def test_isnull():
assert not isnull(1.)
assert isnull(None)
assert isnull(np.NaN)
assert not isnull(np.inf)
assert not isnull(-np.inf)
# series
for s in [tm.makeFloatSeries(),tm.makeStringSeries(),
tm.makeObjectSeries(),tm.makeTimeSeries(),tm.makePeriodSeries()]:
assert(isinstance(isnull(s), Series))
# frame
for df in [tm.makeTimeDataFrame(),tm.makePeriodFrame(),tm.makeMixedDataFrame()]:
result = isnull(df)
expected = df.apply(isnull)
tm.assert_frame_equal(result, expected)
# panel
for p in [ tm.makePanel(), tm.makePeriodPanel(), tm.add_nans(tm.makePanel()) ]:
result = isnull(p)
expected = p.apply(isnull)
tm.assert_panel_equal(result, expected)
# panel 4d
for p in [ tm.makePanel4D(), tm.add_nans_panel4d(tm.makePanel4D()) ]:
result = isnull(p)
expected = p.apply(isnull)
tm.assert_panel4d_equal(result, expected)
def test_squeeze(self):
# noop
for s in [
tm.makeFloatSeries(),
tm.makeStringSeries(),
tm.makeObjectSeries()
]:
tm.assert_series_equal(s.squeeze(), s)
for df in [tm.makeTimeDataFrame()]:
tm.assert_frame_equal(df.squeeze(), df)
with catch_warnings(record=True):
for p in [tm.makePanel()]:
tm.assert_panel_equal(p.squeeze(), p)
with catch_warnings(record=True):
for p4d in [tm.makePanel4D()]:
tm.assert_panel4d_equal(p4d.squeeze(), p4d)
# squeezing
df = tm.makeTimeDataFrame().reindex(columns=['A'])
tm.assert_series_equal(df.squeeze(), df['A'])
with catch_warnings(record=True):
p = tm.makePanel().reindex(items=['ItemA'])
tm.assert_frame_equal(p.squeeze(), p['ItemA'])
p = tm.makePanel().reindex(items=['ItemA'], minor_axis=['A'])
tm.assert_series_equal(p.squeeze(), p.loc['ItemA', :, 'A'])
with catch_warnings(record=True):
p4d = tm.makePanel4D().reindex(labels=['label1'])
tm.assert_panel_equal(p4d.squeeze(), p4d['label1'])
with catch_warnings(record=True):
p4d = tm.makePanel4D().reindex(labels=['label1'], items=['ItemA'])
tm.assert_frame_equal(p4d.squeeze(), p4d.loc['label1', 'ItemA'])
# don't fail with 0 length dimensions GH11229 & GH8999
empty_series = Series([], name='five')
empty_frame = DataFrame([empty_series])
with catch_warnings(record=True):
empty_panel = Panel({'six': empty_frame})
[
tm.assert_series_equal(empty_series, higher_dim.squeeze())
for higher_dim in [empty_series, empty_frame, empty_panel]
]
# axis argument
df = tm.makeTimeDataFrame(nper=1).iloc[:, :1]
assert df.shape == (1, 1)
tm.assert_series_equal(df.squeeze(axis=0), df.iloc[0])
tm.assert_series_equal(df.squeeze(axis='index'), df.iloc[0])
tm.assert_series_equal(df.squeeze(axis=1), df.iloc[:, 0])
tm.assert_series_equal(df.squeeze(axis='columns'), df.iloc[:, 0])
assert df.squeeze() == df.iloc[0, 0]
pytest.raises(ValueError, df.squeeze, axis=2)
pytest.raises(ValueError, df.squeeze, axis='x')
df = tm.makeTimeDataFrame(3)
tm.assert_frame_equal(df.squeeze(axis=0), df)
def test_comparisons(self):
with catch_warnings(record=True):
p1 = tm.makePanel4D()
p2 = tm.makePanel4D()
tp = p1.reindex(labels=p1.labels.tolist() + ['foo'])
p = p1[p1.labels[0]]
def test_comp(func):
result = func(p1, p2)
tm.assert_numpy_array_equal(result.values,
func(p1.values, p2.values))
# versus non-indexed same objs
pytest.raises(Exception, func, p1, tp)
# versus different objs
pytest.raises(Exception, func, p1, p)
result3 = func(self.panel4d, 0)
tm.assert_numpy_array_equal(result3.values,
func(self.panel4d.values, 0))
with np.errstate(invalid='ignore'):
test_comp(operator.eq)
test_comp(operator.ne)
test_comp(operator.lt)
test_comp(operator.gt)
test_comp(operator.ge)
test_comp(operator.le)
def test_isnull(self):
self.assertFalse(isnull(1.))
