class TestMultiLevel(unittest.TestCase): def setUp(self): index = MultiIndex(levels=[['foo', 'bar', 'baz', 'qux'], ['one', 'two', 'three']], labels=[[0, 0, 0, 1, 1, 2, 2, 3, 3, 3], [0, 1, 2, 0, 1, 1, 2, 0, 1, 2]]) self.frame = DataFrame(np.random.randn(10, 3), index=index, columns=['A', 'B', 'C']) tm.N = 100 self.tdf = tm.makeTimeDataFrame() self.ymd = self.tdf.groupby([lambda x: x.year, lambda x: x.month, lambda x: x.day]).sum() def test_pickle(self): import cPickle def _test_roundtrip(frame): pickled = cPickle.dumps(frame) unpickled = cPickle.loads(pickled) assert_frame_equal(frame, unpickled) _test_roundtrip(self.frame) _test_roundtrip(self.frame.T) _test_roundtrip(self.ymd) _test_roundtrip(self.ymd.T) def test_reindex(self): reindexed = self.frame.ix[[('foo', 'one'), ('bar', 'one')]] expected = self.frame.ix[[0, 3]] assert_frame_equal(reindexed, expected) def test_repr_to_string(self): repr(self.frame) repr(self.ymd) repr(self.frame.T) repr(self.ymd.T) buf = StringIO() self.frame.to_string(buf=buf) self.ymd.to_string(buf=buf) self.frame.T.to_string(buf=buf) self.ymd.T.to_string(buf=buf) def test_getitem_simple(self): df = self.frame.T col = df['foo', 'one'] assert_almost_equal(col.values, df.values[:, 0]) self.assertRaises(KeyError, df.__getitem__, ('foo', 'four')) self.assertRaises(KeyError, df.__getitem__, 'foobar') def test_series_getitem(self): s = self.ymd['A'] result = s[2000, 3] result2 = s.ix[2000, 3] expected = s[42:65] expected.index = expected.index.droplevel(0).droplevel(0) assert_series_equal(result, expected) result = s[2000, 3, 10] expected = s[49] self.assertEquals(result, expected) # fancy result = s.ix[[(2000, 3, 10), (2000, 3, 13)]] expected = s[49:51] assert_series_equal(result, expected) # key error self.assertRaises(KeyError, s.__getitem__, (2000, 3, 4)) def test_series_setitem(self): s = self.ymd['A'] s[2000, 3] = np.nan self.assert_(isnull(s[42:65]).all()) self.assert_(notnull(s[:42]).all()) self.assert_(notnull(s[65:]).all()) s[2000, 3, 10] = np.nan self.assert_(isnull(s[49])) def test_series_slice_partial(self): pass def test_xs(self): xs = self.frame.xs(('bar', 'two')) xs2 = self.frame.ix[('bar', 'two')] assert_series_equal(xs, xs2) assert_almost_equal(xs.values, self.frame.values[4]) def test_xs_partial(self): result = self.frame.xs('foo') result2 = self.frame.ix['foo'] expected = self.frame.T['foo'].T assert_frame_equal(result, expected) assert_frame_equal(result, result2) def test_fancy_2d(self): result = self.frame.ix['foo', 'B'] expected = self.frame.xs('foo')['B'] assert_series_equal(result, expected) ft = self.frame.T result = ft.ix['B', 'foo'] expected = ft.xs('B')['foo'] assert_series_equal(result, expected) def test_getitem_toplevel(self): df = self.frame.T result = df['foo'] expected = df.reindex(columns=df.columns[:3]) expected.columns = expected.columns.droplevel(0) assert_frame_equal(result, expected) result = df['bar'] result2 = df.ix[:, 'bar'] expected = df.reindex(columns=df.columns[3:5]) expected.columns = expected.columns.droplevel(0) assert_frame_equal(result, expected) assert_frame_equal(result, result2) def test_getitem_partial(self): ymd = self.ymd.T result = ymd[2000, 2] expected = ymd.reindex(columns=ymd.columns[ymd.columns.labels[1] == 