def test_axis_dummies(self):
from pandas.core.reshape import make_axis_dummies
minor_dummies = make_axis_dummies(self.panel, "minor")
self.assertEqual(len(minor_dummies.columns), len(self.panel.index.levels[1]))
major_dummies = make_axis_dummies(self.panel, "major")
self.assertEqual(len(major_dummies.columns), len(self.panel.index.levels[0]))
mapping = {"A": "one", "B": "one", "C": "two", "D": "two"}
transformed = make_axis_dummies(self.panel, "minor", transform=mapping.get)
self.assertEqual(len(transformed.columns), 2)
self.assert_(np.array_equal(transformed.columns, ["one", "two"]))
def _add_entity_effects(self, panel):
"""
Add entity dummies to panel
Returns
-------
DataFrame
"""
from pandas.core.reshape import make_axis_dummies
if not self._entity_effects:
return panel
self.log('-- Adding entity fixed effect dummies')
dummies = make_axis_dummies(panel, 'minor')
if not self._use_all_dummies:
if 'entity' in self._dropped_dummies:
to_exclude = str(self._dropped_dummies.get('entity'))
else:
to_exclude = dummies.columns[0]
if to_exclude not in dummies.columns:
raise Exception('%s not in %s' % (to_exclude,
dummies.columns))
self.log('-- Excluding dummy for entity: %s' % to_exclude)
dummies = dummies.filter(dummies.columns.difference([to_exclude]))
dummies = dummies.add_prefix('FE_')
panel = panel.join(dummies)
return panel
def _add_entity_effects(self, panel):
"""
Add entity dummies to panel
Returns
-------
DataFrame
"""
from pandas.core.reshape import make_axis_dummies
if not self._entity_effects:
return panel
self.log('-- Adding entity fixed effect dummies')
dummies = make_axis_dummies(panel, 'minor')
if not self._use_all_dummies:
if 'entity' in self._dropped_dummies:
to_exclude = str(self._dropped_dummies.get('entity'))
else:
to_exclude = dummies.columns[0]
if to_exclude not in dummies.columns:
raise Exception('%s not in %s' % (to_exclude,
dummies.columns))
self.log('-- Excluding dummy for entity: %s' % to_exclude)
dummies = dummies.filter(dummies.columns - [to_exclude])
dummies = dummies.add_prefix('FE_')
panel = panel.join(dummies)
return panel
def test_get_dummies(self):
from pandas.core.reshape import make_column_dummies, make_axis_dummies
self.panel["Label"] = self.panel.index.labels[1]
minor_dummies = make_axis_dummies(self.panel, "minor")
dummies = make_column_dummies(self.panel, "Label")
self.assert_(np.array_equal(dummies.values, minor_dummies.values))
def test_get_dummies(self):
from pandas.core.reshape import make_column_dummies, make_axis_dummies
self.panel['Label'] = self.panel.index.labels[1]
minor_dummies = make_axis_dummies(self.panel, 'minor')
dummies = make_column_dummies(self.panel, 'Label')
self.assert_(np.array_equal(dummies.values, minor_dummies.values))
def _add_entity_effects(self, panel):
"""
Add entity dummies to panel
Returns
-------
DataFrame
"""
from pandas.core.reshape import make_axis_dummies
if not self._entity_effects:
return panel
self.log("-- Adding entity fixed effect dummies")
dummies = make_axis_dummies(panel, "minor")
if not self._use_all_dummies:
if "entity" in self._dropped_dummies:
to_exclude = str(self._dropped_dummies.get("entity"))
else:
to_exclude = dummies.columns[0]
if to_exclude not in dummies.columns:
raise Exception("%s not in %s" % (to_exclude, dummies.columns))
self.log("-- Excluding dummy for entity: %s" % to_exclude)
dummies = dummies.filter(dummies.columns - [to_exclude])
dummies = dummies.add_prefix("FE_")
panel = panel.join(dummies)
return panel
def test_get_dummies(self):
from pandas.core.reshape import get_dummies, make_axis_dummies
self.panel['Label'] = self.panel.index.labels[1]
minor_dummies = make_axis_dummies(self.panel, 'minor')
dummies = get_dummies(self.panel['Label'])
self.assert_(np.array_equal(dummies.values, minor_dummies.values))
def test_preserve_categorical_dtype(self):
# GH13854
for ordered in [False, True]:
cidx = pd.CategoricalIndex(list("xyz"), ordered=ordered)
midx = pd.MultiIndex(levels=[['a'], cidx],
labels=[[0, 0], [0, 1]])
df = DataFrame([[10, 11]], index=midx)
expected = DataFrame([[1.0, 0.0, 0.0], [0.0, 1.0, 0.0]],
index=midx, columns=cidx)
from pandas.core.reshape import make_axis_dummies
result = make_axis_dummies(df)
tm.assert_frame_equal(result, expected)
result = make_axis_dummies(df, transform=lambda x: x)
tm.assert_frame_equal(result, expected)
def test_preserve_categorical_dtype(self):
# GH13854
for ordered in [False, True]:
cidx = pd.CategoricalIndex(list("xyz"), ordered=ordered)
midx = pd.MultiIndex(levels=[['a'], cidx], labels=[[0, 0], [0, 1]])
df = DataFrame([[10, 11]], index=midx)
expected = DataFrame([[1.0, 0.0, 0.0], [0.0, 1.0, 0.0]],
index=midx,
columns=cidx)
from pandas.core.reshape import make_axis_dummies
result = make_axis_dummies(df)
tm.assert_frame_equal(result, expected)
result = make_axis_dummies(df, transform=lambda x: x)
tm.assert_frame_equal(result, expected)
def test_axis_dummies(self):
from pandas.core.reshape import make_axis_dummies
minor_dummies = make_axis_dummies(self.panel, 'minor')
self.assertEqual(len(minor_dummies.columns),
len(self.panel.index.levels[1]))
major_dummies = make_axis_dummies(self.panel, 'major')
self.assertEqual(len(major_dummies.columns),
len(self.panel.index.levels[0]))
mapping = {'A': 'one', 'B': 'one', 'C': 'two', 'D': 'two'}
transformed = make_axis_dummies(self.panel,
'minor',
transform=mapping.get)
self.assertEqual(len(transformed.columns), 2)
self.assert_(np.array_equal(transformed.columns, ['one', 'two']))
def test_axis_dummies(self):
from pandas.core.reshape import make_axis_dummies
minor_dummies = make_axis_dummies(self.panel, 'minor')
self.assertEqual(len(minor_dummies.columns),
len(self.panel.index.levels[1]))
major_dummies = make_axis_dummies(self.panel, 'major')
self.assertEqual(len(major_dummies.columns),
len(self.panel.index.levels[0]))
mapping = {'A' : 'one',
'B' : 'one',
'C' : 'two',
'D' : 'two'}
transformed = make_axis_dummies(self.panel, 'minor',
transform=mapping.get)
self.assertEqual(len(transformed.columns), 2)
self.assert_(np.array_equal(transformed.columns, ['one', 'two']))