self.assertTrue(isnull(None))
self.assertTrue(isnull(np.NaN))
self.assertTrue(float('nan'))
self.assertFalse(isnull(np.inf))
self.assertFalse(isnull(-np.inf))
# series
for s in [tm.makeFloatSeries(), tm.makeStringSeries(),
tm.makeObjectSeries(), tm.makeTimeSeries(),
tm.makePeriodSeries()]:
self.assertIsInstance(isnull(s), Series)
# frame
for df in [tm.makeTimeDataFrame(), tm.makePeriodFrame(),
tm.makeMixedDataFrame()]:
result = isnull(df)
expected = df.apply(isnull)
tm.assert_frame_equal(result, expected)
# panel
with catch_warnings(record=True):
for p in [tm.makePanel(), tm.makePeriodPanel(),
tm.add_nans(tm.makePanel())]:
result = isnull(p)
expected = p.apply(isnull)
tm.assert_panel_equal(result, expected)
# panel 4d
with catch_warnings(record=True):
for p in [tm.makePanel4D(), tm.add_nans_panel4d(tm.makePanel4D())]:
result = isnull(p)
expected = p.apply(isnull)
tm.assert_panel4d_equal(result, expected)
def test_comparisons(self):
with catch_warnings(record=True):
p1 = tm.makePanel4D()
p2 = tm.makePanel4D()
tp = p1.reindex(labels=p1.labels.tolist() + ['foo'])
p = p1[p1.labels[0]]
def test_comp(func):
result = func(p1, p2)
tm.assert_numpy_array_equal(result.values,
func(p1.values, p2.values))
# versus non-indexed same objs
pytest.raises(Exception, func, p1, tp)
# versus different objs
pytest.raises(Exception, func, p1, p)
result3 = func(self.panel4d, 0)
tm.assert_numpy_array_equal(result3.values,
func(self.panel4d.values, 0))
with np.errstate(invalid='ignore'):
test_comp(operator.eq)
test_comp(operator.ne)
test_comp(operator.lt)
test_comp(operator.gt)
test_comp(operator.ge)
test_comp(operator.le)
def test_squeeze(self):
# noop
for s in [ tm.makeFloatSeries(), tm.makeStringSeries(), tm.makeObjectSeries() ]:
tm.assert_series_equal(s.squeeze(),s)
for df in [ tm.makeTimeDataFrame() ]:
tm.assert_frame_equal(df.squeeze(),df)
for p in [ tm.makePanel() ]:
tm.assert_panel_equal(p.squeeze(),p)
for p4d in [ tm.makePanel4D() ]:
tm.assert_panel4d_equal(p4d.squeeze(),p4d)
# squeezing
df = tm.makeTimeDataFrame().reindex(columns=['A'])
tm.assert_series_equal(df.squeeze(),df['A'])
p = tm.makePanel().reindex(items=['ItemA'])
tm.assert_frame_equal(p.squeeze(),p['ItemA'])
p = tm.makePanel().reindex(items=['ItemA'],minor_axis=['A'])
tm.assert_series_equal(p.squeeze(),p.ix['ItemA',:,'A'])
p4d = tm.makePanel4D().reindex(labels=['label1'])
tm.assert_panel_equal(p4d.squeeze(),p4d['label1'])
p4d = tm.makePanel4D().reindex(labels=['label1'],items=['ItemA'])
tm.assert_frame_equal(p4d.squeeze(),p4d.ix['label1','ItemA'])
def test_comparisons(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
p1 = tm.makePanel4D()
p2 = tm.makePanel4D()
tp = p1.reindex(labels=p1.labels.tolist() + ['foo'])
p = p1[p1.labels[0]]
def test_comp(func):
result = func(p1, p2)
self.assert_numpy_array_equal(result.values,
func(p1.values, p2.values))
# versus non-indexed same objs
self.assertRaises(Exception, func, p1, tp)
# versus different objs
self.assertRaises(Exception, func, p1, p)
result3 = func(self.panel4d, 0)
self.assert_numpy_array_equal(result3.values,
func(self.panel4d.values, 0))
with np.errstate(invalid='ignore'):
test_comp(operator.eq)
test_comp(operator.ne)
test_comp(operator.lt)
test_comp(operator.gt)
test_comp(operator.ge)
test_comp(operator.le)
def test_isnull(self):
self.assertFalse(isnull(1.))
self.assertTrue(isnull(None))
self.assertTrue(isnull(np.NaN))
self.assertTrue(float('nan'))
self.assertFalse(isnull(np.inf))
self.assertFalse(isnull(-np.inf))
# series
for s in [tm.makeFloatSeries(), tm.makeStringSeries(),
tm.makeObjectSeries(), tm.makeTimeSeries(),
tm.makePeriodSeries()]:
assert isinstance(isnull(s), Series)
# frame
for df in [tm.makeTimeDataFrame(), tm.makePeriodFrame(),
tm.makeMixedDataFrame()]:
result = isnull(df)
expected = df.apply(isnull)
tm.assert_frame_equal(result, expected)
# panel
with catch_warnings(record=True):
for p in [tm.makePanel(), tm.makePeriodPanel(),
tm.add_nans(tm.makePanel())]:
result = isnull(p)
expected = p.apply(isnull)
tm.assert_panel_equal(result, expected)
# panel 4d
with catch_warnings(record=True):
for p in [tm.makePanel4D(), tm.add_nans_panel4d(tm.makePanel4D())]:
result = isnull(p)
expected = p.apply(isnull)
tm.assert_panel4d_equal(result, expected)
def test_isnull():
assert not isnull(1.)
assert isnull(None)
assert isnull(np.NaN)
assert not isnull(np.inf)
assert not isnull(-np.inf)
# series
for s in [tm.makeFloatSeries(), tm.makeStringSeries(),
tm.makeObjectSeries(), tm.makeTimeSeries(),
tm.makePeriodSeries()]:
assert (isinstance(isnull(s), Series))
# frame
for df in [tm.makeTimeDataFrame(), tm.makePeriodFrame(),
tm.makeMixedDataFrame()]:
result = isnull(df)
expected = df.apply(isnull)
tm.assert_frame_equal(result, expected)
# panel
for p in [tm.makePanel(), tm.makePeriodPanel(), tm.add_nans(tm.makePanel())
]:
result = isnull(p)
expected = p.apply(isnull)
tm.assert_panel_equal(result, expected)
# panel 4d
for p in [tm.makePanel4D(), tm.add_nans_panel4d(tm.makePanel4D())]:
result = isnull(p)
expected = p.apply(isnull)
tm.assert_panel4d_equal(result, expected)
