diff --git a/pandas/tests/frame/test_reshape.py b/pandas/tests/frame/test_reshape.py index 28222a82945be8..daac084f657afd 100644 --- a/pandas/tests/frame/test_reshape.py +++ b/pandas/tests/frame/test_reshape.py @@ -4,7 +4,6 @@ from datetime import datetime import itertools -from warnings import catch_warnings, simplefilter import numpy as np import pytest @@ -49,14 +48,6 @@ def test_pivot(self): assert pivoted.index.name == 'index' assert pivoted.columns.names == (None, 'columns') - with catch_warnings(record=True): - # pivot multiple columns - simplefilter("ignore", FutureWarning) - wp = tm.makePanel() - lp = wp.to_frame() - df = lp.reset_index() - tm.assert_frame_equal(df.pivot('major', 'minor'), lp.unstack()) - def test_pivot_duplicates(self): data = DataFrame({'a': ['bar', 'bar', 'foo', 'foo', 'foo'], 'b': ['one', 'two', 'one', 'one', 'two'], diff --git a/pandas/tests/generic/test_generic.py b/pandas/tests/generic/test_generic.py index 7183fea85a069e..fb17b47948336c 100644 --- a/pandas/tests/generic/test_generic.py +++ b/pandas/tests/generic/test_generic.py @@ -740,23 +740,11 @@ def test_squeeze(self): tm.assert_series_equal(s.squeeze(), s) for df in [tm.makeTimeDataFrame()]: tm.assert_frame_equal(df.squeeze(), df) - with catch_warnings(record=True): - simplefilter("ignore", FutureWarning) - for p in [tm.makePanel()]: - tm.assert_panel_equal(p.squeeze(), p) # squeezing df = tm.makeTimeDataFrame().reindex(columns=['A']) tm.assert_series_equal(df.squeeze(), df['A']) - with catch_warnings(record=True): - simplefilter("ignore", FutureWarning) - 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']) - # don't fail with 0 length dimensions GH11229 & GH8999 empty_series = Series([], name='five') empty_frame = DataFrame([empty_series]) @@ -789,8 +777,6 @@ def test_numpy_squeeze(self): tm.assert_series_equal(np.squeeze(df), df['A']) 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 @@ -798,14 +784,6 @@ def test_transpose(self): for df in [tm.makeTimeDataFrame()]: tm.assert_frame_equal(df.transpose().transpose(), df) - with catch_warnings(record=True): - simplefilter("ignore", FutureWarning) - for p in [tm.makePanel()]: - tm.assert_panel_equal(p.transpose(2, 0, 1) - .transpose(1, 2, 0), p) - with pytest.raises(TypeError, match=msg): - p.transpose(2, 0, 1, axes=(2, 0, 1)) - def test_numpy_transpose(self): msg = "the 'axes' parameter is not supported" @@ -821,13 +799,6 @@ def test_numpy_transpose(self): with pytest.raises(ValueError, match=msg): np.transpose(df, axes=1) - with catch_warnings(record=True): - simplefilter("ignore", FutureWarning) - p = tm.makePanel() - tm.assert_panel_equal(np.transpose( - np.transpose(p, axes=(2, 0, 1)), - axes=(1, 2, 0)), p) - def test_take(self): indices = [1, 5, -2, 6, 3, -1] for s in [tm.makeFloatSeries(), tm.makeStringSeries(), @@ -843,27 +814,12 @@ def test_take(self): columns=df.columns) tm.assert_frame_equal(out, expected) - indices = [-3, 2, 0, 1] - with catch_warnings(record=True): - simplefilter("ignore", FutureWarning) - 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) - def test_take_invalid_kwargs(self): indices = [-3, 2, 0, 1] s = tm.makeFloatSeries() df = tm.makeTimeDataFrame() - with catch_warnings(record=True): - simplefilter("ignore", FutureWarning) - p = tm.makePanel() - - for obj in (s, df, p): + for obj in (s, df): msg = r"take\(\) got an unexpected keyword argument 'foo'" with pytest.raises(TypeError, match=msg): obj.take(indices, foo=2) @@ -966,12 +922,6 @@ def test_equals(self): assert a.equals(e) assert e.equals(f) - def test_describe_raises(self): - with catch_warnings(record=True): - simplefilter("ignore", FutureWarning) - with pytest.raises(NotImplementedError): - tm.makePanel().describe() - def test_pipe(self): df = DataFrame({'A': [1, 2, 3]}) f = lambda x, y: x ** y diff --git a/pandas/tests/generic/test_panel.py b/pandas/tests/generic/test_panel.py index 8b090d951957e5..73b8798661011c 100644 --- a/pandas/tests/generic/test_panel.py +++ b/pandas/tests/generic/test_panel.py @@ -3,11 +3,8 @@ from warnings import catch_warnings, simplefilter -import pandas.util._test_decorators as td - from pandas import Panel -import pandas.util.testing as tm -from pandas.util.testing import assert_almost_equal, assert_panel_equal +from pandas.util.testing import assert_panel_equal from .test_generic import Generic @@ -16,24 +13,6 @@ class TestPanel(Generic): _typ = Panel _comparator = lambda self, x, y: assert_panel_equal(x, y, by_blocks=True) - @td.skip_if_no('xarray', min_version='0.7.0') - def test_to_xarray(self): - from xarray import DataArray - - with catch_warnings(record=True): - simplefilter("ignore", FutureWarning) - p = tm.makePanel() - - result = p.to_xarray() - assert isinstance(result, DataArray) - assert len(result.coords) == 3 - assert_almost_equal(list(result.coords.keys()), - ['items', 'major_axis', 'minor_axis']) - assert len(result.dims) == 3 - - # idempotency - assert_panel_equal(result.to_pandas(), p) - # run all the tests, but wrap each in a warning catcher for t in ['test_rename', 'test_get_numeric_data', diff --git a/pandas/tests/indexing/test_panel.py b/pandas/tests/indexing/test_panel.py index 34708e1148c904..8530adec011be6 100644 --- a/pandas/tests/indexing/test_panel.py +++ b/pandas/tests/indexing/test_panel.py @@ -122,28 +122,6 @@ def test_panel_getitem(self): test1 = panel.loc[:, "2002"] tm.assert_panel_equal(test1, test2) - # GH8710 - # multi-element getting with a list - panel = tm.makePanel() - - expected = panel.iloc[[0, 1]] - - result = panel.loc[['ItemA', 'ItemB']] - tm.assert_panel_equal(result, expected) - - result = panel.loc[['ItemA', 'ItemB'], :, :] - tm.assert_panel_equal(result, expected) - - result = panel[['ItemA', 'ItemB']] - tm.assert_panel_equal(result, expected) - - result = panel.loc['ItemA':'ItemB'] - tm.assert_panel_equal(result, expected) - - with catch_warnings(record=True): - result = panel.ix[['ItemA', 'ItemB']] - tm.assert_panel_equal(result, expected) - # with an object-like # GH 9140 class TestObject(object): diff --git a/pandas/tests/io/test_sql.py b/pandas/tests/io/test_sql.py index 75a6d8d0090830..9d0bce3b342b41 100644 --- a/pandas/tests/io/test_sql.py +++ b/pandas/tests/io/test_sql.py @@ -605,12 +605,6 @@ def test_to_sql_series(self): s2 = sql.read_sql_query("SELECT * FROM test_series", self.conn) tm.assert_frame_equal(s.to_frame(), s2) - @pytest.mark.filterwarnings("ignore:\\nPanel:FutureWarning") - def test_to_sql_panel(self): - panel = tm.makePanel() - pytest.raises(NotImplementedError, sql.to_sql, panel, - 'test_panel', self.conn) - def test_roundtrip(self): sql.to_sql(self.test_frame1, 'test_frame_roundtrip', con=self.conn) diff --git a/pandas/tests/reshape/test_reshape.py b/pandas/tests/reshape/test_reshape.py index 7b544b7981c1f8..a5b6cffd1d86c0 100644 --- a/pandas/tests/reshape/test_reshape.py +++ b/pandas/tests/reshape/test_reshape.py @@ -580,23 +580,28 @@ def test_get_dummies_duplicate_columns(self, df): class TestCategoricalReshape(object): - @pytest.mark.filterwarnings("ignore:\\nPanel:FutureWarning") - def test_reshaping_panel_categorical(self): + def test_reshaping_multi_index_categorical(self): - p = tm.makePanel() - p['str'] = 'foo' - df = p.to_frame() + # construct a MultiIndexed DataFrame formerly created + # via `tm.makePanel().to_frame()` + cols = ['ItemA', 'ItemB', 'ItemC'] + data = {c: tm.makeTimeDataFrame() for