Python pandas.util.testing.assert_contains_all() Examples

The following are 30 code examples of pandas.util.testing.assert_contains_all(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module pandas.util.testing , or try the search function .
Example #1
Source File: test_base.py    From twitter-stock-recommendation with MIT License 6 votes vote down vote up 
def test_union_dt_as_obj(self):
        # TODO: Replace with fixturesult
        with tm.assert_produces_warning(RuntimeWarning):
            firstCat = self.strIndex.union(self.dateIndex)
        secondCat = self.strIndex.union(self.strIndex)

        if self.dateIndex.dtype == np.object_:
            appended = np.append(self.strIndex, self.dateIndex)
        else:
            appended = np.append(self.strIndex, self.dateIndex.astype('O'))

        assert tm.equalContents(firstCat, appended)
        assert tm.equalContents(secondCat, self.strIndex)
        tm.assert_contains_all(self.strIndex, firstCat)
        tm.assert_contains_all(self.strIndex, secondCat)
        tm.assert_contains_all(self.dateIndex, firstCat)
Example #2
Source File: test_base.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def test_union_dt_as_obj(self):
        # TODO: Replace with fixturesult
        with tm.assert_produces_warning(RuntimeWarning):
            firstCat = self.strIndex.union(self.dateIndex)
        secondCat = self.strIndex.union(self.strIndex)

        if self.dateIndex.dtype == np.object_:
            appended = np.append(self.strIndex, self.dateIndex)
        else:
            appended = np.append(self.strIndex, self.dateIndex.astype('O'))

        assert tm.equalContents(firstCat, appended)
        assert tm.equalContents(secondCat, self.strIndex)
        tm.assert_contains_all(self.strIndex, firstCat)
        tm.assert_contains_all(self.strIndex, secondCat)
        tm.assert_contains_all(self.dateIndex, firstCat)
Example #3
Source File: test_base.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up 
def test_constructor(self):
        # regular instance creation
        tm.assert_contains_all(self.strIndex, self.strIndex)
        tm.assert_contains_all(self.dateIndex, self.dateIndex)

        # casting
        arr = np.array(self.strIndex)
        index = Index(arr)
        tm.assert_contains_all(arr, index)
        tm.assert_index_equal(self.strIndex, index)

        # copy
        arr = np.array(self.strIndex)
        index = Index(arr, copy=True, name='name')
        assert isinstance(index, Index)
        assert index.name == 'name'
        tm.assert_numpy_array_equal(arr, index.values)
        arr[0] = "SOMEBIGLONGSTRING"
        assert index[0] != "SOMEBIGLONGSTRING"

        # what to do here?
        # arr = np.array(5.)
        # pytest.raises(Exception, arr.view, Index)
Example #4
Source File: test_base.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_constructor_regular(self, attr):
        # regular instance creation
        index = getattr(self, attr)
        tm.assert_contains_all(index, index)
Example #5
Source File: test_base.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_union_dt_as_obj(self, sort):
        # TODO: Replace with fixturesult
        firstCat = self.strIndex.union(self.dateIndex)
        secondCat = self.strIndex.union(self.strIndex)

        if self.dateIndex.dtype == np.object_:
            appended = np.append(self.strIndex, self.dateIndex)
        else:
            appended = np.append(self.strIndex, self.dateIndex.astype('O'))