def test_comparisons(self):
p1 = tm.makePanel4D()
p2 = tm.makePanel4D()
tp = p1.reindex(labels=p1.labels.tolist() + ['foo'])
p = p1[p1.labels[0]]
def test_comp(func):
result = func(p1, p2)
self.assert_numpy_array_equal(result.values,
func(p1.values, p2.values))
# versus non-indexed same objs
self.assertRaises(Exception, func, p1, tp)
# versus different objs
self.assertRaises(Exception, func, p1, p)
result3 = func(self.panel4d, 0)
self.assert_numpy_array_equal(result3.values,
func(self.panel4d.values, 0))
test_comp(operator.eq)
test_comp(operator.ne)
test_comp(operator.lt)
test_comp(operator.gt)
test_comp(operator.ge)
test_comp(operator.le)
def test_squeeze(self):
# noop
for s in [
tm.makeFloatSeries(),
tm.makeStringSeries(),
tm.makeObjectSeries()
]:
tm.assert_series_equal(s.squeeze(), s)
for df in [tm.makeTimeDataFrame()]:
tm.assert_frame_equal(df.squeeze(), df)
for p in [tm.makePanel()]:
tm.assert_panel_equal(p.squeeze(), p)
for p4d in [tm.makePanel4D()]:
tm.assert_panel4d_equal(p4d.squeeze(), p4d)
# squeezing
df = tm.makeTimeDataFrame().reindex(columns=['A'])
tm.assert_series_equal(df.squeeze(), df['A'])
p = tm.makePanel().reindex(items=['ItemA'])
tm.assert_frame_equal(p.squeeze(), p['ItemA'])
p = tm.makePanel().reindex(items=['ItemA'], minor_axis=['A'])
tm.assert_series_equal(p.squeeze(), p.ix['ItemA', :, 'A'])
p4d = tm.makePanel4D().reindex(labels=['label1'])
tm.assert_panel_equal(p4d.squeeze(), p4d['label1'])
p4d = tm.makePanel4D().reindex(labels=['label1'], items=['ItemA'])
tm.assert_frame_equal(p4d.squeeze(), p4d.ix['label1', 'ItemA'])
def test_comparisons(self):
p1 = tm.makePanel4D()
p2 = tm.makePanel4D()
tp = p1.reindex(labels=p1.labels + ['foo'])
p = p1[p1.labels[0]]
def test_comp(func):
result = func(p1, p2)
self.assert_(np.array_equal(result.values,
func(p1.values, p2.values)))
# versus non-indexed same objs
self.assertRaises(Exception, func, p1, tp)
# versus different objs
self.assertRaises(Exception, func, p1, p)
result3 = func(self.panel4d, 0)
self.assert_(np.array_equal(result3.values,
func(self.panel4d.values, 0)))
test_comp(operator.eq)
test_comp(operator.ne)
test_comp(operator.lt)
test_comp(operator.gt)
test_comp(operator.ge)
test_comp(operator.le)
def test_squeeze(self):
# noop
for s in [tm.makeFloatSeries(), tm.makeStringSeries(),
tm.makeObjectSeries()]:
tm.assert_series_equal(s.squeeze(), s)
for df in [tm.makeTimeDataFrame()]:
tm.assert_frame_equal(df.squeeze(), df)
with catch_warnings(record=True):
for p in [tm.makePanel()]:
tm.assert_panel_equal(p.squeeze(), p)
with catch_warnings(record=True):
for p4d in [tm.makePanel4D()]:
tm.assert_panel4d_equal(p4d.squeeze(), p4d)
# squeezing
df = tm.makeTimeDataFrame().reindex(columns=['A'])
tm.assert_series_equal(df.squeeze(), df['A'])
with catch_warnings(record=True):
p = tm.makePanel().reindex(items=['ItemA'])
tm.assert_frame_equal(p.squeeze(), p['ItemA'])
p = tm.makePanel().reindex(items=['ItemA'], minor_axis=['A'])
tm.assert_series_equal(p.squeeze(), p.loc['ItemA', :, 'A'])
with catch_warnings(record=True):
p4d = tm.makePanel4D().reindex(labels=['label1'])
tm.assert_panel_equal(p4d.squeeze(), p4d['label1'])
with catch_warnings(record=True):
p4d = tm.makePanel4D().reindex(labels=['label1'], items=['ItemA'])
tm.assert_frame_equal(p4d.squeeze(), p4d.loc['label1', 'ItemA'])
# don't fail with 0 length dimensions GH11229 & GH8999
empty_series = Series([], name='five')
empty_frame = DataFrame([empty_series])
with catch_warnings(record=True):
empty_panel = Panel({'six': empty_frame})
[tm.assert_series_equal(empty_series, higher_dim.squeeze())
for higher_dim in [empty_series, empty_frame, empty_panel]]
# axis argument
df = tm.makeTimeDataFrame(nper=1).iloc[:, :1]
assert df.shape == (1, 1)
tm.assert_series_equal(df.squeeze(axis=0), df.iloc[0])
tm.assert_series_equal(df.squeeze(axis='index'), df.iloc[0])
tm.assert_series_equal(df.squeeze(axis=1), df.iloc[:, 0])
tm.assert_series_equal(df.squeeze(axis='columns'), df.iloc[:, 0])
assert df.squeeze() == df.iloc[0, 0]
pytest.raises(ValueError, df.squeeze, axis=2)
pytest.raises(ValueError, df.squeeze, axis='x')
df = tm.makeTimeDataFrame(3)
tm.assert_frame_equal(df.squeeze(axis=0), df)
def test_ndim_indexables(self):
""" test using ndim tables in new ways"""
p4d = tm.makePanel4D()
# append then change (will take existing schema)
self.store.remove('p4d')
self.store.append('p4d', p4d.ix[:,:,:10,:], axes=['items','major_axis','minor_axis'])
self.store.append('p4d', p4d.ix[:,:,10:,:], axes=['labels','items','major_axis'])
# pass incorrect number of axes
self.store.remove('p4d')
self.assertRaises(Exception, self.store.append, 'p4d', p4d.ix[:,:,:10,:], axes=['major_axis','minor_axis'])
# different than default indexables
self.store.remove('p4d')
self.store.append('p4d', p4d.ix[:,:,:10,:], axes=[0,2,3])
self.store.append('p4d', p4d.ix[:,:,10:,:], axes=[0,2,3])
tm.assert_panel4d_equal(self.store['p4d'], p4d)
# partial selection
result = self.store.select('p4d',['labels=l1'])
expected = p4d.reindex(labels = ['l1'])
tm.assert_panel4d_equal(result, expected)