c in cols} + df = pd.concat({c: data[c].stack() for c in data}, axis='columns') + df.index.names = ['major', 'minor'] + df['str'] = 'foo' + + dti = df.index.levels[0] df['category'] = df['str'].astype('category') result = df['category'].unstack() - c = Categorical(['foo'] * len(p.major_axis)) + c = Categorical(['foo'] * len(dti)) expected = DataFrame({'A': c.copy(), 'B': c.copy(), 'C': c.copy(), 'D': c.copy()}, columns=Index(list('ABCD'), name='minor'), - index=p.major_axis.set_names('major')) + index=dti) tm.assert_frame_equal(result, expected) diff --git a/pandas/tests/test_panel.py b/pandas/tests/test_panel.py index 5d8de3e1f87d50..bfcafda1dc7839 100644 --- a/pandas/tests/test_panel.py +++ b/pandas/tests/test_panel.py @@ -2,56 +2,28 @@ # pylint: disable=W0612,E1101 from collections import OrderedDict from datetime import datetime -import operator -from warnings import catch_warnings, simplefilter import numpy as np import pytest -from pandas.compat import StringIO, lrange, range, signature -import pandas.util._test_decorators as td +from pandas.compat import lrange -from pandas.core.dtypes.common import is_float_dtype - -from pandas import ( - DataFrame, Index, MultiIndex, Series, compat, date_range, isna, notna) -from pandas.core.nanops import nanall, nanany +from pandas import DataFrame, MultiIndex, Series, date_range, notna import pandas.core.panel as panelm from pandas.core.panel import Panel import pandas.util.testing as tm from pandas.util.testing import ( assert_almost_equal, assert_frame_equal, assert_panel_equal, - assert_series_equal, ensure_clean, makeCustomDataframe as mkdf, - makeMixedDataFrame) + assert_series_equal, makeCustomDataframe as mkdf, makeMixedDataFrame) from pandas.io.formats.printing import pprint_thing -from pandas.tseries.offsets import BDay, MonthEnd - - -def make_test_panel(): - with catch_warnings(record=True): - simplefilter("ignore", FutureWarning) - _panel = tm.makePanel() - tm.add_nans(_panel) - _panel = _panel.copy() - return _panel +from pandas.tseries.offsets import MonthEnd @pytest.mark.filterwarnings("ignore:\\nPanel:FutureWarning") class PanelTests(object): panel = None - def test_pickle(self): - unpickled = tm.round_trip_pickle(self.panel) - assert_frame_equal(unpickled['ItemA'], self.panel['ItemA']) - - def test_rank(self): - pytest.raises(NotImplementedError, lambda: self.panel.rank()) - - def test_cumsum(self): - cumsum = self.panel.cumsum() - assert_frame_equal(cumsum['ItemA'], self.panel['ItemA'].cumsum()) - def not_hashable(self): c_empty = Panel() c = Panel(Panel([[[1]]])) @@ -59,298 +31,9 @@ def not_hashable(self): pytest.raises(TypeError, hash, c) -@pytest.mark.filterwarnings("ignore:\\nPanel:FutureWarning") -class SafeForLongAndSparse(object): - - def test_repr(self): - repr(self.panel) - - def test_copy_names(self): - for attr in ('major_axis', 'minor_axis'): - getattr(self.panel, attr).name = None - cp = self.panel.copy() - getattr(cp, attr).name = 'foo' - assert getattr(self.panel, attr).name is None - - def test_iter(self): - tm.equalContents(list(self.panel), self.panel.items) - - def test_count(self): - f = lambda s: notna(s).sum() - self._check_stat_op('count', f, obj=self.panel, has_skipna=False) - - def test_sum(self): - self._check_stat_op('sum', np.sum, skipna_alternative=np.nansum) - - def test_mean(self): - self._check_stat_op('mean', np.mean) - - def test_prod(self): - self._check_stat_op('prod', np.prod, skipna_alternative=np.nanprod) - - @pytest.mark.filterwarnings("ignore:Invalid value:RuntimeWarning") - @pytest.mark.filterwarnings("ignore:All-NaN:RuntimeWarning") - def test_median(self): - def wrapper(x): - if isna(x).any(): - return np.nan - return np.median(x) - - self._check_stat_op('median', wrapper) - - @pytest.mark.filterwarnings("ignore:Invalid value:RuntimeWarning") - def test_min(self): - self._check_stat_op('min', np.min) - - @pytest.mark.filterwarnings("ignore:Invalid value:RuntimeWarning") - def test_max(self): - self._check_stat_op('max', np.max) - - @td.skip_if_no_scipy - def test_skew(self): - from scipy.stats import skew - - def this_skew(x): - if len(x) < 3: - return np.nan - return skew(x, bias=False) - - self._check_stat_op('skew', this_skew) - - def test_var(self): - def alt(x): - if len(x) < 2: - return np.nan - return np.var(x, ddof=1) - - self._check_stat_op('var', alt) - - def test_std(self): - def alt(x): - if len(x) < 2: - return np.nan - return np.std(x, ddof=1) - - self._check_stat_op('std', alt) - - def test_sem(self): - def alt(x): - if len(x) < 2: - return np.nan - return np.std(x, ddof=1) / np.sqrt(len(x)) - - self._check_stat_op('sem', alt) - - def _check_stat_op(self, name, alternative, obj=None, has_skipna=True, - skipna_alternative=None): - if obj is None: - obj = self.panel - - # # set some NAs - # obj.loc[5:10] = np.nan - # obj.loc[15:20, -2:] = np.nan - - f = getattr(obj, name) - - if has_skipna: - - skipna_wrapper = tm._make_skipna_wrapper(alternative, - skipna_alternative) - - def wrapper(x): - return alternative(np.asarray(x)) - - for i in range(obj.ndim): - result = f(axis=i, skipna=False) - assert_frame_equal(result, obj.apply(wrapper, axis=i)) - else: - skipna_wrapper = alternative - wrapper = alternative - - for i in range(obj.ndim): - result = f(axis=i) - if name in ['sum', 'prod']: - assert_frame_equal(result, obj.apply(skipna_wrapper, axis=i)) - - pytest.raises(Exception, f, axis=obj.ndim) - - # Unimplemented numeric_only parameter. - if 'numeric_only' in signature(f).args: - with pytest.raises(NotImplementedError, match=name): - f(numeric_only=True) - - @pytest.mark.filterwarnings("ignore:\\nPanel:FutureWarning") class SafeForSparse(object): - def test_get_axis(self): - assert (self.panel._get_axis(0) is self.panel.items) - assert (self.panel._get_axis(1) is self.panel.major_axis) - assert (self.panel._get_axis(2) is self.panel.minor_axis) - - def test_set_axis(self): - new_items = Index(np.arange(len(self.panel.items))) - new_major = Index(np.arange(len(self.panel.major_axis))) - new_minor = Index(np.arange(len(self.panel.minor_axis))) - - # ensure propagate to potentially prior-cached items too - item = self.panel['ItemA'] - self.panel.items = new_items - - if hasattr(self.panel, '_item_cache'): - assert 'ItemA' not in self.panel._item_cache - assert self.panel.items is new_items - - # TODO: unused? - item = self.panel[0] # noqa - - self.panel.major_axis = new_major - assert self.panel[0].index is new_major - assert self.panel.major_axis is new_major - - # TODO: unused? - item = self.panel[0] # noqa - - self.panel.minor_axis = new_minor - assert self.panel[0].columns is new_minor - assert self.panel.minor_axis is new_minor - - def test_get_axis_number(self): - assert self.panel._get_axis_number('items') == 0 - assert self.panel._get_axis_number('major') == 1 - assert self.panel._get_axis_number('minor') == 2 - - with pytest.raises(ValueError, match="No axis named foo"): - self.panel._get_axis_number('foo') - - with pytest.raises(ValueError, match="No axis named foo"): - self.panel.