        assert tm.equalContents(firstCat, appended)
        assert tm.equalContents(secondCat, self.strIndex)
        tm.assert_contains_all(self.strIndex, firstCat)
        tm.assert_contains_all(self.strIndex, secondCat)
        tm.assert_contains_all(self.dateIndex, firstCat)
Example #6
Source File: test_base.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_constructor_casting(self):
        # casting
        arr = np.array(self.strIndex)
        index = Index(arr)
        tm.assert_contains_all(arr, index)
        tm.assert_index_equal(self.strIndex, index)
Example #7
Source File: test_excel.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_reading_all_sheets(self, ext):
        # Test reading all sheetnames by setting sheetname to None,
        # Ensure a dict is returned.
        # See PR #9450
        basename = 'test_multisheet'
        dfs = self.get_exceldf(basename, ext, sheet_name=None)
        # ensure this is not alphabetical to test order preservation
        expected_keys = ['Charlie', 'Alpha', 'Beta']
        tm.assert_contains_all(expected_keys, dfs.keys())
        # Issue 9930
        # Ensure sheet order is preserved
        assert expected_keys == list(dfs.keys())
Example #8
Source File: test_excel.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_reading_multiple_specific_sheets(self, ext):
        # Test reading specific sheetnames by specifying a mixed list
        # of integers and strings, and confirm that duplicated sheet
        # references (positions/names) are removed properly.
        # Ensure a dict is returned
        # See PR #9450
        basename = 'test_multisheet'
        # Explicitly request duplicates. Only the set should be returned.
        expected_keys = [2, 'Charlie', 'Charlie']
        dfs = self.get_exceldf(basename, ext, sheet_name=expected_keys)
        expected_keys = list(set(expected_keys))
        tm.assert_contains_all(expected_keys, dfs.keys())
        assert len(expected_keys) == len(dfs.keys())
Example #9
Source File: test_excel.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_reading_all_sheets_with_blank(self, ext):
        # Test reading all sheetnames by setting sheetname to None,
        # In the case where some sheets are blank.
        # Issue #11711
        basename = 'blank_with_header'
        dfs = self.get_exceldf(basename, ext, sheet_name=None)
        expected_keys = ['Sheet1', 'Sheet2', 'Sheet3']
        tm.assert_contains_all(expected_keys, dfs.keys())

    # GH6403
Example #10
Source File: test_api.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_contains(self):
        tm.assert_contains_all(self.ts.index, self.ts)
Example #11
Source File: test_excel.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_reading_all_sheets(self):
        # Test reading all sheetnames by setting sheetname to None,
        # Ensure a dict is returned.
        # See PR #9450
        basename = 'test_multisheet'
        dfs = self.get_exceldf(basename, sheet_name=None)
        # ensure this is not alphabetical to test order preservation
        expected_keys = ['Charlie', 'Alpha', 'Beta']
        tm.assert_contains_all(expected_keys, dfs.keys())
        # Issue 9930
        # Ensure sheet order is preserved
        assert expected_keys == list(dfs.keys())
Example #12
Source File: test_excel.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_reading_all_sheets_with_blank(self):
        # Test reading all sheetnames by setting sheetname to None,
        # In the case where some sheets are blank.
        # Issue #11711
        basename = 'blank_with_header'
        dfs = self.get_exceldf(basename, sheet_name=None)
        expected_keys = ['Sheet1', 'Sheet2', 'Sheet3']
        tm.assert_contains_all(expected_keys, dfs.keys())

    # GH6403
Example #13
Source File: test_base.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_constructor_regular(self, attr):
        # regular instance creation
        index = getattr(self, attr)
        tm.assert_contains_all(index, index)
Example #14
Source File: test_base.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_constructor_casting(self):
        # casting
        arr = np.array(self.strIndex)
        index = Index(arr)
        tm.assert_contains_all(arr, index)
        tm.assert_index_equal(self.strIndex, index)
Example #15
Source File: test_base.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_union_dt_as_obj(self, sort):
        # TODO: Replace with fixturesult
        firstCat = self.strIndex.union(self.dateIndex)
        secondCat = self.strIndex.union(self.strIndex)

        if self.dateIndex.dtype == np.object_:
            appended = np.append(self.strIndex, self.dateIndex)
        else:
            appended = np.append(self.strIndex, self.dateIndex.astype('O'))

        assert tm.equalContents(firstCat, appended)
        assert tm.equalContents(secondCat, self.strIndex)
        tm.assert_contains_all(self.strIndex, firstCat)
        tm.assert_contains_all(self.strIndex, secondCat)
        tm.assert_contains_all(self.dateIndex, firstCat)
Example #16
Source File: test_base.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_constructor_regular(self, attr):
        # regular instance creation
        index = getattr(self, attr)
        tm.assert_contains_all(index, index)
Example #17
Source File: test_base.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_constructor_casting(self):
        # casting
        arr = np.array(self.strIndex)
        index = Index(arr)
        tm.assert_contains_all(arr, index)
        tm.assert_index_equal(self.strIndex, index)
Example #18
Source File: test_excel.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_reading_all_sheets_with_blank(self, ext):
        # Test reading all sheetnames by setting sheetname to None,
        # In the case where some sheets are blank.
        # Issue #11711
        basename = 'blank_with_header'
        dfs = self.get_exceldf(basename, ext, sheet_name=None)
        expected_keys = ['Sheet1', 'Sheet2', 'Sheet3']
        tm.assert_contains_all(expected_keys, dfs.keys())