# partial selection2
result = self.store.select('p4d',[Term('labels=l1'), Term('items=ItemA'), Term('minor_axis=B')])
expected = p4d.reindex(labels = ['l1'], items = ['ItemA'], minor_axis = ['B'])
tm.assert_panel4d_equal(result, expected)
# non-existant partial selection
result = self.store.select('p4d',[Term('labels=l1'), Term('items=Item1'), Term('minor_axis=B')])
expected = p4d.reindex(labels = ['l1'], items = [], minor_axis = ['B'])
tm.assert_panel4d_equal(result, expected)
def test_take(self):
indices = [1, 5, -2, 6, 3, -1]
for s in [tm.makeFloatSeries(), tm.makeStringSeries(),
tm.makeObjectSeries()]:
out = s.take(indices)
expected = Series(data=s.values.take(indices),
index=s.index.take(indices), dtype=s.dtype)
tm.assert_series_equal(out, expected)
for df in [tm.makeTimeDataFrame()]:
out = df.take(indices)
expected = DataFrame(data=df.values.take(indices, axis=0),
index=df.index.take(indices),
columns=df.columns)
tm.assert_frame_equal(out, expected)
indices = [-3, 2, 0, 1]
with catch_warnings(record=True):
for p in [tm.makePanel()]:
out = p.take(indices)
expected = Panel(data=p.values.take(indices, axis=0),
items=p.items.take(indices),
major_axis=p.major_axis,
minor_axis=p.minor_axis)
tm.assert_panel_equal(out, expected)
with catch_warnings(record=True):
for p4d in [tm.makePanel4D()]:
out = p4d.take(indices)
expected = Panel4D(data=p4d.values.take(indices, axis=0),
labels=p4d.labels.take(indices),
major_axis=p4d.major_axis,
minor_axis=p4d.minor_axis,
items=p4d.items)
tm.assert_panel4d_equal(out, expected)
def test_numpy_transpose(self):
msg = "the 'axes' parameter is not supported"
s = tm.makeFloatSeries()
tm.assert_series_equal(
np.transpose(s), s)
tm.assert_raises_regex(ValueError, msg,
np.transpose, s, axes=1)
df = tm.makeTimeDataFrame()
tm.assert_frame_equal(np.transpose(
np.transpose(df)), df)
tm.assert_raises_regex(ValueError, msg,
np.transpose, df, axes=1)
with catch_warnings(record=True):
p = tm.makePanel()
tm.assert_panel_equal(np.transpose(
np.transpose(p, axes=(2, 0, 1)),
axes=(1, 2, 0)), p)
with catch_warnings(record=True):
p4d = tm.makePanel4D()
tm.assert_panel4d_equal(np.transpose(
np.transpose(p4d, axes=(2, 0, 3, 1)),
axes=(1, 3, 0, 2)), p4d)
def test_take_invalid_kwargs(self):
indices = [-3, 2, 0, 1]
s = tm.makeFloatSeries()
df = tm.makeTimeDataFrame()
with catch_warnings(record=True):
p = tm.makePanel()
p4d = tm.makePanel4D()
for obj in (s, df, p, p4d):
msg = r"take\(\) got an unexpected keyword argument 'foo'"
tm.assert_raises_regex(TypeError, msg, obj.take, indices, foo=2)
msg = "the 'out' parameter is not supported"
tm.assert_raises_regex(ValueError,
msg,
obj.take,
indices,
out=indices)
msg = "the 'mode' parameter is not supported"
tm.assert_raises_regex(ValueError,
msg,
obj.take,
indices,
mode='clip')
def test_ndim_indexables(self):
""" test using ndim tables in new ways"""
p4d = tm.makePanel4D()
def check_indexers(key, indexers):
for i,idx in enumerate(indexers):
self.assert_(getattr(getattr(self.store.root,key).table.description,idx)._v_pos == i)
# append then change (will take existing schema)
indexers = ['items','major_axis','minor_axis']
self.store.remove('p4d')
self.store.append('p4d', p4d.ix[:,:,:10,:], axes=indexers)
self.store.append('p4d', p4d.ix[:,:,10:,:])
tm.assert_panel4d_equal(self.store.select('p4d'),p4d)
check_indexers('p4d',indexers)
# same as above, but try to append with differnt axes
self.store.remove('p4d')
self.store.append('p4d', p4d.ix[:,:,:10,:], axes=indexers)
self.store.append('p4d', p4d.ix[:,:,10:,:], axes=['labels','items','major_axis'])
tm.assert_panel4d_equal(self.store.select('p4d'),p4d)
check_indexers('p4d',indexers)
# pass incorrect number of axes
self.store.remove('p4d')
self.assertRaises(Exception, self.store.append, 'p4d', p4d.ix[:,:,:10,:], axes=['major_axis','minor_axis'])
# different than default indexables #1
indexers = ['labels','major_axis','minor_axis']
self.store.remove('p4d')
self.store.append('p4d', p4d.ix[:,:,:10,:], axes=indexers)
self.store.append('p4d', p4d.ix[:,:,10:,:])
tm.assert_panel4d_equal(self.store['p4d'], p4d)
check_indexers('p4d',indexers)
# different than default indexables #2
indexers = ['major_axis','labels','minor_axis']
self.store.remove('p4d')
self.store.append('p4d', p4d.ix[:,:,:10,:], axes=indexers)
self.store.append('p4d', p4d.ix[:,:,10:,:])
tm.assert_panel4d_equal(self.store['p4d'], p4d)
check_indexers('p4d',indexers)
# partial selection
result = self.store.select('p4d',['labels=l1'])
expected = p4d.reindex(labels = ['l1'])
tm.assert_panel4d_equal(result, expected)
# partial selection2
result = self.store.select('p4d',[Term('labels=l1'), Term('items=ItemA'), Term('minor_axis=B')])
expected = p4d.reindex(labels = ['l1'], items = ['ItemA'], minor_axis = ['B'])
tm.assert_panel4d_equal(result, expected)
# non-existant partial selection
result = self.store.select('p4d',[Term('labels=l1'), Term('items=Item1'), Term('minor_axis=B')])
expected = p4d.reindex(labels = ['l1'], items = [], minor_axis = ['B'])
tm.assert_panel4d_equal(result, expected)
def test_isna_isnull(self, isna_f):
assert not isna_f(1.)