1]) expected.columns = expected.columns.droplevel(0).droplevel(0) assert_frame_equal(result, expected) def test_setitem_change_dtype(self): dft = self.frame.T s = dft['foo', 'two'] dft['foo', 'two'] = s > s.median() assert_series_equal(dft['foo', 'two'], s > s.median()) self.assert_(isinstance(dft._data.blocks[1].items, MultiIndex)) reindexed = dft.reindex(columns=[('foo', 'two')]) assert_series_equal(reindexed['foo', 'two'], s > s.median()) def test_fancy_slice_partial(self): result = self.frame.ix['bar':'baz'] expected = self.frame[3:7] assert_frame_equal(result, expected) result = self.ymd.ix[(2000,2):(2000,4)] lev = self.ymd.index.labels[1] expected = self.ymd[(lev >= 1) & (lev <= 3)] assert_frame_equal(result, expected) def test_sortlevel(self): df = self.frame.copy() df.index = np.arange(len(df)) self.assertRaises(Exception, df.sortlevel, 0) # axis=1 # series a_sorted = self.frame['A'].sortlevel(0) self.assertRaises(Exception, self.frame.delevel()['A'].sortlevel) def test_sortlevel_mixed(self): sorted_before = self.frame.sortlevel(1) df = self.frame.copy() df['foo'] = 'bar' sorted_after = df.sortlevel(1) assert_frame_equal(sorted_before, sorted_after.drop(['foo'], axis=1)) dft = self.frame.T sorted_before = dft.sortlevel(1, axis=1) dft['foo', 'three'] = 'bar' sorted_after = dft.sortlevel(1, axis=1) assert_frame_equal(sorted_before.drop([('foo', 'three')], axis=1), sorted_after.drop([('foo', 'three')], axis=1)) def test_count_level(self): def _check_counts(frame, axis=0): index = frame._get_axis(axis) for i in range(index.nlevels): result = frame.count(axis=axis, level=i) expected = frame.groupby(axis=axis, level=i).count(axis=axis) _check_counts(self.frame) _check_counts(self.ymd) _check_counts(self.frame.T, axis=1) _check_counts(self.ymd.T, axis=1) # can't call with level on regular DataFrame df = tm.makeTimeDataFrame() self.assertRaises(Exception, df.count, level=0) def test_unstack(self): # just check that it works for now unstacked = self.ymd.unstack() unstacked2 = unstacked.unstack() def test_insert_index(self): df = self.ymd[:5].T df[2000, 1, 10] = df[2000, 1, 7] self.assert_(isinstance(df.columns, MultiIndex)) self.assert_((df[2000, 1, 10] == df[2000, 1, 7]).all()) def test_alignment(self): pass def test_is_lexsorted(self): levels = [[0, 1], [0, 1, 2]] index = MultiIndex(levels=levels, labels=[[0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 1, 2]]) self.assert_(index.is_lexsorted()) index = MultiIndex(levels=levels, labels=[[0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 2, 1]]) self.assert_(not index.is_lexsorted()) index = MultiIndex(levels=levels, labels=[[0, 0, 1, 0, 1, 1], [0, 1, 0, 2, 2, 1]]) self.assert_(not index.is_lexsorted()) self.assert_(index.lexsort_depth == 0)
class TestMultiLevel(unittest.TestCase): def setUp(self): index = MultiIndex(levels=[['foo', 'bar', 'baz', 'qux'], ['one', 'two', 'three']], labels=[[0, 0, 0, 1, 1, 2, 2, 3, 3, 3], [0, 1, 2, 0, 1, 1, 2, 0, 1, 2]]) self.frame = DataFrame(np.random.randn(10, 3), index=index, columns=['A', 'B', 'C']) tm.N = 100 self.tdf = tm.makeTimeDataFrame() self.ymd = self.tdf.groupby([lambda x: x.year, lambda x: x.month, lambda x: x.day]).sum() def test_pickle(self): import cPickle def _test_roundtrip(frame): pickled = cPickle.dumps(frame) unpickled = cPickle.loads(pickled) assert_frame_equal(frame, unpickled) _test_roundtrip(self.frame) _test_roundtrip(self.frame.T) _test_roundtrip(self.ymd) _test_roundtrip(self.ymd.T) def test_reindex(self): reindexed = self.frame.ix[[('foo', 'one'), ('bar', 'one')]] expected = self.frame.ix[[0, 3]] assert_frame_equal(reindexed, expected) def test_reindex_preserve_levels(self): new_index = self.ymd.index[::10] chunk = self.ymd.reindex(new_index) self.assert_(chunk.index is new_index) chunk = self.ymd.ix[new_index] self.assert_(chunk.index is new_index) ymdT = self.ymd.T chunk = ymdT.reindex(columns=new_index) self.assert_(chunk.columns is new_index) chunk = ymdT.ix[:, new_index] self.assert_(chunk.columns is new_index) def test_repr_to_string(self): repr(self.frame) repr(self.ymd) repr(self.frame.T) repr(self.ymd.T) buf = StringIO() self.frame.to_string(buf=buf) self.ymd.to_string(buf=buf) self.frame.T.to_string(buf=buf) self.ymd.T.to_string(buf=buf) def test_getitem_simple(self): df = self.frame.T col = df['foo', 'one'] assert_almost_equal(col.values, df.values[:, 0]) self.assertRaises(KeyError, df.__getitem__, ('foo', 'four')) self.assertRaises(KeyError, df.__getitem__, 'foobar') def test_series_getitem(self): s = self.ymd['A'] result = s[2000, 3] result2 = s.ix[2000, 3] expected = s[42:65] expected.index = expected.index.droplevel(0).droplevel(0) assert_series_equal(result, expected) result = s[2000, 3, 10] expected = s[49] self.assertEquals(result, expected) # fancy result = s.ix[[(2000, 3, 10), (2000, 3, 13)]] expected = s[49:51] assert_series_equal(result, expected) # key error self.assertRaises(KeyError, s.__getitem__, (2000, 3, 4)) def test_series_setitem(self): s = self.ymd['A'] s[2000, 3] = np.nan self.assert_(isnull(s[42:65]).all()) self.assert_(notnull(s[:42]).all()) self.assert_(notnull(s[65:]).all()) s[2000, 3, 10] = np.nan self.assert_(isnull(s[49])) def test_series_slice_partial(self): pass def test_xs(self): xs = self.frame.xs(('bar', 'two')) xs2 = self.frame.ix[('bar', 'two')] assert_series_equal(xs, xs2) assert_almost_equal(xs.values, self.frame.values[4]) def test_xs_partial(self): result = self.frame.xs('foo') result2 = self.frame.ix['foo'] expected = self.frame.T['foo'].T assert_frame_equal(result, expected) assert_frame_equal(result, result2) def test_fancy_2d(self): result = self.frame.ix['foo', 'B'] expected = self.frame.xs('foo')['B'] assert_series_equal(result, expected) ft = self.frame.T result = ft.ix['B', 'foo'] expected = ft.xs('B')['foo'] assert_series_equal(result, expected) def test_getitem_toplevel(self): df = self.frame.T result = df['foo'] expected = df.reindex(columns=df.columns[:3]) expected.columns = expected.columns.droplevel(0) assert_frame_equal(result, expected) result = df['bar'] result2 = df.ix[:, 'bar'] expected = df.reindex(columns=df.columns[3:5]) expected.columns = expected.columns.droplevel(0) assert_frame_equal(result, expected) assert_frame_equal(result, result2) def test_getitem_int(self): levels = [[0, 1], [0, 1, 2]] labels = [[0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 1, 2]] index = MultiIndex(levels=levels, labels=labels) frame = DataFrame(np.random.randn(6, 2), index=index) result = frame.ix[1] expected = frame[-3:] expected.index = expected.index.droplevel(0) assert_frame_equal(result, expected) # raises exception self.assertRaises(KeyError, frame.ix.