    # GH6403
Example #19
Source File: test_base.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_constructor_regular(self, attr):
        # regular instance creation
        index = getattr(self, attr)
        tm.assert_contains_all(index, index)
Example #20
Source File: test_excel.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_reading_multiple_specific_sheets(self, ext):
        # Test reading specific sheetnames by specifying a mixed list
        # of integers and strings, and confirm that duplicated sheet
        # references (positions/names) are removed properly.
        # Ensure a dict is returned
        # See PR #9450
        basename = 'test_multisheet'
        # Explicitly request duplicates. Only the set should be returned.
        expected_keys = [2, 'Charlie', 'Charlie']
        dfs = self.get_exceldf(basename, ext, sheet_name=expected_keys)
        expected_keys = list(set(expected_keys))
        tm.assert_contains_all(expected_keys, dfs.keys())
        assert len(expected_keys) == len(dfs.keys())
Example #21
Source File: test_excel.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_reading_all_sheets(self, ext):
        # Test reading all sheetnames by setting sheetname to None,
        # Ensure a dict is returned.
        # See PR #9450
        basename = 'test_multisheet'
        dfs = self.get_exceldf(basename, ext, sheet_name=None)
        # ensure this is not alphabetical to test order preservation
        expected_keys = ['Charlie', 'Alpha', 'Beta']
        tm.assert_contains_all(expected_keys, dfs.keys())
        # Issue 9930
        # Ensure sheet order is preserved
        assert expected_keys == list(dfs.keys())
Example #22
Source File: test_base.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_constructor_casting(self):
        # casting
        arr = np.array(self.strIndex)
        index = Index(arr)
        tm.assert_contains_all(arr, index)
        tm.assert_index_equal(self.strIndex, index)
Example #23
Source File: test_base.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_constructor_casting(self):
        # casting
        arr = np.array(self.strIndex)
        index = Index(arr)
        tm.assert_contains_all(arr, index)
        tm.assert_index_equal(self.strIndex, index)
Example #24
Source File: test_base.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_constructor_regular(self, attr):
        # regular instance creation
        index = getattr(self, attr)
        tm.assert_contains_all(index, index)
Example #25
Source File: test_base.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_union_dt_as_obj(self, sort):
        # TODO: Replace with fixturesult
        firstCat = self.strIndex.union(self.dateIndex)
        secondCat = self.strIndex.union(self.strIndex)

        if self.dateIndex.dtype == np.object_:
            appended = np.append(self.strIndex, self.dateIndex)
        else:
            appended = np.append(self.strIndex, self.dateIndex.astype('O'))

        assert tm.equalContents(firstCat, appended)
        assert tm.equalContents(secondCat, self.strIndex)
        tm.assert_contains_all(self.strIndex, firstCat)
        tm.assert_contains_all(self.strIndex, secondCat)
        tm.assert_contains_all(self.dateIndex, firstCat)
Example #26
Source File: test_excel.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_reading_all_sheets_with_blank(self, ext):
        # Test reading all sheetnames by setting sheetname to None,
        # In the case where some sheets are blank.
        # Issue #11711
        basename = 'blank_with_header'
        dfs = self.get_exceldf(basename, ext, sheet_name=None)
        expected_keys = ['Sheet1', 'Sheet2', 'Sheet3']
        tm.assert_contains_all(expected_keys, dfs.keys())

    # GH6403
Example #27
Source File: test_excel.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_reading_all_sheets(self, ext):
        # Test reading all sheetnames by setting sheetname to None,
        # Ensure a dict is returned.
        # See PR #9450
        basename = 'test_multisheet'
        dfs = self.get_exceldf(basename, ext, sheet_name=None)
        # ensure this is not alphabetical to test order preservation
        expected_keys = ['Charlie', 'Alpha', 'Beta']
        tm.assert_contains_all(expected_keys, dfs.keys())
        # Issue 9930
        # Ensure sheet order is preserved
        assert expected_keys == list(dfs.keys())
Example #28
Source File: test_excel.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_reading_multiple_specific_sheets(self, ext):
        # Test reading specific sheetnames by specifying a mixed list
        # of integers and strings, and confirm that duplicated sheet
        # references (positions/names) are removed properly.
        # Ensure a dict is returned
        # See PR #9450
        basename = 'test_multisheet'
        # Explicitly request duplicates. Only the set should be returned.
        expected_keys = [2, 'Charlie', 'Charlie']
        dfs = self.get_exceldf(basename, ext, sheet_name=expected_keys)
        expected_keys = list(set(expected_keys))
        tm.assert_contains_all(expected_keys, dfs.keys())
        assert len(expected_keys) == len(dfs.keys())
Example #29
Source File: test_to_from_scipy.py    From vnpy_crypto with MIT License 4 votes vote down vote up 
def test_from_to_scipy(spmatrix, index, columns, fill_value, dtype):
    # GH 4343
    # Make one ndarray and from it one sparse matrix, both to be used for
    # constructing frames and comparing results
    arr = np.eye(3, dtype=dtype)
    # GH 16179
    arr[0, 1] = dtype(2)
    try:
        spm = spmatrix(arr)
        assert spm.dtype == arr.dtype
    except (TypeError, AssertionError):
        # If conversion to sparse fails for this spmatrix type and arr.dtype,
        # then the combination is not currently supported in NumPy, so we
        # can just skip testing it thoroughly
        return

