fix names on return structure

Author: jreback

doc/source/computation.rst

@@ -549,12 +549,12 @@ can even be omitted:
 .. ipython:: python
 
  covs = df[['B','C','D']].rolling(window=50).cov(df[['A','B','C']], pairwise=True)
- covs.iloc[-50].unstack()
+ covs.unstack(-1).iloc[-50]
 
 .. ipython:: python
 
  correls = df.rolling(window=50).corr()
- correls.iloc[-50].unstack()
+ correls.unstack(-1).iloc[-50]
 
 You can efficiently retrieve the time series of correlations between two
 columns using ``.loc`` indexing:
@@ -567,7 +567,7 @@ columns using ``.loc`` indexing:
 .. ipython:: python
 
  @savefig rolling_corr_pairwise_ex.png
- correls[('A', 'C')].plot()
+ correls.unstack(-1).[('A', 'C')].plot()
 
 .. _stats.aggregate:
 

doc/source/whatsnew/v0.20.0.txt

@@ -731,9 +731,10 @@ See the section on :ref:`Windowed Binary Operations <stats.moments.binary>` for
 .. ipython:: python
 
  np.random.seed(1234)
- df = DataFrame(np.random.rand(100, 2),
- columns=['A', 'B'],
- index=pd.date_range('20160101', periods=100, freq='D'))
+ df = pd.DataFrame(np.random.rand(100, 2),
+ columns=pd.Index(['A', 'B'], name='bar'),
+ index=pd.date_range('20160101',
+ periods=100, freq='D', name='foo'))
  df
 
 Old Behavior:
@@ -755,12 +756,11 @@ New Behavior:
  res = df.rolling(12).corr()
  res
 
-Retrieving a correlation matrix for a specified index
+Retrieving a correlation matrix for a cross-section
 
 .. ipython:: python
 
- res.iloc[-1].unstack()
-
+ df.rolling(12).corr().loc['2016-04-07']
 
 .. _whatsnew_0200.api_breaking.hdfstore_where:
 

pandas/core/window.py

@@ -1707,7 +1707,7 @@ def dataframe_from_int_dict(data, frame_template):
 
  # TODO: not the most efficient (perf-wise)
  # though not bad code-wise
- from pandas import Panel, MultiIndex
+ from pandas import Panel, MultiIndex, Index
  p = Panel.from_dict(results).swapaxes('items', 'major')
  if len(p.major_axis) > 0:
  p.major_axis = arg1.columns[p.major_axis]
@@ -1721,14 +1721,16 @@ def dataframe_from_int_dict(data, frame_template):
  else:
 
  result = DataFrame(
- index=MultiIndex(levels=[arg1.columns, arg2.index],
+ index=MultiIndex(levels=[arg1.index, arg1.columns],
  labels=[[], []]),
- columns=arg1.columns,
+ columns=arg2.columns,
  dtype='float64')
 
- # reset our names
- result.columns.name = None
- result.index.names = ['major', 'minor']
+ # reset our names to arg1 names
+ # careful not to mutate the original names
+ result.columns = Index(result.columns).set_names(None)
+ result.index = result.index.set_names(
+ [arg1.index.name, arg1.columns.name])
 
  return result
 

pandas/tests/test_window.py

@@ -2660,11 +2660,13 @@ def test_rolling_functions_window_non_shrinkage(self):
  def test_rolling_functions_window_non_shrinkage_binary(self):
 
  # corr/cov return a MI DataFrame
- df = DataFrame([[1, 5], [3, 2], [3, 9], [-1, 0]], columns=['A', 'B'])
+ df = DataFrame([[1, 5], [3, 2], [3, 9], [-1, 0]],
+ columns=Index(['A', 'B'], name='foo'),
+ index=Index(range(4), name='bar'))
  df_expected = DataFrame(
- columns=df.columns,
+ columns=Index(['A', 'B']),
  index=pd.MultiIndex.from_product([df.index, df.columns],
- names=['major', 'minor']),
+ names=['bar', 'foo']),
  dtype='float64')
  functions = [lambda x: (x.rolling(window=10, min_periods=5)
  .cov(x, pairwise=True)),
@@ -2739,17 +2741,17 @@ def test_moment_functions_zero_length_pairwise(self):
 
  df1 = DataFrame()
  df1_expected = df1
- df2 = DataFrame(columns=['a'])
+ df2 = DataFrame(columns=Index(['a'], name='foo'),
+ index=Index([], name='bar'))
  df2['a'] = df2['a'].astype('float64')
 