assert isna_f(None)
assert isna_f(np.NaN)
assert float('nan')
assert not isna_f(np.inf)
assert not isna_f(-np.inf)
# series
for s in [
tm.makeFloatSeries(),
tm.makeStringSeries(),
tm.makeObjectSeries(),
tm.makeTimeSeries(),
tm.makePeriodSeries()
]:
assert isinstance(isna_f(s), Series)
# frame
for df in [
tm.makeTimeDataFrame(),
tm.makePeriodFrame(),
tm.makeMixedDataFrame()
]:
result = isna_f(df)
expected = df.apply(isna_f)
tm.assert_frame_equal(result, expected)
# panel
with catch_warnings(record=True):
for p in [
tm.makePanel(),
tm.makePeriodPanel(),
tm.add_nans(tm.makePanel())
]:
result = isna_f(p)
expected = p.apply(isna_f)
tm.assert_panel_equal(result, expected)
# panel 4d
with catch_warnings(record=True):
for p in [tm.makePanel4D(), tm.add_nans_panel4d(tm.makePanel4D())]:
result = isna_f(p)
expected = p.apply(isna_f)
tm.assert_panel4d_equal(result, expected)
def _make_one_p4d():
wp = tm.makePanel4D()
wp['obj1'] = 'foo'
wp['obj2'] = 'bar'
wp['bool1'] = wp['l1'] > 0
wp['bool2'] = wp['l2'] > 0
wp['int1'] = 1
wp['int2'] = 2
return wp.consolidate()
def _make_one_p4d():
wp = tm.makePanel4D()
wp['obj1'] = 'foo'
wp['obj2'] = 'bar'
wp['bool1'] = wp['l1'] > 0
wp['bool2'] = wp['l2'] > 0
wp['int1'] = 1
wp['int2'] = 2
return wp.consolidate()
def test_terms(self):
wp = tm.makePanel()
p4d = tm.makePanel4D()
self.store.put('wp', wp, table=True)
self.store.put('p4d', p4d, table=True)
# some invalid terms
terms = [
[ 'minor', ['A','B'] ],
[ 'index', ['20121114'] ],
[ 'index', ['20121114', '20121114'] ],
]
for t in terms:
self.assertRaises(Exception, self.store.select, 'wp', t)
self.assertRaises(Exception, Term.__init__)
self.assertRaises(Exception, Term.__init__, 'blah')
self.assertRaises(Exception, Term.__init__, 'index')
self.assertRaises(Exception, Term.__init__, 'index', '==')
self.assertRaises(Exception, Term.__init__, 'index', '>', 5)
# panel
result = self.store.select('wp',[ Term('major_axis<20000108'), Term('minor_axis', '=', ['A','B']) ])
expected = wp.truncate(after='20000108').reindex(minor=['A', 'B'])
tm.assert_panel_equal(result, expected)
# p4d
result = self.store.select('p4d',[ Term('major_axis<20000108'), Term('minor_axis', '=', ['A','B']) ])
expected = p4d.truncate(after='20000108').reindex(minor=['A', 'B'])
tm.assert_panel4d_equal(result, expected)
# valid terms
terms = [
dict(field = 'major_axis', op = '>', value = '20121114'),
('major_axis', '20121114'),
('major_axis', '>', '20121114'),
(('major_axis', ['20121114','20121114']),),
('major_axis', datetime(2012,11,14)),
'major_axis>20121114',
'major_axis>20121114',
'major_axis>20121114',
(('minor_axis', ['A','B']),),
(('minor_axis', ['A','B']),),
((('minor_axis', ['A','B']),),),
]
for t in terms:
self.store.select('wp', t)
self.store.select('p4d', t)
def test_panel4d_concat(self):
p4d = tm.makePanel4D()
p1 = p4d.ix[:, :, :5, :]
p2 = p4d.ix[:, :, 5:, :]
result = concat([p1, p2], axis=2)
tm.assert_panel4d_equal(result, p4d)
p1 = p4d.ix[:, :, :, :2]
p2 = p4d.ix[:, :, :, 2:]
result = concat([p1, p2], axis=3)
tm.assert_panel4d_equal(result, p4d)
def test_panel4d_concat(self):
p4d = tm.makePanel4D()
p1 = p4d.ix[:, :, :5, :]
p2 = p4d.ix[:, :, 5:, :]
result = concat([p1, p2], axis=2)
tm.assert_panel4d_equal(result, p4d)
p1 = p4d.ix[:, :, :, :2]
p2 = p4d.ix[:, :, :, 2:]
result = concat([p1, p2], axis=3)
tm.assert_panel4d_equal(result, p4d)
def test_panel4d_concat(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
p4d = tm.makePanel4D()
p1 = p4d.ix[:, :, :5, :]
p2 = p4d.ix[:, :, 5:, :]
result = concat([p1, p2], axis=2)
tm.assert_panel4d_equal(result, p4d)
p1 = p4d.ix[:, :, :, :2]
p2 = p4d.ix[:, :, :, 2:]
result = concat([p1, p2], axis=3)
tm.assert_panel4d_equal(result, p4d)
def test_panel4d_concat_mixed_type(self):
p4d = tm.makePanel4D()
# if things are a bit misbehaved
p1 = p4d.ix[:, :2, :, :2]
p2 = p4d.ix[:, :, :, 2:]
p1['L5'] = 'baz'
result = concat([p1, p2], axis=3)
p2['L5'] = np.nan
expected = concat([p1, p2], axis=3)
expected = expected.ix[result.labels]
tm.assert_panel4d_equal(result, expected)
def test_panel4d_concat_mixed_type(self):
p4d = tm.makePanel4D()
# if things are a bit misbehaved
p1 = p4d.ix[:, :2, :, :2]
p2 = p4d.ix[:, :, :, 2:]
p1['L5'] = 'baz'
result = concat([p1, p2], axis=3)
p2['L5'] = np.nan
expected = concat([p1, p2], axis=3)
expected = expected.ix[result.labels]
tm.assert_panel4d_equal(result, expected)
def test_panel4d_concat_mixed_type(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
p4d = tm.makePanel4D()
# if things are a bit misbehaved
p1 = p4d.ix[:, :2, :, :2]
p2 = p4d.ix[:, :, :, 2:]
p1['L5'] = 'baz'
result = concat([p1, p2], axis=3)
p2['L5'] = np.nan
expected = concat([p1, p2], axis=3)
expected = expected.ix[result.labels]
tm.assert_panel4d_equal(result, expected)
def test_to_xarray(self):
from xarray import DataArray
with catch_warnings(record=True):
p = tm.makePanel4D()
result = p.to_xarray()
assert isinstance(result, DataArray)
assert len(result.coords) == 4