    sdf = SparseDataFrame(spm, index=index, columns=columns,
                          default_fill_value=fill_value)

    # Expected result construction is kind of tricky for all
    # dtype-fill_value combinations; easiest to cast to something generic
    # and except later on
    rarr = arr.astype(object)
    rarr[arr == 0] = np.nan
    expected = SparseDataFrame(rarr, index=index, columns=columns).fillna(
        fill_value if fill_value is not None else np.nan)

    # Assert frame is as expected
    sdf_obj = sdf.astype(object)
    tm.assert_sp_frame_equal(sdf_obj, expected)
    tm.assert_frame_equal(sdf_obj.to_dense(), expected.to_dense())

    # Assert spmatrices equal
    assert dict(sdf.to_coo().todok()) == dict(spm.todok())

    # Ensure dtype is preserved if possible
    was_upcast = ((fill_value is None or is_float(fill_value)) and
                  not is_object_dtype(dtype) and
                  not is_float_dtype(dtype))
    res_dtype = (bool if is_bool_dtype(dtype) else
                 float if was_upcast else
                 dtype)
    tm.assert_contains_all(sdf.dtypes, {np.dtype(res_dtype)})
    assert sdf.to_coo().dtype == res_dtype

    # However, adding a str column results in an upcast to object
    sdf['strings'] = np.arange(len(sdf)).astype(str)
    assert sdf.to_coo().dtype == np.object_
Example #30
Source File: test_to_from_scipy.py    From recruit with Apache License 2.0 4 votes vote down vote up 
def test_from_to_scipy_object(spmatrix, fill_value):
    # GH 4343
    dtype = object
    columns = list('cd')
    index = list('ab')

    if (spmatrix is scipy.sparse.dok_matrix and LooseVersion(
            scipy.__version__) >= LooseVersion('0.19.0')):
        pytest.skip("dok_matrix from object does not work in SciPy >= 0.19")

    # Make one ndarray and from it one sparse matrix, both to be used for
    # constructing frames and comparing results
    arr = np.eye(2, dtype=dtype)
    try:
        spm = spmatrix(arr)
        assert spm.dtype == arr.dtype
    except (TypeError, AssertionError):
        # If conversion to sparse fails for this spmatrix type and arr.dtype,
        # then the combination is not currently supported in NumPy, so we
        # can just skip testing it thoroughly
        return

    sdf = SparseDataFrame(spm, index=index, columns=columns,
                          default_fill_value=fill_value)

    # Expected result construction is kind of tricky for all
    # dtype-fill_value combinations; easiest to cast to something generic
    # and except later on
    rarr = arr.astype(object)
    rarr[arr == 0] = np.nan
    expected = SparseDataFrame(rarr, index=index, columns=columns).fillna(
        fill_value if fill_value is not None else np.nan)

    # Assert frame is as expected
    sdf_obj = sdf.astype(SparseDtype(object, fill_value))
    tm.assert_sp_frame_equal(sdf_obj, expected)
    tm.assert_frame_equal(sdf_obj.to_dense(), expected.to_dense())

    # Assert spmatrices equal
    assert dict(sdf.to_coo().todok()) == dict(spm.todok())

    # Ensure dtype is preserved if possible
    res_dtype = object
    tm.assert_contains_all(sdf.dtypes.apply(lambda dtype: dtype.subtype),
                           {np.dtype(res_dtype)})
    assert sdf.to_coo().dtype == res_dtype