__getitem__, 3) # however this will work result = self.frame.ix[2] expected = self.frame.xs(self.frame.index[2]) assert_series_equal(result, expected) def test_getitem_partial(self): ymd = self.ymd.T result = ymd[2000, 2] expected = ymd.reindex(columns=ymd.columns[ymd.columns.labels[1] == 1]) expected.columns = expected.columns.droplevel(0).droplevel(0) assert_frame_equal(result, expected) def test_setitem_change_dtype(self): dft = self.frame.T s = dft['foo', 'two'] dft['foo', 'two'] = s > s.median() assert_series_equal(dft['foo', 'two'], s > s.median()) self.assert_(isinstance(dft._data.blocks[1].items, MultiIndex)) reindexed = dft.reindex(columns=[('foo', 'two')]) assert_series_equal(reindexed['foo', 'two'], s > s.median()) def test_fancy_slice_partial(self): result = self.frame.ix['bar':'baz'] expected = self.frame[3:7] assert_frame_equal(result, expected) result = self.ymd.ix[(2000,2):(2000,4)] lev = self.ymd.index.labels[1] expected = self.ymd[(lev >= 1) & (lev <= 3)] assert_frame_equal(result, expected) def test_sortlevel(self): df = self.frame.copy() df.index = np.arange(len(df)) self.assertRaises(Exception, df.sortlevel, 0) # axis=1 # series a_sorted = self.frame['A'].sortlevel(0) self.assertRaises(Exception, self.frame.delevel()['A'].sortlevel) def test_sortlevel_mixed(self): sorted_before = self.frame.sortlevel(1) df = self.frame.copy() df['foo'] = 'bar' sorted_after = df.sortlevel(1) assert_frame_equal(sorted_before, sorted_after.drop(['foo'], axis=1)) dft = self.frame.T sorted_before = dft.sortlevel(1, axis=1) dft['foo', 'three'] = 'bar' sorted_after = dft.sortlevel(1, axis=1) assert_frame_equal(sorted_before.drop([('foo', 'three')], axis=1), sorted_after.drop([('foo', 'three')], axis=1)) def test_count_level(self): def _check_counts(frame, axis=0): index = frame._get_axis(axis) for i in range(index.nlevels): result = frame.count(axis=axis, level=i) expected = frame.groupby(axis=axis, level=i).count(axis=axis) _check_counts(self.frame) _check_counts(self.ymd) _check_counts(self.frame.T, axis=1) _check_counts(self.ymd.T, axis=1) # can't call with level on regular DataFrame df = tm.makeTimeDataFrame() self.assertRaises(Exception, df.count, level=0) def test_unstack(self): # just check that it works for now unstacked = self.ymd.unstack() unstacked2 = unstacked.unstack() # test that ints work unstacked = self.ymd.astype(int).unstack() def test_stack(self): # regular roundtrip unstacked = self.ymd.unstack() restacked = unstacked.stack() assert_frame_equal(restacked, self.ymd) unlexsorted = self.ymd.sortlevel(2) unstacked = unlexsorted.unstack(2) restacked = unstacked.stack() assert_frame_equal(restacked.sortlevel(0), self.ymd) unlexsorted = unlexsorted[::-1] unstacked = unlexsorted.unstack(1) restacked = unstacked.stack().swaplevel(1, 2) assert_frame_equal(restacked.sortlevel(0), self.ymd) unlexsorted = unlexsorted.swaplevel(0, 1) unstacked = unlexsorted.unstack(0).swaplevel(0, 1, axis=1) restacked = unstacked.stack(0).swaplevel(1, 2) assert_frame_equal(restacked.sortlevel(0), self.ymd) # columns unsorted unstacked = self.ymd.unstack() unstacked = unstacked.sort(axis=1, ascending=False) restacked = unstacked.stack() assert_frame_equal(restacked, self.ymd) # more than 2 levels in the columns unstacked = self.ymd.unstack(1).unstack(1) result = unstacked.stack(1) expected = self.ymd.unstack() assert_frame_equal(result, expected) result = unstacked.stack(2) expected = self.ymd.unstack(1) assert_frame_equal(result, expected) result = unstacked.stack(0) expected = self.ymd.stack().unstack(1).unstack(1) assert_frame_equal(result, expected) # not all levels present in each echelon unstacked = self.ymd.unstack(2).ix[:, ::3] stacked = unstacked.stack().stack() ymd_stacked = self.ymd.stack() assert_series_equal(stacked, ymd_stacked.reindex(stacked.index)) def test_stack_mixed_dtype(self): df = self.frame.T df['foo', 'four'] = 'foo' df = df.sortlevel(1, axis=1) stacked = df.stack() assert_series_equal(stacked['foo'], df['foo'].stack()) self.assert_(stacked['bar'].dtype == np.float_) def test_swaplevel(self): swapped = self.frame['A'].swaplevel(0, 1) self.assert_(not swapped.index.equals(self.frame.index)) back = swapped.swaplevel(0, 1) self.assert_(back.index.equals(self.frame.index)) def test_insert_index(self): df = self.ymd[:5].T df[2000, 1, 10] = df[2000, 1, 7] self.assert_(isinstance(df.columns, MultiIndex)) self.assert_((df[2000, 1, 10] == df[2000, 1, 7]).all()) def test_alignment(self): pass def test_is_lexsorted(self): levels = [[0, 1], [0, 1, 2]] index = MultiIndex(levels=levels, labels=[[0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 1, 2]]) self.assert_(index.is_lexsorted()) index = MultiIndex(levels=levels, labels=[[0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 2, 1]]) self.assert_(not index.is_lexsorted()) index = MultiIndex(levels=levels, labels=[[0, 0, 1, 0, 1, 1], [0, 1, 0, 2, 2, 1]]) self.assert_(not index.is_lexsorted()) self.assert_(index.lexsort_depth == 0) def test_frame_getitem_view(self): df = self.frame.T df['foo'].values[:] = 0 self.assert_((df['foo'].values == 0).all()) # but not if it's mixed-type df['foo', 'four'] = 'foo' df = df.sortlevel(0, axis=1) df['foo']['one'] = 2 self.assert_((df['foo', 'one'] == 0).all()) def test_frame_getitem_not_sorted(self): df = self.frame.T df['foo', 'four'] = 'foo' arrays = [np.array(x) for x in zip(*df.columns.get_tuple_index())] result = df['foo'] result2 = df.ix[:, 'foo'] expected = df.reindex(columns=df.columns[arrays[0] == 'foo']) expected.columns = expected.columns.droplevel(0) assert_frame_equal(result, expected) assert_frame_equal(result2, expected) df = df.T result = df.xs('foo') result2 = df.ix['foo'] expected = df.reindex(df.index[arrays[0] == 'foo']) expected.index = expected.index.droplevel(0) assert_frame_equal(result, expected) assert_frame_equal(result2, expected) def test_series_getitem_not_sorted(self): arrays = [['bar', 'bar', 'baz', 'baz', 'qux', 'qux', 'foo', 'foo'], ['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']] tuples = zip(*arrays) index = MultiIndex.from_tuples(tuples) s = Series(randn(8), index=index) arrays = [np.array(x) for x in zip(*index.get_tuple_index())] result = s['qux'] result2 = s.ix['qux'] expected = s[arrays[0] == 'qux'] expected.index = expected.index.droplevel(0) assert_series_equal(result, expected) assert_series_equal(result2, expected)