assert_almost_equal(list(result.coords.keys()),
['labels', 'items', 'major_axis',
'minor_axis'])
assert len(result.dims) == 4
# non-convertible
pytest.raises(ValueError, lambda: result.to_pandas())
def test_append(self):
pth = '__test_append__.h5'
try:
store = HDFStore(pth)
df = tm.makeTimeDataFrame()
store.append('df1', df[:10])
store.append('df1', df[10:])
tm.assert_frame_equal(store['df1'], df)
store.put('df2', df[:10], table=True)
store.append('df2', df[10:])
tm.assert_frame_equal(store['df2'], df)
store.append('/df3', df[:10])
store.append('/df3', df[10:])
tm.assert_frame_equal(store['df3'], df)
# this is allowed by almost always don't want to do it
import warnings
import tables
warnings.filterwarnings('ignore', category=tables.NaturalNameWarning)
store.append('/df3 foo', df[:10])
store.append('/df3 foo', df[10:])
tm.assert_frame_equal(store['df3 foo'], df)
warnings.filterwarnings('always', category=tables.NaturalNameWarning)
# panel
wp = tm.makePanel()
store.append('wp1', wp.ix[:,:10,:])
store.append('wp1', wp.ix[:,10:,:])
tm.assert_panel_equal(store['wp1'], wp)
# ndim
p4d = tm.makePanel4D()
store.append('p4d', p4d.ix[:,:,:10,:])
store.append('p4d', p4d.ix[:,:,10:,:])
tm.assert_panel4d_equal(store['p4d'], p4d)
except:
raise
finally:
store.close()
os.remove(pth)
def test_append(self):
df = tm.makeTimeDataFrame()
self.store.remove('df1')
self.store.append('df1', df[:10])
self.store.append('df1', df[10:])
tm.assert_frame_equal(self.store['df1'], df)
self.store.remove('df2')
self.store.put('df2', df[:10], table=True)
self.store.append('df2', df[10:])
tm.assert_frame_equal(self.store['df2'], df)
self.store.remove('df3')
self.store.append('/df3', df[:10])
self.store.append('/df3', df[10:])
tm.assert_frame_equal(self.store['df3'], df)
# this is allowed by almost always don't want to do it
warnings.filterwarnings('ignore', category=tables.NaturalNameWarning)
self.store.remove('/df3 foo')
self.store.append('/df3 foo', df[:10])
self.store.append('/df3 foo', df[10:])
tm.assert_frame_equal(self.store['df3 foo'], df)
warnings.filterwarnings('always', category=tables.NaturalNameWarning)
# panel
wp = tm.makePanel()
self.store.remove('wp1')
self.store.append('wp1', wp.ix[:,:10,:])
self.store.append('wp1', wp.ix[:,10:,:])
tm.assert_panel_equal(self.store['wp1'], wp)
# ndim
p4d = tm.makePanel4D()
self.store.remove('p4d')
self.store.append('p4d', p4d.ix[:,:,:10,:])
self.store.append('p4d', p4d.ix[:,:,10:,:])
tm.assert_panel4d_equal(self.store['p4d'], p4d)
# test using axis labels
self.store.remove('p4d')
self.store.append('p4d', p4d.ix[:,:,:10,:], axes=['items','major_axis','minor_axis'])
self.store.append('p4d', p4d.ix[:,:,10:,:], axes=['items','major_axis','minor_axis'])
tm.assert_panel4d_equal(self.store['p4d'], p4d)
def test_take_invalid_kwargs(self):
indices = [-3, 2, 0, 1]
s = tm.makeFloatSeries()
df = tm.makeTimeDataFrame()
with catch_warnings(record=True):
p = tm.makePanel()
p4d = tm.makePanel4D()
for obj in (s, df, p, p4d):
msg = r"take\(\) got an unexpected keyword argument 'foo'"
tm.assert_raises_regex(TypeError, msg, obj.take,
indices, foo=2)
msg = "the 'out' parameter is not supported"
tm.assert_raises_regex(ValueError, msg, obj.take,
indices, out=indices)
msg = "the 'mode' parameter is not supported"
tm.assert_raises_regex(ValueError, msg, obj.take,
indices, mode='clip')
def test_numpy_transpose(self):
msg = "the 'axes' parameter is not supported"
s = tm.makeFloatSeries()
tm.assert_series_equal(np.transpose(s), s)
tm.assert_raises_regex(ValueError, msg, np.transpose, s, axes=1)
df = tm.makeTimeDataFrame()
tm.assert_frame_equal(np.transpose(np.transpose(df)), df)
tm.assert_raises_regex(ValueError, msg, np.transpose, df, axes=1)
with catch_warnings(record=True):
p = tm.makePanel()
tm.assert_panel_equal(
np.transpose(np.transpose(p, axes=(2, 0, 1)), axes=(1, 2, 0)),
p)
with catch_warnings(record=True):
p4d = tm.makePanel4D()
tm.assert_panel4d_equal(
np.transpose(np.transpose(p4d, axes=(2, 0, 3, 1)),
axes=(1, 3, 0, 2)), p4d)
def test_take(self):
indices = [1, 5, -2, 6, 3, -1]
for s in [
tm.makeFloatSeries(),
tm.makeStringSeries(),
tm.makeObjectSeries()
]:
out = s.take(indices)
expected = Series(data=s.values.take(indices),
index=s.index.take(indices),
dtype=s.dtype)
tm.assert_series_equal(out, expected)
for df in [tm.makeTimeDataFrame()]:
out = df.take(indices)
expected = DataFrame(data=df.values.take(indices, axis=0),
index=df.index.take(indices),
columns=df.columns)
tm.assert_frame_equal(out, expected)
indices = [-3, 2, 0, 1]
with catch_warnings(record=True):
for p in [tm.makePanel()]:
out = p.take(indices)
expected = Panel(data=p.values.take(indices, axis=0),
items=p.items.take(indices),
major_axis=p.major_axis,
minor_axis=p.minor_axis)
tm.assert_panel_equal(out, expected)
with catch_warnings(record=True):
for p4d in [tm.makePanel4D()]:
out = p4d.take(indices)
expected = Panel4D(data=p4d.values.take(indices, axis=0),
labels=p4d.labels.take(indices),