  df1_expected = DataFrame(
- index=pd.MultiIndex.from_product([df1.columns, df1.index],
- names=['major', 'minor']),
- columns=df1.columns)
+ index=pd.MultiIndex.from_product([df1.index, df1.columns]),
+ columns=Index([]))
  df2_expected = DataFrame(
- index=pd.MultiIndex.from_product([df2.columns, df2.index],
- names=['major', 'minor']),
- columns=df2.columns,
+ index=pd.MultiIndex.from_product([df2.index, df2.columns],
+ names=['bar', 'foo']),
+ columns=Index(['a']),
  dtype='float64')
 
  functions = [lambda x: (x.expanding(min_periods=5)
@@ -2770,35 +2772,51 @@ def test_moment_functions_zero_length_pairwise(self):
 
  def test_expanding_cov_pairwise_diff_length(self):
  # GH 7512
- df1 = DataFrame([[1, 5], [3, 2], [3, 9]], columns=['A', 'B'])
- df1a = DataFrame([[1, 5], [3, 9]], index=[0, 2], columns=['A', 'B'])
- df2 = DataFrame([[5, 6], [None, None], [2, 1]], columns=['X', 'Y'])
- df2a = DataFrame([[5, 6], [2, 1]], index=[0, 2], columns=['X', 'Y'])
+ df1 = DataFrame([[1, 5], [3, 2], [3, 9]],
+ columns=Index(['A', 'B'], name='foo'))
+ df1a = DataFrame([[1, 5], [3, 9]],
+ index=[0, 2],
+ columns=Index(['A', 'B'], name='foo'))
+ df2 = DataFrame([[5, 6], [None, None], [2, 1]],
+ columns=Index(['X', 'Y'], name='foo'))
+ df2a = DataFrame([[5, 6], [2, 1]],
+ index=[0, 2],
+ columns=Index(['X', 'Y'], name='foo'))
+ # TODO: xref gh-15826
+ # .loc is not preserving the names
  result1 = df1.expanding().cov(df2a, pairwise=True).loc[2]
  result2 = df1.expanding().cov(df2a, pairwise=True).loc[2]
  result3 = df1a.expanding().cov(df2, pairwise=True).loc[2]
  result4 = df1a.expanding().cov(df2a, pairwise=True).loc[2]
  expected = DataFrame([[-3.0, -6.0], [-5.0, -10.0]],
  columns=['A', 'B'],
- index=Index(['X', 'Y'], name='minor'))
+ index=Index(['X', 'Y'], name='foo'))
  tm.assert_frame_equal(result1, expected)
  tm.assert_frame_equal(result2, expected)
  tm.assert_frame_equal(result3, expected)
  tm.assert_frame_equal(result4, expected)
 
  def test_expanding_corr_pairwise_diff_length(self):
  # GH 7512
- df1 = DataFrame([[1, 2], [3, 2], [3, 4]], columns=['A', 'B'])
- df1a = DataFrame([[1, 2], [3, 4]], index=[0, 2], columns=['A', 'B'])
- df2 = DataFrame([[5, 6], [None, None], [2, 1]], columns=['X', 'Y'])
- df2a = DataFrame([[5, 6], [2, 1]], index=[0, 2], columns=['X', 'Y'])
+ df1 = DataFrame([[1, 2], [3, 2], [3, 4]],
+ columns=['A', 'B'],
+ index=Index(range(3), name='bar'))
+ df1a = DataFrame([[1, 2], [3, 4]],
+ index=Index([0, 2], name='bar'),
+ columns=['A', 'B'])
+ df2 = DataFrame([[5, 6], [None, None], [2, 1]],
+ columns=['X', 'Y'],
+ index=Index(range(3), name='bar'))
+ df2a = DataFrame([[5, 6], [2, 1]],
+ index=Index([0, 2], name='bar'),
+ columns=['X', 'Y'])
  result1 = df1.expanding().corr(df2, pairwise=True).loc[2]
  result2 = df1.expanding().corr(df2a, pairwise=True).loc[2]
  result3 = df1a.expanding().corr(df2, pairwise=True).loc[2]
  result4 = df1a.expanding().corr(df2a, pairwise=True).loc[2]
  expected = DataFrame([[-1.0, -1.0], [-1.0, -1.0]],
  columns=['A', 'B'],
- index=Index(['X', 'Y'], name='minor'))
+ index=Index(['X', 'Y']))
  tm.assert_frame_equal(result1, expected)
  tm.assert_frame_equal(result2, expected)
  tm.assert_frame_equal(result3, expected)