__ge__(self.panel, axis='foo') - - def test_get_axis_name(self): - assert self.panel._get_axis_name(0) == 'items' - assert self.panel._get_axis_name(1) == 'major_axis' - assert self.panel._get_axis_name(2) == 'minor_axis' - - def test_get_plane_axes(self): - # what to do here? - - index, columns = self.panel._get_plane_axes('items') - index, columns = self.panel._get_plane_axes('major_axis') - index, columns = self.panel._get_plane_axes('minor_axis') - index, columns = self.panel._get_plane_axes(0) - - def test_truncate(self): - dates = self.panel.major_axis - start, end = dates[1], dates[5] - - trunced = self.panel.truncate(start, end, axis='major') - expected = self.panel['ItemA'].truncate(start, end) - - assert_frame_equal(trunced['ItemA'], expected) - - trunced = self.panel.truncate(before=start, axis='major') - expected = self.panel['ItemA'].truncate(before=start) - - assert_frame_equal(trunced['ItemA'], expected) - - trunced = self.panel.truncate(after=end, axis='major') - expected = self.panel['ItemA'].truncate(after=end) - - assert_frame_equal(trunced['ItemA'], expected) - - def test_arith(self): - self._test_op(self.panel, operator.add) - self._test_op(self.panel, operator.sub) - self._test_op(self.panel, operator.mul) - self._test_op(self.panel, operator.truediv) - self._test_op(self.panel, operator.floordiv) - self._test_op(self.panel, operator.pow) - - self._test_op(self.panel, lambda x, y: y + x) - self._test_op(self.panel, lambda x, y: y - x) - self._test_op(self.panel, lambda x, y: y * x) - self._test_op(self.panel, lambda x, y: y / x) - self._test_op(self.panel, lambda x, y: y ** x) - - self._test_op(self.panel, lambda x, y: x + y) # panel + 1 - self._test_op(self.panel, lambda x, y: x - y) # panel - 1 - self._test_op(self.panel, lambda x, y: x * y) # panel * 1 - self._test_op(self.panel, lambda x, y: x / y) # panel / 1 - self._test_op(self.panel, lambda x, y: x ** y) # panel ** 1 - - pytest.raises(Exception, self.panel.__add__, - self.panel['ItemA']) - - @staticmethod - def _test_op(panel, op): - result = op(panel, 1) - assert_frame_equal(result['ItemA'], op(panel['ItemA'], 1)) - - def test_keys(self): - tm.equalContents(list(self.panel.keys()), self.panel.items) - - def test_iteritems(self): - # Test panel.iteritems(), aka panel.iteritems() - # just test that it works - for k, v in self.panel.iteritems(): - pass - - assert len(list(self.panel.iteritems())) == len(self.panel.items) - - def test_combineFrame(self): - def check_op(op, name): - # items - df = self.panel['ItemA'] - - func = getattr(self.panel, name) - - result = func(df, axis='items') - - assert_frame_equal( - result['ItemB'], op(self.panel['ItemB'], df)) - - # major - xs = self.panel.major_xs(self.panel.major_axis[0]) - result = func(xs, axis='major') - - idx = self.panel.major_axis[1] - - assert_frame_equal(result.major_xs(idx), - op(self.panel.major_xs(idx), xs)) - - # minor - xs = self.panel.minor_xs(self.panel.minor_axis[0]) - result = func(xs, axis='minor') - - idx = self.panel.minor_axis[1] - - assert_frame_equal(result.minor_xs(idx), - op(self.panel.minor_xs(idx), xs)) - - ops = ['add', 'sub', 'mul', 'truediv', 'floordiv', 'pow', 'mod'] - if not compat.PY3: - ops.append('div') - - for op in ops: - try: - check_op(getattr(operator, op), op) - except AttributeError: - pprint_thing("Failing operation: %r" % op) - raise - if compat.PY3: - try: - check_op(operator.truediv, 'div') - except AttributeError: - pprint_thing("Failing operation: %r" % 'div') - raise - - def test_combinePanel(self): - result = self.panel.add(self.panel) - assert_panel_equal(result, self.panel * 2) - - def test_neg(self): - assert_panel_equal(-self.panel, self.panel * -1) - # issue 7692 def test_raise_when_not_implemented(self): p = Panel(np.arange(3 * 4 * 5).reshape(3, 4, 5), @@ -364,84 +47,11 @@ def test_raise_when_not_implemented(self): with pytest.raises(NotImplementedError): getattr(p, op)(d, axis=0) - def test_select(self): - p = self.panel - - # select items - with tm.assert_produces_warning(FutureWarning, check_stacklevel=False): - result = p.select(lambda x: x in ('ItemA', 'ItemC'), axis='items') - expected = p.reindex(items=['ItemA', 'ItemC']) - assert_panel_equal(result, expected) - - # select major_axis - with tm.assert_produces_warning(FutureWarning, check_stacklevel=False): - result = p.select(lambda x: x >= datetime( - 2000, 1, 15), axis='major') - new_major = p.major_axis[p.major_axis >= datetime(2000, 1, 15)] - expected = p.reindex(major=new_major) - assert_panel_equal(result, expected) - - # select minor_axis - with tm.assert_produces_warning(FutureWarning, check_stacklevel=False): - result = p.select(lambda x: x in ('D', 'A'), axis=2) - expected = p.reindex(minor=['A', 'D']) - assert_panel_equal(result, expected) - - # corner case, empty thing - with tm.assert_produces_warning(FutureWarning, check_stacklevel=False): - result = p.select(lambda x: x in ('foo', ), axis='items') - assert_panel_equal(result, p.reindex(items=[])) - - def test_get_value(self): - for item in self.panel.items: - for mjr in self.panel.major_axis[::2]: - for mnr in self.panel.minor_axis: - with tm.assert_produces_warning(FutureWarning, - check_stacklevel=False): - result = self.panel.get_value(item, mjr, mnr) - expected = self.panel[item][mnr][mjr] - assert_almost_equal(result, expected) - - def test_abs(self): - - result = self.panel.abs() - result2 = abs(self.panel) - expected = np.abs(self.panel) - assert_panel_equal(result, expected) - assert_panel_equal(result2, expected) - - df = self.panel['ItemA'] - result = df.abs() - result2 = abs(df) - expected = np.abs(df) - assert_frame_equal(result, expected) - assert_frame_equal(result2, expected) - - s = df['A'] - result = s.abs() - result2 = abs(s) - expected = np.abs(s) - assert_series_equal(result, expected) - assert_series_equal(result2, expected) - assert result.name == 'A' - assert result2.name == 'A' - @pytest.mark.filterwarnings("ignore:\\nPanel:FutureWarning") class CheckIndexing(object): - def test_getitem(self): - pytest.raises(Exception, self.panel.__getitem__, 'ItemQ') - def test_delitem_and_pop(self): - expected = self.panel['ItemA'] - result = self.panel.pop('ItemA') - assert_frame_equal(expected, result) - assert 'ItemA' not in self.panel.items - - del self.panel['ItemB'] - assert 'ItemB' not in self.panel.items - pytest.raises(Exception, self.panel.__delitem__, 'ItemB') values = np.empty((3, 3, 3)) values[0] = 0 @@ -468,38 +78,6 @@ def test_delitem_and_pop(self): tm.assert_frame_equal(panelc[0], panel[0]) def test_setitem(self): - lp = self.panel.filter(['ItemA', 'ItemB']).to_frame() - - with pytest.raises(TypeError): - self.panel['ItemE'] = lp - - # DataFrame - df = self.panel['ItemA'][2:].filter(items=['A', 'B']) - self.panel['ItemF'] = df - self.panel['ItemE'] = df - - df2 = self.panel['ItemF'] - - assert_frame_equal(df, df2.reindex( - index=df.index, columns=df.columns)) - - # scalar - self.panel['ItemG'] = 1 - self.panel['ItemE'] = True - assert self.panel['ItemG'].values.dtype == np.int64 - assert self.panel['ItemE'].values.dtype == np.bool_ - - # object dtype - self.panel['ItemQ'] = 'foo' - assert self.panel['ItemQ'].values.dtype == np.object_ - - # boolean dtype - self.panel['ItemP'] = self.panel['ItemA'] > 0 - assert self.panel['ItemP'].values.dtype == np.bool_ - - pytest.raises(TypeError, self.panel.