major_axis=p4d.major_axis,
minor_axis=p4d.minor_axis,
items=p4d.items)
tm.assert_panel4d_equal(out, expected)
def test_transpose(self):
msg = (r"transpose\(\) got multiple values for "
r"keyword argument 'axes'")
for s in [tm.makeFloatSeries(), tm.makeStringSeries(),
tm.makeObjectSeries()]:
# calls implementation in pandas/core/base.py
tm.assert_series_equal(s.transpose(), s)
for df in [tm.makeTimeDataFrame()]:
tm.assert_frame_equal(df.transpose().transpose(), df)
with catch_warnings(record=True):
for p in [tm.makePanel()]:
tm.assert_panel_equal(p.transpose(2, 0, 1)
.transpose(1, 2, 0), p)
tm.assert_raises_regex(TypeError, msg, p.transpose,
2, 0, 1, axes=(2, 0, 1))
with catch_warnings(record=True):
for p4d in [tm.makePanel4D()]:
tm.assert_panel4d_equal(p4d.transpose(2, 0, 3, 1)
.transpose(1, 3, 0, 2), p4d)
tm.assert_raises_regex(TypeError, msg, p4d.transpose,
2, 0, 3, 1, axes=(2, 0, 3, 1))
def test_transpose(self):
msg = (r"transpose\(\) got multiple values for "
r"keyword argument 'axes'")
for s in [
tm.makeFloatSeries(),
tm.makeStringSeries(),
tm.makeObjectSeries()
]:
# calls implementation in pandas/core/base.py
tm.assert_series_equal(s.transpose(), s)
for df in [tm.makeTimeDataFrame()]:
tm.assert_frame_equal(df.transpose().transpose(), df)
with catch_warnings(record=True):
for p in [tm.makePanel()]:
tm.assert_panel_equal(
p.transpose(2, 0, 1).transpose(1, 2, 0), p)
tm.assert_raises_regex(TypeError,
msg,
p.transpose,
2,
0,
1,
axes=(2, 0, 1))
with catch_warnings(record=True):
for p4d in [tm.makePanel4D()]:
tm.assert_panel4d_equal(
p4d.transpose(2, 0, 3, 1).transpose(1, 3, 0, 2), p4d)
tm.assert_raises_regex(TypeError,
msg,
p4d.transpose,
2,
0,
3,
1,
axes=(2, 0, 3, 1))
def setup_method(self, method):
with catch_warnings(record=True):
self.panel4d = tm.makePanel4D(nper=8)
add_nans(self.panel4d)
def test_panel4d(self):
with catch_warnings(record=True):
self.run_panel(tm.makePanel4D(), np.random.randn() + 0.5,
assert_func=assert_panel4d_equal, binary_comp=3)
def test_raise_on_panel4d_with_multiindex(self, parser, engine):
tm.skip_if_no_ne()
p4d = tm.makePanel4D(7)
p4d.items = tm.makeCustomIndex(len(p4d.items), nlevels=2)
with pytest.raises(NotImplementedError):
pd.eval('p4d + 1', parser=parser, engine=engine)
def test_panel4d(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
self.run_panel(tm.makePanel4D(), np.random.randn() + 0.5,
assert_func=assert_panel4d_equal, binary_comp=3)
def test_panel4d(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
self.run_panel(tm.makePanel4D(), np.random.randn() + 0.5,
assert_func=assert_panel4d_equal, binary_comp=3)
def setUp(self):
self.panel4d = tm.makePanel4D(nper=8)
add_nans(self.panel4d)
def test_ndim_indexables(self):
""" test using ndim tables in new ways"""
p4d = tm.makePanel4D()
def check_indexers(key, indexers):
for i, idx in enumerate(indexers):
self.assert_(
getattr(
getattr(self.store.root, key).table.description,
idx)._v_pos == i)
# append then change (will take existing schema)
indexers = ['items', 'major_axis', 'minor_axis']
self.store.remove('p4d')
self.store.append('p4d', p4d.ix[:, :, :10, :], axes=indexers)
self.store.append('p4d', p4d.ix[:, :, 10:, :])
tm.assert_panel4d_equal(self.store.select('p4d'), p4d)
check_indexers('p4d', indexers)
# same as above, but try to append with differnt axes
self.store.remove('p4d')
self.store.append('p4d', p4d.ix[:, :, :10, :], axes=indexers)
self.store.append('p4d',
p4d.ix[:, :, 10:, :],
axes=['labels', 'items', 'major_axis'])
tm.assert_panel4d_equal(self.store.select('p4d'), p4d)
check_indexers('p4d', indexers)
# pass incorrect number of axes
self.store.remove('p4d')
self.assertRaises(Exception,
self.store.append,
'p4d',
p4d.ix[:, :, :10, :],
axes=['major_axis', 'minor_axis'])
# different than default indexables #1
indexers = ['labels', 'major_axis', 'minor_axis']
self.store.remove('p4d')
self.store.append('p4d', p4d.ix[:, :, :10, :], axes=indexers)
self.store.append('p4d', p4d.ix[:, :, 10:, :])
tm.assert_panel4d_equal(self.store['p4d'], p4d)
check_indexers('p4d', indexers)
# different than default indexables #2
indexers = ['major_axis', 'labels', 'minor_axis']
self.store.remove('p4d')
self.store.append('p4d', p4d.ix[:, :, :10, :], axes=indexers)
self.store.append('p4d', p4d.ix[:, :, 10:, :])
tm.assert_panel4d_equal(self.store['p4d'], p4d)
check_indexers('p4d', indexers)
# partial selection
result = self.store.select('p4d', ['labels=l1'])
expected = p4d.reindex(labels=['l1'])
tm.assert_panel4d_equal(result, expected)
# partial selection2
result = self.store.select(
'p4d',
[Term('labels=l1'),
Term('items=ItemA'),
Term('minor_axis=B')])
expected = p4d.reindex(labels=['l1'],
items=['ItemA'],
minor_axis=['B'])
tm.assert_panel4d_equal(result, expected)
# non-existant partial selection
result = self.store.select(
'p4d',
[Term('labels=l1'),
Term('items=Item1'),
Term('minor_axis=B')])
expected = p4d.reindex(labels=['l1'], items=[], minor_axis=['B'])
tm.assert_panel4d_equal(result, expected)
