it index and if True resulting in the original index with duplicate entries? What about the option @TomAugspurger proposed?

If True, the original index is reused.
In the resulting MulitIndex the names of the unpivoted columns
are added as an additional level to ensure uniqueness.

See also
--------
Expand Down Expand Up @@ -4439,11 +4443,11 @@ def unstack(self, level=-1, fill_value=None):
versionadded='.. versionadded:: 0.20.0\n',
other='melt'))
def melt(self, id_vars=None, value_vars=None, var_name=None,
value_name='value', col_level=None):
value_name='value', col_level=None, keep_index=False):
from pandas.core.reshape.reshape import melt
return melt(self, id_vars=id_vars, value_vars=value_vars,
var_name=var_name, value_name=value_name,
col_level=col_level)
col_level=col_level, keep_index=keep_index)

# ----------------------------------------------------------------------
# Time series-related
Expand Down
20 changes: 17 additions & 3 deletions pandas/core/reshape/reshape.py
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Original file line number Diff line number Diff line change
Expand Up @@ -720,8 +720,7 @@ def _convert_level_number(level_num, columns):
versionadded="",
other='DataFrame.melt'))
def melt(frame, id_vars=None, value_vars=None, var_name=None,
value_name='value', col_level=None):
# TODO: what about the existing index?
value_name='value', col_level=None, keep_index=False):
if id_vars is not None:
if not is_list_like(id_vars):
id_vars = [id_vars]
Expand Down Expand Up @@ -779,7 +778,22 @@ def melt(frame, id_vars=None, value_vars=None, var_name=None,
mdata[col] = np.asanyarray(frame.columns
._get_level_values(i)).repeat(N)

return DataFrame(mdata, columns=mcolumns)
result = DataFrame(mdata, columns=mcolumns)

if keep_index:
orig_index_values = list(np.tile(frame.index.get_values(), K))

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this is quite awkward, you have several cases which you need to disambiguate. e.g. if the original is a MI or not.

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Thanks @jreback for looking over my code and the comment.

I think what I wrote should work with any number of levels.

E. g.

arrays = [['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],
          ['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']]
tuples = list(zip(*arrays))
idx_multi = pd.MultiIndex.from_tuples(tuples)
idx_single = pd.Index(arrays[0])

# Index
print(list(np.tile(idx_single, 1)))
print(list(np.tile(idx_single, 2)))

# MultiIndex
print(list(np.tile(idx_multi, 1)))
print(list(np.tile(idx_multi, 2)))

But do I have to make it more explicit (= Pythonic)? Or did I miss something else?

if len(frame.index.names) == len(set(frame.index.names)):
orig_index_names = frame.index.names
else:
orig_index_names = ["original_index_{i}".format(i=i)
for i in range(len(frame.index.names))]

result[orig_index_names] = DataFrame(orig_index_values)

result = result.set_index(orig_index_names + list(var_name))

return result


def lreshape(data, groups, dropna=True, label=None):
Expand Down