__setitem__, 'foo', - self.panel.loc[['ItemP']]) - # bad shape p = Panel(np.random.randn(4, 3, 2)) msg = (r"shape of value must be \(3, 2\), " @@ -537,159 +115,9 @@ def test_set_minor_major(self): assert_frame_equal(panel.loc[:, 'NewMajor', :], newmajor.astype(object)) - def test_major_xs(self): - ref = self.panel['ItemA'] - - idx = self.panel.major_axis[5] - xs = self.panel.major_xs(idx) - - result = xs['ItemA'] - assert_series_equal(result, ref.xs(idx), check_names=False) - assert result.name == 'ItemA' - - # not contained - idx = self.panel.major_axis[0] - BDay() - pytest.raises(Exception, self.panel.major_xs, idx) - - def test_major_xs_mixed(self): - self.panel['ItemD'] = 'foo' - xs = self.panel.major_xs(self.panel.major_axis[0]) - assert xs['ItemA'].dtype == np.float64 - assert xs['ItemD'].dtype == np.object_ - - def test_minor_xs(self): - ref = self.panel['ItemA'] - - idx = self.panel.minor_axis[1] - xs = self.panel.minor_xs(idx) - - assert_series_equal(xs['ItemA'], ref[idx], check_names=False) - - # not contained - pytest.raises(Exception, self.panel.minor_xs, 'E') - - def test_minor_xs_mixed(self): - self.panel['ItemD'] = 'foo' - - xs = self.panel.minor_xs('D') - assert xs['ItemA'].dtype == np.float64 - assert xs['ItemD'].dtype == np.object_ - - def test_xs(self): - itemA = self.panel.xs('ItemA', axis=0) - expected = self.panel['ItemA'] - tm.assert_frame_equal(itemA, expected) - - # Get a view by default. - itemA_view = self.panel.xs('ItemA', axis=0) - itemA_view.values[:] = np.nan - - assert np.isnan(self.panel['ItemA'].values).all() - - # Mixed-type yields a copy. - self.panel['strings'] = 'foo' - result = self.panel.xs('D', axis=2) - assert result._is_copy is not None - - def test_getitem_fancy_labels(self): - p = self.panel - - items = p.items[[1, 0]] - dates = p.major_axis[::2] - cols = ['D', 'C', 'F'] - - # all 3 specified - with catch_warnings(): - simplefilter("ignore", FutureWarning) - # XXX: warning in _validate_read_indexer - assert_panel_equal(p.loc[items, dates, cols], - p.reindex(items=items, major=dates, minor=cols)) - - # 2 specified - assert_panel_equal(p.loc[:, dates, cols], - p.reindex(major=dates, minor=cols)) - - assert_panel_equal(p.loc[items, :, cols], - p.reindex(items=items, minor=cols)) - - assert_panel_equal(p.loc[items, dates, :], - p.reindex(items=items, major=dates)) - - # only 1 - assert_panel_equal(p.loc[items, :, :], p.reindex(items=items)) - - assert_panel_equal(p.loc[:, dates, :], p.reindex(major=dates)) - - assert_panel_equal(p.loc[:, :, cols], p.reindex(minor=cols)) - def test_getitem_fancy_slice(self): pass - def test_getitem_fancy_ints(self): - p = self.panel - - # #1603 - result = p.iloc[:, -1, :] - expected = p.loc[:, p.major_axis[-1], :] - assert_frame_equal(result, expected) - - def test_getitem_fancy_xs(self): - p = self.panel - item = 'ItemB' - - date = p.major_axis[5] - col = 'C' - - # get DataFrame - # item - assert_frame_equal(p.loc[item], p[item]) - assert_frame_equal(p.loc[item, :], p[item]) - assert_frame_equal(p.loc[item, :, :], p[item]) - - # major axis, axis=1 - assert_frame_equal(p.loc[:, date], p.major_xs(date)) - assert_frame_equal(p.loc[:, date, :], p.major_xs(date)) - - # minor axis, axis=2 - assert_frame_equal(p.loc[:, :, 'C'], p.minor_xs('C')) - - # get Series - assert_series_equal(p.loc[item, date], p[item].loc[date]) - assert_series_equal(p.loc[item, date, :], p[item].loc[date]) - assert_series_equal(p.loc[item, :, col], p[item][col]) - assert_series_equal(p.loc[:, date, col], p.major_xs(date).loc[col]) - - def test_getitem_fancy_xs_check_view(self): - item = 'ItemB' - date = self.panel.major_axis[5] - - # make sure it's always a view - NS = slice(None, None) - - # DataFrames - comp = assert_frame_equal - self._check_view(item, comp) - self._check_view((item, NS), comp) - self._check_view((item, NS, NS), comp) - self._check_view((NS, date), comp) - self._check_view((NS, date, NS), comp) - self._check_view((NS, NS, 'C'), comp) - - # Series - comp = assert_series_equal - self._check_view((item, date), comp) - self._check_view((item, date, NS), comp) - self._check_view((item, NS, 'C'), comp) - self._check_view((NS, date, 'C'), comp) - - def test_getitem_callable(self): - p = self.panel - # GH 12533 - - assert_frame_equal(p[lambda x: 'ItemB'], p.loc['ItemB']) - assert_panel_equal(p[lambda x: ['ItemB', 'ItemC']], - p.loc[['ItemB', 'ItemC']]) - def test_ix_setitem_slice_dataframe(self): a = Panel(items=[1, 2, 3], major_axis=[11, 22, 33], minor_axis=[111, 222, 333]) @@ -719,43 +147,6 @@ def test_ix_align(self): assert_series_equal(df.loc[0, 0, :].reindex(b.index), b) def test_ix_frame_align(self): - p_orig = tm.makePanel() - df = p_orig.iloc[0].copy() - assert_frame_equal(p_orig['ItemA'], df) - - p = p_orig.copy() - p.iloc[0, :, :] = df - assert_panel_equal(p, p_orig) - - p = p_orig.copy() - p.iloc[0] = df - assert_panel_equal(p, p_orig) - - p = p_orig.copy() - p.iloc[0, :, :] = df - assert_panel_equal(p, p_orig) - - p = p_orig.copy() - p.iloc[0] = df - assert_panel_equal(p, p_orig) - - p = p_orig.copy() - p.loc['ItemA'] = df - assert_panel_equal(p, p_orig) - - p = p_orig.copy() - p.loc['ItemA', :, :] = df - assert_panel_equal(p, p_orig) - - p = p_orig.copy() - p['ItemA'] = df - assert_panel_equal(p, p_orig) - - p = p_orig.copy() - p.iloc[0, [0, 1, 3, 5], -2:] = df - out = p.iloc[0, [0, 1, 3, 5], -2:] - assert_frame_equal(out, df.iloc[[0, 1, 3, 5], [2, 3]]) - # GH3830, panel assignent by values/frame for dtype in ['float64', 'int64']: @@ -782,13 +173,6 @@ def test_ix_frame_align(self): tm.assert_frame_equal(panel.loc['a1'], df1) tm.assert_frame_equal(panel.loc['a2'], df2) - def _check_view(self, indexer, comp): - cp = self.panel.copy() - obj = cp.loc[indexer] - obj.values[:] = 0 - assert (obj.values == 0).all() - comp(cp.loc[indexer].reindex_like(obj), obj) - def test_logical_with_nas(self): d = Panel({'ItemA': {'a': [np.nan, False]}, 'ItemB': {'a': [True, True]}}) @@ -802,157 +186,11 @@ def test_logical_with_nas(self): expected = DataFrame({'a': [True, True]}) assert_frame_equal(result, expected) - def test_neg(self): - assert_panel_equal(-self.panel, -1 * self.panel) - - def test_invert(self): - assert_panel_equal(-(self.panel < 0), ~(self.panel < 0)) - - def test_comparisons(self): - p1 = tm.makePanel() - p2 = tm.makePanel() - - tp = p1.reindex(items=p1.items + ['foo']) - df = p1[p1.items[0]] - - def test_comp(func): - - # versus same index - 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, df) - - # versus scalar - result3 = func(self.panel, 0) - tm.assert_numpy_array_equal(result3.values, - func(self.panel.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_get_value(self): - for item in self.panel.items: - for mjr in self.panel.major_axis[::2]: - for mnr in self.panel.minor_axis: - with tm.assert_produces_warning(FutureWarning, - check_stacklevel=False): - result = self.panel.get_value(item, mjr, mnr) - expected = self.panel[item][mnr][mjr] - assert_almost_equal(result, expected) - with catch_warnings(): - simplefilter("ignore", FutureWarning) - msg = "There must be an argument for each axis" - with pytest.raises(TypeError, match=msg): - self.panel.get_value('a') - - def test_set_value(self): - for item in self.panel.items: - for mjr in self.panel.major_axis[::2]: - for mnr in self.panel.minor_axis: - with tm.assert_produces_warning(FutureWarning, - check_stacklevel=False): - self.panel.set_value(item, mjr, mnr, 1.) - tm.assert_almost_equal(self.panel[item][mnr][mjr], 1.) - - # resize - with catch_warnings(): - simplefilter("ignore", FutureWarning) - res = self.panel.set_value('ItemE', 'foo', 'bar', 1.5) - assert isinstance(res, Panel) - assert res is not self.panel - assert res.get_value('ItemE', 