def test_terms(self):
wp = tm.makePanel()
p4d = tm.makePanel4D()
self.store.put('wp', wp, table=True)
self.store.put('p4d', p4d, table=True)
# some invalid terms
terms = [
['minor', ['A', 'B']],
['index', ['20121114']],
['index', ['20121114', '20121114']],
]
for t in terms:
self.assertRaises(Exception, self.store.select, 'wp', t)
self.assertRaises(Exception, Term.__init__)
self.assertRaises(Exception, Term.__init__, 'blah')
self.assertRaises(Exception, Term.__init__, 'index')
self.assertRaises(Exception, Term.__init__, 'index', '==')
self.assertRaises(Exception, Term.__init__, 'index', '>', 5)
# panel
result = self.store.select(
'wp',
[Term('major_axis<20000108'),
Term('minor_axis', '=', ['A', 'B'])])
expected = wp.truncate(after='20000108').reindex(minor=['A', 'B'])
tm.assert_panel_equal(result, expected)
# p4d
result = self.store.select('p4d', [
Term('major_axis<20000108'),
Term('minor_axis', '=', ['A', 'B']),
Term('items', '=', ['ItemA', 'ItemB'])
])
expected = p4d.truncate(after='20000108').reindex(
minor=['A', 'B'], items=['ItemA', 'ItemB'])
tm.assert_panel4d_equal(result, expected)
# valid terms
terms = [
dict(field='major_axis', op='>', value='20121114'),
('major_axis', '20121114'),
('major_axis', '>', '20121114'),
(('major_axis', ['20121114', '20121114']), ),
('major_axis', datetime(2012, 11, 14)),
'major_axis>20121114',
'major_axis>20121114',
'major_axis>20121114',
(('minor_axis', ['A', 'B']), ),
(('minor_axis', ['A', 'B']), ),
((('minor_axis', ['A', 'B']), ), ),
(('items', ['ItemA', 'ItemB']), ),
('items=ItemA'),
]
for t in terms:
self.store.select('wp', t)
self.store.select('p4d', t)
# valid for p4d only
terms = [
(('labels', '=', ['l1', 'l2']), ),
Term('labels', '=', ['l1', 'l2']),
]
for t in terms:
self.store.select('p4d', t)
def check_raise_on_panel4d_with_multiindex(self, parser, engine):
tm.skip_if_no_ne()
p4d = tm.makePanel4D(7)
p4d.items = tm.makeCustomIndex(len(p4d.items), nlevels=2)
with tm.assertRaises(NotImplementedError):
pd.eval('p4d + 1', parser=parser, engine=engine)
def test_panel4d(self):
with catch_warnings(record=True):
self.run_panel(tm.makePanel4D(),
np.random.randn() + 0.5,
assert_func=assert_panel4d_equal,
binary_comp=3)
def setUp(self):
with catch_warnings(record=True):
self.panel4d = tm.makePanel4D(nper=8)
add_nans(self.panel4d)
def setUp(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
self.panel4d = tm.makePanel4D(nper=8)
add_nans(self.panel4d)
def setUp(self):
self.panel4d = tm.makePanel4D(nper=8)
add_nans(self.panel4d)
def setup_method(self, method):
with catch_warnings(record=True):
self.panel4d = tm.makePanel4D(nper=8)
add_nans(self.panel4d)
def test_append(self):
df = tm.makeTimeDataFrame()
self.store.remove('df1')
self.store.append('df1', df[:10])
self.store.append('df1', df[10:])
tm.assert_frame_equal(self.store['df1'], df)
self.store.remove('df2')
self.store.put('df2', df[:10], table=True)
self.store.append('df2', df[10:])
tm.assert_frame_equal(self.store['df2'], df)
self.store.remove('df3')
self.store.append('/df3', df[:10])
self.store.append('/df3', df[10:])
tm.assert_frame_equal(self.store['df3'], df)
# this is allowed by almost always don't want to do it
warnings.filterwarnings('ignore', category=tables.NaturalNameWarning)
self.store.remove('/df3 foo')
self.store.append('/df3 foo', df[:10])
self.store.append('/df3 foo', df[10:])
tm.assert_frame_equal(self.store['df3 foo'], df)
warnings.filterwarnings('always', category=tables.NaturalNameWarning)
# panel
wp = tm.makePanel()
self.store.remove('wp1')
self.store.append('wp1', wp.ix[:, :10, :])
self.store.append('wp1', wp.ix[:, 10:, :])
tm.assert_panel_equal(self.store['wp1'], wp)
# ndim
p4d = tm.makePanel4D()
self.store.remove('p4d')
self.store.append('p4d', p4d.ix[:, :, :10, :])
self.store.append('p4d', p4d.ix[:, :, 10:, :])
tm.assert_panel4d_equal(self.store['p4d'], p4d)
# test using axis labels
self.store.remove('p4d')
self.store.append('p4d',
p4d.ix[:, :, :10, :],
axes=['items', 'major_axis', 'minor_axis'])
self.store.append('p4d',
p4d.ix[:, :, 10:, :],
axes=['items', 'major_axis', 'minor_axis'])
tm.assert_panel4d_equal(self.store['p4d'], p4d)
# test using differnt number of items on each axis
p4d2 = p4d.copy()
p4d2['l4'] = p4d['l1']
p4d2['l5'] = p4d['l1']
self.store.remove('p4d2')
self.store.append('p4d2',
p4d2,
axes=['items', 'major_axis', 'minor_axis'])
tm.assert_panel4d_equal(self.store['p4d2'], p4d2)
# test using differt order of items on the non-index axes
self.store.remove('wp1')
wp_append1 = wp.ix[:, :10, :]
self.store.append('wp1', wp_append1)
wp_append2 = wp.ix[:, 10:, :].reindex(items=wp.items[::-1])
self.store.append('wp1', wp_append2)
tm.assert_panel_equal(self.store['wp1'], wp)
def setUp(self):
with catch_warnings(record=True):
self.panel4d = tm.makePanel4D(nper=8)
add_nans(self.panel4d)
def test_panel4d(self):
self.run_panel(tm.makePanel4D(), np.random.randn() + 0.5,
assert_func=assert_panel4d_equal, binary_comp=3)