'foo', 'bar') == 1.5 - - res3 = self.panel.set_value('ItemE', 'foobar', 'baz', 5) - assert is_float_dtype(res3['ItemE'].values) - - msg = ("There must be an argument for each " - "axis plus the value provided") - with pytest.raises(TypeError, match=msg): - self.panel.set_value('a') - @pytest.mark.filterwarnings("ignore:\\nPanel:FutureWarning") -class TestPanel(PanelTests, CheckIndexing, SafeForLongAndSparse, - SafeForSparse): - - def setup_method(self, method): - self.panel = make_test_panel() - self.panel.major_axis.name = None - self.panel.minor_axis.name = None - self.panel.items.name = None - - def test_constructor(self): - # with BlockManager - wp = Panel(self.panel._data) - assert wp._data is self.panel._data - - wp = Panel(self.panel._data, copy=True) - assert wp._data is not self.panel._data - tm.assert_panel_equal(wp, self.panel) - - # strings handled prop - wp = Panel([[['foo', 'foo', 'foo', ], ['foo', 'foo', 'foo']]]) - assert wp.values.dtype == np.object_ - - vals = self.panel.values - - # no copy - wp = Panel(vals) - assert wp.values is vals - - # copy - wp = Panel(vals, copy=True) - assert wp.values is not vals - - # GH #8285, test when scalar data is used to construct a Panel - # if dtype is not passed, it should be inferred - value_and_dtype = [(1, 'int64'), (3.14, 'float64'), - ('foo', np.object_)] - for (val, dtype) in value_and_dtype: - wp = Panel(val, items=range(2), major_axis=range(3), - minor_axis=range(4)) - vals = np.empty((2, 3, 4), dtype=dtype) - vals.fill(val) - - tm.assert_panel_equal(wp, Panel(vals, dtype=dtype)) - - # test the case when dtype is passed - wp = Panel(1, items=range(2), major_axis=range(3), - minor_axis=range(4), - dtype='float32') - vals = np.empty((2, 3, 4), dtype='float32') - vals.fill(1) - - tm.assert_panel_equal(wp, Panel(vals, dtype='float32')) +class TestPanel(PanelTests, CheckIndexing, SafeForSparse): def test_constructor_cast(self): - zero_filled = self.panel.fillna(0) - - casted = Panel(zero_filled._data, dtype=int) - casted2 = Panel(zero_filled.values, dtype=int) - - exp_values = zero_filled.values.astype(int) - assert_almost_equal(casted.values, exp_values) - assert_almost_equal(casted2.values, exp_values) - - casted = Panel(zero_filled._data, dtype=np.int32) - casted2 = Panel(zero_filled.values, dtype=np.int32) - - exp_values = zero_filled.values.astype(np.int32) - assert_almost_equal(casted.values, exp_values) - assert_almost_equal(casted2.values, exp_values) - # can't cast data = [[['foo', 'bar', 'baz']]] pytest.raises(ValueError, Panel, data, dtype=float) @@ -1017,86 +255,6 @@ def test_constructor_fails_with_not_3d_input(self): with pytest.raises(ValueError, match=msg): Panel(np.random.randn(10, 2)) - def test_consolidate(self): - assert self.panel._data.is_consolidated() - - self.panel['foo'] = 1. - assert not self.panel._data.is_consolidated() - - panel = self.panel._consolidate() - assert panel._data.is_consolidated() - - def test_ctor_dict(self): - itema = self.panel['ItemA'] - itemb = self.panel['ItemB'] - - d = {'A': itema, 'B': itemb[5:]} - d2 = {'A': itema._series, 'B': itemb[5:]._series} - d3 = {'A': None, - 'B': DataFrame(itemb[5:]._series), - 'C': DataFrame(itema._series)} - - wp = Panel.from_dict(d) - wp2 = Panel.from_dict(d2) # nested Dict - - # TODO: unused? - wp3 = Panel.from_dict(d3) # noqa - - tm.assert_index_equal(wp.major_axis, self.panel.major_axis) - assert_panel_equal(wp, wp2) - - # intersect - wp = Panel.from_dict(d, intersect=True) - tm.assert_index_equal(wp.major_axis, itemb.index[5:]) - - # use constructor - assert_panel_equal(Panel(d), Panel.from_dict(d)) - assert_panel_equal(Panel(d2), Panel.from_dict(d2)) - assert_panel_equal(Panel(d3), Panel.from_dict(d3)) - - # a pathological case - d4 = {'A': None, 'B': None} - - # TODO: unused? - wp4 = Panel.from_dict(d4) # noqa - - assert_panel_equal(Panel(d4), Panel(items=['A', 'B'])) - - # cast - dcasted = {k: v.reindex(wp.major_axis).fillna(0) - for k, v in compat.iteritems(d)} - result = Panel(dcasted, dtype=int) - expected = Panel({k: v.astype(int) - for k, v in compat.iteritems(dcasted)}) - assert_panel_equal(result, expected) - - result = Panel(dcasted, dtype=np.int32) - expected = Panel({k: v.astype(np.int32) - for k, v in compat.iteritems(dcasted)}) - assert_panel_equal(result, expected) - - def test_constructor_dict_mixed(self): - data = {k: v.values for k, v in self.panel.iteritems()} - result = Panel(data) - exp_major = Index(np.arange(len(self.panel.major_axis))) - tm.assert_index_equal(result.major_axis, exp_major) - - result = Panel(data, items=self.panel.items, - major_axis=self.panel.major_axis, - minor_axis=self.panel.minor_axis) - assert_panel_equal(result, self.panel) - - data['ItemC'] = self.panel['ItemC'] - result = Panel(data) - assert_panel_equal(result, self.panel) - - # corner, blow up - data['ItemB'] = data['ItemB'][:-1] - pytest.raises(Exception, Panel, data) - - data['ItemB'] = self.panel['ItemB'].values[:, :-1] - pytest.raises(Exception, Panel, data) - def test_ctor_orderedDict(self): keys = list(set(np.random.randint(0, 5000, 100)))[ :50] # unique random int keys @@ -1107,30 +265,6 @@ def test_ctor_orderedDict(self): p = Panel.from_dict(d) assert list(p.items) == keys - def test_constructor_resize(self): - data = self.panel._data - items = self.panel.items[:-1] - major = self.panel.major_axis[:-1] - minor = self.panel.minor_axis[:-1] - - result = Panel(data, items=items, - major_axis=major, minor_axis=minor) - expected = self.panel.reindex( - items=items, major=major, minor=minor) - assert_panel_equal(result, expected) - - result = Panel(data, items=items, major_axis=major) - expected = self.panel.reindex(items=items, major=major) - assert_panel_equal(result, expected) - - result = Panel(data, items=items) - expected = self.panel.reindex(items=items) - assert_panel_equal(result, expected) - - result = Panel(data, minor_axis=minor) - expected = self.panel.reindex(minor=minor) - assert_panel_equal(result, expected) - def test_from_dict_mixed_orient(self): df = tm.makeDataFrame() df['foo'] = 'bar' @@ -1161,13 +295,6 @@ def test_constructor_error_msgs(self): Panel(np.random.randn(3, 4, 5), lrange(5), lrange(5), lrange(4)) - def test_conform(self): - df = self.panel['ItemA'][:-5].filter(items=['A', 'B']) - conformed = self.panel.conform(df) - - tm.assert_index_equal(conformed.index, self.panel.major_axis) - tm.assert_index_equal(conformed.columns, self.panel.minor_axis) - def test_convert_objects(self): # GH 4937 p = Panel(dict(A=dict(a=['1', '1.0']))) @@ -1175,12 +302,6 @@ def test_convert_objects(self): result = p._convert(numeric=True, coerce=True) assert_panel_equal(result, expected) - def test_dtypes(self): - - result = self.panel.dtypes - expected = Series(np.dtype('float64'), index=self.panel.items) - assert_series_equal(result, expected) - def test_astype(self): # GH7271 data = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]]) @@ -1193,121 +314,7 @@ def test_astype(self): pytest.raises(NotImplementedError, panel.astype, {0: str}) - def test_apply(self): - # GH1148 - - # ufunc - applied = self.panel.apply(np.sqrt) - with np.errstate(invalid='ignore'): - expected = np.sqrt(self.panel.values) - assert_almost_equal(applied.values, expected) - - # ufunc same shape - result = self.panel.apply(lambda x: x * 2, axis='items') - expected = self.panel * 2 - assert_panel_equal(result, expected) - result = self.panel.apply(lambda x: x * 2, axis='major_axis') - expected = self.panel * 2 - assert_panel_equal(result, expected) - result = self.panel.apply(lambda x: x * 2, axis='minor_axis') - expected = self.panel * 2 - assert_panel_equal(result, expected) - - # reduction to DataFrame - result = self.panel.apply(lambda x: x.dtype, axis='items') - expected = DataFrame(np.dtype('float64'), - index=self.panel.major_axis, - columns=self.panel.minor_axis) - assert_frame_equal(result, expected) - result = self.panel.apply(lambda x: x.dtype, axis='major_axis') - expected = DataFrame(np.dtype('float64'), - index=self.panel.minor_axis, - columns=self.panel.items) - assert_frame_equal(result, expected) - result = self.panel.apply(lambda x: x.dtype, axis='minor_axis') - expected = DataFrame(np.dtype('float64'), - index=self.panel.major_axis, - columns=self.panel.items) - assert_frame_equal(result, expected) - - # reductions via other dims - expected = self.panel.sum(0) - result = self.panel.apply(lambda x: x.sum(), axis='items') - assert_frame_equal(result, expected) - expected = self.panel.sum(1) - result = self.panel.apply(lambda x: x.sum(), axis='major_axis') - assert_frame_equal(result, expected) - expected = self.panel.sum(2) - result = self.panel.apply(lambda x: x.sum(), axis='minor_axis') - assert_frame_equal(result, expected) - - # pass kwargs - result = self.panel.apply( - lambda x, y: x.sum() + y, axis='items', y=5) - expected = self.panel.sum(0) + 5 - assert_frame_equal(result, expected) - def test_apply_slabs(self): - - # same shape as original - result = self.panel.apply(lambda x: x * 2, - axis=['items', 'major_axis']) - expected = (self.panel * 2).transpose('minor_axis', 'major_axis', - 'items') - assert_panel_equal(result, expected) - result = self.panel.apply(lambda x: x * 2, - axis=['major_axis', 'items']) - assert_panel_equal(result, expected) - - result = self.panel.apply(lambda x: x * 2, - axis=['items', 'minor_axis']) - expected = (self.panel * 2).transpose('major_axis', 'minor_axis', - 'items') - assert_panel_equal(result, expected) - result = self.panel.apply(lambda x: x * 2, - axis=['minor_axis', 'items']) - assert_panel_equal(result, expected) - - result = self.panel.apply(lambda x: x * 2, - axis=['major_axis', 'minor_axis']) - expected = self.panel * 2 - assert_panel_equal(result, expected) - result = self.panel.apply(lambda x: x * 2, - axis=['minor_axis', 'major_axis']) - assert_panel_equal(result, expected) - - # reductions - result = self.panel.apply(lambda x: x.sum(0), axis=[ - 'items', 'major_axis' - ]) - expected = self.panel.sum(1).T - assert_frame_equal(result, expected) - - result = self.panel.apply(lambda x: x.sum(1), axis=[ - 'items', 'major_axis' - ]) - expected = self.panel.sum(0) - assert_frame_equal(result, expected) - - # transforms - f = lambda x: ((x.T - x.mean(1)) / x.std(1)).T - - # make sure that we don't trigger any warnings - result = self.panel.apply(f, axis=['items', 'major_axis']) - expected = Panel({ax: f(self.panel.loc[:, :, ax]) - for ax in self.panel.minor_axis}) - assert_panel_equal(result, expected) - - result = self.panel.apply(f, axis=['major_axis', 'minor_axis']) - expected = Panel({ax: f(self.panel.loc[ax]) - for ax in self.panel.items}) - assert_panel_equal(result, expected) - - result = self.panel.apply(f, axis=['minor_axis', 'items']) - expected = Panel({ax: f(self.panel.loc[:, ax]) - for ax in self.panel.major_axis}) - assert_panel_equal(result, expected) - # with multi-indexes # GH7469 index = MultiIndex.from_tuples([('one', 'a'), ('one', 'b'), ( @@ -1343,53 +350,6 @@ def test_apply_no_or_zero_ndim(self): assert_series_equal(result_float, expected_float) assert_series_equal(result_float64, expected_float64) - def test_reindex(self): - ref = self.panel['ItemB'] - - # items - result = self.panel.reindex(items=['ItemA', 'ItemB']) - assert_frame_equal(result['ItemB'], ref) - - # major - new_major = list(self.panel.major_axis[:10]) - result = self.panel.reindex(major=new_major) - assert_frame_equal(result['ItemB'], ref.reindex(index=new_major)) - - # raise exception put both major and major_axis - pytest.raises(Exception, self.panel.reindex, - major_axis=new_major, - major=new_major) - - # minor - new_minor = list(self.panel.minor_axis[:2]) - result = self.panel.reindex(minor=new_minor) - assert_frame_equal(result['ItemB'], ref.reindex(columns=new_minor)) - - # raise exception put both major and major_axis - pytest.raises(Exception, self.panel.reindex, - minor_axis=new_minor, - minor=new_minor) - - # this ok - result = self.panel.reindex() - assert_panel_equal(result, self.panel) - assert result is not self.panel - - # with filling - smaller_major = self.panel.major_axis[::5] - smaller = self.panel.reindex(major=smaller_major) - - larger = smaller.reindex(major=self.panel.major_axis, method='pad') - - assert_frame_equal(larger.major_xs(self.panel.major_axis[1]), - smaller.major_xs(smaller_major[0])) - - # don't necessarily copy - result = self.panel.reindex( - major=self.panel.major_axis, copy=False) - assert_panel_equal(result, self.panel) - assert result is self.panel - def test_reindex_axis_style(self): panel = Panel(np.random.rand(5, 5, 5)) expected0 = Panel(panel.values).iloc[[0, 1]] @@ -1410,22 +370,6 @@ def test_reindex_axis_style(self): def test_reindex_multi(self): - # with and without copy full reindexing - result = self.panel.reindex( - items=self.panel.items, - major=self.panel.major_axis, - minor=self.panel.minor_axis, copy=False) - - assert result.items is self.panel.items - assert result.major_axis is self.panel.major_axis - assert result.minor_axis is self.panel.minor_axis - - result = self.panel.reindex( - items=self.panel.items, - major=self.panel.major_axis, - minor=self.panel.minor_axis, copy=False) - assert_panel_equal(result, self.panel) - # multi-axis indexing consistency # GH 5900 df = DataFrame(np.random.randn(4, 3)) @@ -1454,86 +398,7 @@ def test_reindex_multi(self): for i, r in enumerate(results): assert_panel_equal(expected, r) - def test_reindex_like(self): - # reindex_like - smaller = self.panel.reindex(items=self.panel.items[:-1], - major=self.panel.major_axis[:-1], - minor=self.panel.minor_axis[:-1]) - smaller_like = self.panel.reindex_like(smaller) - assert_panel_equal(smaller, smaller_like) - - def test_take(self): - # axis == 0 - result = self.panel.take([2, 0, 1], axis=0) - expected = self.panel.reindex(items=['ItemC', 'ItemA', 'ItemB']) - assert_panel_equal(result, expected) - - # axis >= 1 - result = self.panel.take([3, 0, 1, 2], axis=2) - expected = self.panel.reindex(minor=['D', 'A', 'B', 'C']) - assert_panel_equal(result, expected) - - # neg indices ok - expected = self.panel.reindex(minor=['D', 'D', 'B', 'C']) - result = self.panel.take([3, -1, 1, 2], axis=2) - assert_panel_equal(result, expected) - - pytest.raises(Exception, self.panel.take, [4, 0, 1, 2], axis=2) - - def test_sort_index(self): - import random - - ritems = list(self.panel.items) - rmajor = list(self.panel.major_axis) - rminor = list(self.panel.minor_axis) - random.shuffle(ritems) - random.shuffle(rmajor) - random.shuffle(rminor) - - random_order = self.panel.reindex(items=ritems) - sorted_panel = random_order.sort_index(axis=0) - assert_panel_equal(sorted_panel, self.panel) - - # descending - random_order = self.panel.reindex(items=ritems) - sorted_panel = random_order.sort_index(axis=0, ascending=False) - assert_panel_equal( - sorted_panel, - self.panel.reindex(items=self.panel.items[::-1])) - - random_order = self.panel.reindex(major=rmajor) - sorted_panel = random_order.sort_index(axis=1) - assert_panel_equal(sorted_panel, self.panel) - - random_order = self.panel.reindex(minor=rminor) - sorted_panel = random_order.sort_index(axis=2) - assert_panel_equal(sorted_panel, self.panel) - def test_fillna(self): - filled = self.panel.fillna(0) - assert np.isfinite(filled.values).all() - - filled = self.panel.fillna(method='backfill') - assert_frame_equal(filled['ItemA'], - self.panel['ItemA'].fillna(method='backfill')) - - panel = self.panel.copy() - panel['str'] = 'foo' - - filled = panel.fillna(method='backfill') - assert_frame_equal(filled['ItemA'], - panel['ItemA'].fillna(method='backfill')) - - empty = self.panel.reindex(items=[]) - filled = empty.fillna(0) - assert_panel_equal(filled, empty) - - pytest.raises(ValueError, self.panel.fillna) - pytest.raises(ValueError, self.panel.fillna, 5, method='ffill') - - pytest.raises(TypeError, self.panel.fillna, [1, 2]) - pytest.raises(TypeError, self.panel.fillna, (1, 2)) - # limit not implemented when only value is specified p = Panel(np.random.randn(3, 4, 5)) p.iloc[0:2, 0:2, 0:2] = np.nan @@ -1559,100 +424,6 @@ def test_fillna(self): p2.fillna(method='bfill', inplace=True) assert_panel_equal(p2, expected) - def test_ffill_bfill(self): - assert_panel_equal(self.panel.ffill(), - self.panel.fillna(method='ffill')) - assert_panel_equal(self.panel.bfill(), - self.panel.fillna(method='bfill')) - - def test_truncate_fillna_bug(self): - # #1823 - result = self.panel.truncate(before=None, after=None, axis='items') - - # it works! - result.fillna(value=0.0) - - def test_swapaxes(self): - result = self.panel.swapaxes('items', 'minor') - assert result.items is self.panel.minor_axis - - result = self.panel.swapaxes('items', 'major') - assert result.items is self.panel.major_axis - - result = self.panel.swapaxes('major', 'minor') - assert result.major_axis is self.panel.minor_axis - - panel = self.panel.copy() - result = panel.swapaxes('major', 'minor') - panel.values[0, 0, 1] = np.nan - expected = panel.swapaxes('major', 'minor') - assert_panel_equal(result, expected) - - # this should also work - result = self.panel.swapaxes(0, 1) - assert result.items is self.panel.major_axis - - # this works, but return a copy - result = self.panel.swapaxes('items', 'items') - assert_panel_equal(self.panel, result) - assert id(self.panel) != id(result) - - def test_transpose(self): - result = self.panel.transpose('minor', 'major', 'items') - expected = self.panel.swapaxes('items', 'minor') - assert_panel_equal(result, expected) - - # test kwargs - result = self.panel.transpose(items='minor', major='major', - minor='items') - expected = self.panel.swapaxes('items', 'minor') - assert_panel_equal(result, expected) - - # text mixture of args - result = self.panel.transpose( - 'minor', major='major', minor='items') - expected = self.panel.swapaxes('items', 'minor') - assert_panel_equal(result, expected) - - result = self.panel.transpose('minor', - 'major', - minor='items') - expected = self.panel.swapaxes('items', 'minor') - assert_panel_equal(result, expected) - - # duplicate axes - with pytest.raises(TypeError, - match='not enough/duplicate arguments'): - self.panel.transpose('minor', maj='major', minor='items') - - with pytest.raises(ValueError, - match='repeated axis in transpose'): - self.panel.transpose('minor', 'major', major='minor', - minor='items') - - result = self.panel.transpose(2, 1, 0) - assert_panel_equal(result, expected) - - result = self.panel.transpose('minor', 'items', 'major') - expected = self.panel.swapaxes('items', 'minor') - expected = expected.swapaxes('major', 'minor') - assert_panel_equal(result, expected) - - result = self.panel.transpose(2, 0, 1) - assert_panel_equal(result, expected) - - pytest.raises(ValueError, self.panel.transpose, 0, 0, 1) - - def test_transpose_copy(self): - panel = self.panel.copy() - result = panel.transpose(2, 0, 1, copy=True) - expected = panel.swapaxes('items', 'minor') - expected = expected.swapaxes('major', 'minor') - assert_panel_equal(result, expected) - - panel.values[0, 1, 1] = np.nan - assert notna(result.values[1, 0, 1]) - def test_to_frame_multi_major(self): idx = MultiIndex.from_tuples( [(1, 'one'), (1, 'two'), (2, 'one'), (2, 'two')]) @@ -1815,40 +586,7 @@ def test_panel_dups(self): def test_filter(self): pass - def test_compound(self): - compounded = self.panel.compound() - - assert_series_equal(compounded['ItemA'], - (1 + self.panel['ItemA']).product(0) - 1, - check_names=False) - def test_shift(self): - # major - idx = self.panel.major_axis[0] - idx_lag = self.panel.major_axis[1] - shifted = self.panel.shift(1) - assert_frame_equal(self.panel.major_xs(idx), - shifted.major_xs(idx_lag)) - - # minor - idx = self.panel.minor_axis[0] - idx_lag = self.panel.minor_axis[1] - shifted = self.panel.shift(1, axis='minor') - assert_frame_equal(self.panel.minor_xs(idx), - shifted.minor_xs(idx_lag)) - - # items - idx = self.panel.items[0] - idx_lag = self.panel.items[1] - shifted = self.panel.shift(1, axis='items') - assert_frame_equal(self.panel[idx], shifted[idx_lag]) - - # negative numbers, #2164 - result = self.panel.shift(-1) - expected = Panel({i: f.shift(-1)[:-1] - for i, f in self.panel.iteritems()}) - assert_panel_equal(result, expected) - # mixed dtypes #6959 data = [('item ' + ch, makeMixedDataFrame()) for ch in list('abcde')] @@ -1857,29 +595,6 @@ def test_shift(self): shifted = mixed_panel.shift(1) assert_series_equal(mixed_panel.dtypes, shifted.dtypes) - def test_tshift(self): - - # DatetimeIndex - panel = make_test_panel() - shifted = panel.tshift(1) - unshifted = shifted.tshift(-1) - - assert_panel_equal(panel, unshifted) - - shifted2 = panel.tshift(freq=panel.major_axis.freq) - assert_panel_equal(shifted, shifted2) - - inferred_ts = Panel(panel.values, items=panel.items, - major_axis=Index(np.asarray(panel.major_axis)), - minor_axis=panel.minor_axis) - shifted = inferred_ts.tshift(1) - unshifted = shifted.tshift(-1) - assert_panel_equal(shifted, panel.tshift(1)) - assert_panel_equal(unshifted, inferred_ts) - - no_freq = panel.iloc[:, [0, 5, 7], :] - pytest.raises(ValueError, no_freq.tshift) - def test_pct_change(self): df1 = DataFrame({'c1': [1, 2, 5], 'c2': [3, 4, 6]}) df2 = df1 + 1 @@ -1992,89 +707,10 @@ def test_multiindex_get(self): MultiIndex.from_tuples([('a', 1), ('a', 2), ('b', 1)], names=['first', 'second']) - @pytest.mark.filterwarnings("ignore:Using a non-tuple:FutureWarning") - def test_multiindex_blocks(self): - ind = MultiIndex.from_tuples([('a', 1), ('a', 2), ('b', 1)], - names=['first', 'second']) - wp = Panel(self.panel._data) - wp.items = ind - f1 = wp['a'] - assert (f1.items == [1, 2]).all() - - f1 = wp[('b', 1)] - assert (f1.columns == ['A', 'B', 'C', 'D']).all() - def test_repr_empty(self): empty = Panel() repr(empty) - # ignore warning from us, because removing panel - @pytest.mark.filterwarnings("ignore:Using:FutureWarning") - def test_rename(self): - mapper = {'ItemA': 'foo', 'ItemB': 'bar', 'ItemC': 'baz'} - - renamed = self.panel.rename(items=mapper) - exp = Index(['foo', 'bar', 'baz']) - tm.assert_index_equal(renamed.items, exp) - - renamed = self.panel.rename(minor_axis=str.lower) - exp = Index(['a', 'b', 'c', 'd']) - tm.assert_index_equal(renamed.minor_axis, exp) - - # don't copy - renamed_nocopy = self.panel.rename(items=mapper, copy=False) - renamed_nocopy['foo'] = 3. - assert (self.panel['ItemA'].values == 3).all() - - def test_get_attr(self): - assert_frame_equal(self.panel['ItemA'], self.panel.ItemA) - - # specific cases from #3440 - self.panel['a'] = self.panel['ItemA'] - assert_frame_equal(self.panel['a'], self.panel.a) - self.panel['i'] = self.panel['ItemA'] - assert_frame_equal(self.panel['i'], self.panel.i) - - def test_to_excel(self): - try: - import xlwt # noqa - import xlrd # noqa - import openpyxl # noqa - from pandas.io.excel import ExcelFile - except ImportError: - pytest.skip("need xlwt xlrd openpyxl") - - for ext in ['xls', 'xlsx']: - with ensure_clean('__tmp__.' + ext) as path: - self.panel.to_excel(path) - try: - reader = ExcelFile(path) - except ImportError: - pytest.skip("need xlwt xlrd openpyxl") - - for item, df in self.panel.iteritems(): - recdf = reader.parse(str(item), index_col=0) - assert_frame_equal(df, recdf) - - def test_to_excel_xlsxwriter(self): - try: - import xlrd # noqa - import xlsxwriter # noqa - from pandas.io.excel import ExcelFile - except ImportError: - pytest.skip("Requires xlrd and xlsxwriter. Skipping test.") - - with ensure_clean('__tmp__.xlsx') as path: - self.panel.to_excel(path, engine='xlsxwriter') - try: - reader = ExcelFile(path) - except ImportError as e: - pytest.skip("cannot write excel file: %s" % e) - - for item, df in self.panel.iteritems(): - recdf = reader.parse(str(item), index_col=0) - assert_frame_equal(df, recdf) - @pytest.mark.filterwarnings("ignore:'.reindex:FutureWarning") def test_dropna(self): p = Panel(np.random.randn(4, 5, 6), major_axis=list('abcde')) @@ -2275,132 +911,6 @@ def test_update_deprecation(self, raise_conflict): with tm.assert_produces_warning(FutureWarning): pan.update(other, raise_conflict=raise_conflict) - def test_all_any(self): - assert (self.panel.all(axis=0).values == nanall( - self.panel, axis=0)).all() - assert (self.panel.all(axis=1).values == nanall( - self.panel, axis=1).T).all() - assert (self.panel.all(axis=2).values == nanall( - self.panel, axis=2).T).all() - assert (self.panel.any(axis=0).values == nanany( - self.panel, axis=0)).all() - assert (self.panel.any(axis=1).values == nanany( - self.panel, axis=1).T).all() - assert (self.panel.any(axis=2).values == nanany( - self.panel, axis=2).T).all() - - def test_all_any_unhandled(self): - pytest.raises(NotImplementedError, self.panel.all, bool_only=True) - pytest.raises(NotImplementedError, self.panel.any, bool_only=True) - - # GH issue 15960 - def test_sort_values(self): - pytest.raises(NotImplementedError, self.panel.sort_values) - pytest.raises(NotImplementedError, self.panel.sort_values, 'ItemA') - - -@pytest.mark.filterwarnings("ignore:\\nPanel:FutureWarning") -class TestPanelFrame(object): - """ - Check that conversions to and from Panel to DataFrame work. - """ - - def setup_method(self, method): - panel = make_test_panel() - self.panel = panel.to_frame() - self.unfiltered_panel = panel.to_frame(filter_observations=False) - - def test_ops_scalar(self): - result = self.panel.mul(2) - expected = DataFrame.__mul__(self.panel, 2) - assert_frame_equal(result, expected) - - def test_combine_scalar(self): - result = self.panel.mul(2) - expected = DataFrame(self.panel._data) * 2 - assert_frame_equal(result, expected) - - def test_combine_series(self): - s = self.panel['ItemA'][:10] - result = self.panel.add(s, axis=0) - expected = DataFrame.add(self.panel, s, axis=0) - assert_frame_equal(result, expected) - - s = self.panel.iloc[5] - result = self.panel + s - expected = DataFrame.add(self.panel, s, axis=1) - assert_frame_equal(result, expected) - - def test_sort(self): - def is_sorted(arr): - return (arr[1:] > arr[:-1]).any() - - sorted_minor = self.panel.sort_index(level=1) - assert is_sorted(sorted_minor.index.codes[1]) - - sorted_major = sorted_minor.sort_index(level=0) - assert is_sorted(sorted_major.index.codes[0]) - - def test_to_string(self): - buf = StringIO() - self.panel.to_string(buf) - - def test_to_sparse(self): - if isinstance(self.panel, Panel): - msg = 'sparsifying is not supported' - with pytest.raises(NotImplementedError, match=msg): - self.panel.to_sparse - - def test_axis_dummies(self): - from pandas.core.reshape.reshape import make_axis_dummies - - minor_dummies = make_axis_dummies(self.panel, 'minor').astype(np.uint8) - assert len(minor_dummies.columns) == len(self.panel.index.levels[1]) - - major_dummies = make_axis_dummies(self.panel, 'major').astype(np.uint8) - assert 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).astype(np.uint8) - assert len(transformed.columns) == 2 - tm.assert_index_equal(transformed.columns, Index(['one', 'two'])) - - # TODO: test correctness - - def test_get_dummies(self): - from pandas.core.reshape.reshape import get_dummies, make_axis_dummies - - self.panel['Label'] = self.panel.index.codes[1] - minor_dummies = make_axis_dummies(self.panel, 'minor').astype(np.uint8) - dummies = get_dummies(self.panel['Label']) - tm.assert_numpy_array_equal(dummies.values, minor_dummies.values) - - def test_count(self): - index = self.panel.index - - major_count = self.panel.count(level=0)['ItemA'] - level_codes = index.codes[0] - for i, idx in enumerate(index.levels[0]): - assert major_count[i] == (level_codes == i).sum() - - minor_count = self.panel.count(level=1)['ItemA'] - level_codes = index.codes[1] - for i, idx in enumerate(index.levels[1]): - assert minor_count[i] == (level_codes == i).sum() - - def test_join(self): - lp1 = self.panel.filter(['ItemA', 'ItemB']) - lp2 = self.panel.filter(['ItemC']) - - joined = lp1.join(lp2) - - assert len(joined.columns) == 3 - - pytest.raises(Exception, lp1.join, - self.panel.filter(['ItemB', 'ItemC'])) - def test_panel_index(): index = panelm.panel_index([1, 2, 3, 4], [1, 2, 3]) diff --git a/pandas/util/testing.py b/pandas/util/testing.py index 053927a77c612a..387f4023485132 100644 --- a/pandas/util/testing.py +++ b/pandas/util/testing.py @@ -34,7 +34,7 @@ import pandas as pd from pandas import ( Categorical, CategoricalIndex, DataFrame, DatetimeIndex, Index, - IntervalIndex, MultiIndex, Panel, RangeIndex, Series, bdate_range) + IntervalIndex, MultiIndex, RangeIndex, Series, bdate_range) from pandas.core.algorithms import take_1d from pandas.core.arrays import ( DatetimeArray, ExtensionArray, IntervalArray, PeriodArray, TimedeltaArray, @@ -2052,14 +2052,6 @@ def makePeriodFrame(nper=None): return DataFrame(data) -def makePanel(nper=None): - with warnings.catch_warnings(record=True): - warnings.filterwarnings("ignore", "\\nPanel", FutureWarning) - cols = ['Item' + c for c in string.ascii_uppercase[:K - 1]] - data = {c: makeTimeDataFrame(nper) for c in cols} - return Panel.fromDict(data) - - def makeCustomIndex(nentries, nlevels, prefix='#', names=False, ndupe_l=None, idx_type=None): """Create an index/multindex with given dimensions, levels, names, etc' @@ -2307,15 +2299,6 @@ def makeMissingDataframe(density=.9, random_state=None): return df -def add_nans(panel): - I, J, N = panel.shape - for i, item in enumerate(panel.items): - dm = panel[item] - for j, col in enumerate(dm.columns): - dm[col][:i + j] = np.NaN - return panel - - class TestSubDict(dict): def __init__(self, *args, **kwargs):