Python MultiIndex.from_product方法代碼示例

# 需要導入模塊: from pandas import MultiIndex [as 別名]
# 或者: from pandas.MultiIndex import from_product [as 別名]
def test_labels_dtypes():

    # GH 8456
    i = MultiIndex.from_tuples([('A', 1), ('A', 2)])
    assert i.codes[0].dtype == 'int8'
    assert i.codes[1].dtype == 'int8'

    i = MultiIndex.from_product([['a'], range(40)])
    assert i.codes[1].dtype == 'int8'
    i = MultiIndex.from_product([['a'], range(400)])
    assert i.codes[1].dtype == 'int16'
    i = MultiIndex.from_product([['a'], range(40000)])
    assert i.codes[1].dtype == 'int32'

    i = pd.MultiIndex.from_product([['a'], range(1000)])
    assert (i.codes[0] >= 0).all()
    assert (i.codes[1] >= 0).all() 

# 需要導入模塊: from pandas import MultiIndex [as 別名]
# 或者: from pandas.MultiIndex import from_product [as 別名]
def take_invalid_kwargs():
    vals = [['A', 'B'],
            [pd.Timestamp('2011-01-01'), pd.Timestamp('2011-01-02')]]
    idx = pd.MultiIndex.from_product(vals, names=['str', 'dt'])
    indices = [1, 2]

    msg = r"take\(\) got an unexpected keyword argument 'foo'"
    with pytest.raises(TypeError, match=msg):
        idx.take(indices, foo=2)

    msg = "the 'out' parameter is not supported"
    with pytest.raises(ValueError, match=msg):
        idx.take(indices, out=indices)

    msg = "the 'mode' parameter is not supported"
    with pytest.raises(ValueError, match=msg):
        idx.take(indices, mode='clip') 

# 需要導入模塊: from pandas import MultiIndex [as 別名]
# 或者: from pandas.MultiIndex import from_product [as 別名]
def test_large_multiindex_error():
    # GH12527
    df_below_1000000 = pd.DataFrame(
        1, index=pd.MultiIndex.from_product([[1, 2], range(499999)]),
        columns=['dest'])
    with pytest.raises(KeyError):
        df_below_1000000.loc[(-1, 0), 'dest']
    with pytest.raises(KeyError):
        df_below_1000000.loc[(3, 0), 'dest']
    df_above_1000000 = pd.DataFrame(
        1, index=pd.MultiIndex.from_product([[1, 2], range(500001)]),
        columns=['dest'])
    with pytest.raises(KeyError):
        df_above_1000000.loc[(-1, 0), 'dest']
    with pytest.raises(KeyError):
        df_above_1000000.loc[(3, 0), 'dest'] 

# 需要導入模塊: from pandas import MultiIndex [as 別名]
# 或者: from pandas.MultiIndex import from_product [as 別名]
def test_from_product_iterator():
    # GH 18434
    first = ['foo', 'bar', 'buz']
    second = ['a', 'b', 'c']
    names = ['first', 'second']
    tuples = [('foo', 'a'), ('foo', 'b'), ('foo', 'c'), ('bar', 'a'),
              ('bar', 'b'), ('bar', 'c'), ('buz', 'a'), ('buz', 'b'),
              ('buz', 'c')]
    expected = MultiIndex.from_tuples(tuples, names=names)

    # iterator as input
    result = MultiIndex.from_product(iter([first, second]), names=names)
    tm.assert_index_equal(result, expected)

    # Invalid non-iterable input
    msg = "Input must be a list / sequence of iterables."
    with pytest.raises(TypeError, match=msg):
        MultiIndex.from_product(0) 

# 需要導入模塊: from pandas import MultiIndex [as 別名]
# 或者: from pandas.MultiIndex import from_product [as 別名]
def test_getitem_partial_int(self):
        # GH 12416
        # with single item
        l1 = [10, 20]
        l2 = ['a', 'b']
        df = DataFrame(index=range(2),
                       columns=MultiIndex.from_product([l1, l2]))
        expected = DataFrame(index=range(2),
                             columns=l2)
        result = df[20]
        tm.assert_frame_equal(result, expected)

        # with list
        expected = DataFrame(index=range(2),
                             columns=MultiIndex.from_product([l1[1:], l2]))
        result = df[[20]]
        tm.assert_frame_equal(result, expected)

        # missing item:
        with pytest.raises(KeyError, match='1'):
            df[1]
        with pytest.raises(KeyError, match=r"'\[1\] not in index'"):
            df[[1]] 

# 需要導入模塊: from pandas import MultiIndex [as 別名]
# 或者: from pandas.MultiIndex import from_product [as 別名]
def test_loc_multiindex_indexer_none(self):

        # GH6788
        # multi-index indexer is None (meaning take all)
        attributes = ['Attribute' + str(i) for i in range(1)]
        attribute_values = ['Value' + str(i) for i in range(5)]

        index = MultiIndex.from_product([attributes, attribute_values])
        df = 0.1 * np.random.randn(10, 1 * 5) + 0.5
        df = DataFrame(df, columns=index)
        result = df[attributes]
        tm.assert_frame_equal(result, df)

        # GH 7349
        # loc with a multi-index seems to be doing fallback
        df = DataFrame(np.arange(12).reshape(-1, 1),
                       index=MultiIndex.from_product([[1, 2, 3, 4],
                                                      [1, 2, 3]]))

        expected = df.loc[([1, 2], ), :]
        result = df.loc[[1, 2]]
        tm.assert_frame_equal(result, expected) 

# 需要導入模塊: from pandas import MultiIndex [as 別名]
# 或者: from pandas.MultiIndex import from_product [as 別名]
def test_multiindex_contains_dropped(self):
        # GH 19027
        # test that dropped MultiIndex levels are not in the MultiIndex
        # despite continuing to be in the MultiIndex's levels
        idx = MultiIndex.from_product([[1, 2], [3, 4]])
        assert 2 in idx
        idx = idx.drop(2)

        # drop implementation keeps 2 in the levels
        assert 2 in idx.levels[0]
        # but it should no longer be in the index itself
        assert 2 not in idx

        # also applies to strings
        idx = MultiIndex.from_product([['a', 'b'], ['c', 'd']])
        assert 'a' in idx
        idx = idx.drop('a')
        assert 'a' in idx.levels[0]
        assert 'a' not in idx 

# 需要導入模塊: from pandas import MultiIndex [as 別名]
# 或者: from pandas.MultiIndex import from_product [as 別名]
def test_rename_axis_mapper(self):
        # GH 19978
        mi = MultiIndex.from_product([['a', 'b', 'c'], [1, 2]],
                                     names=['ll', 'nn'])
        s = Series([i for i in range(len(mi))], index=mi)

        result = s.rename_axis(index={'ll': 'foo'})
        assert result.index.names == ['foo', 'nn']

        result = s.rename_axis(index=str.upper, axis=0)
        assert result.index.names == ['LL', 'NN']

        result = s.rename_axis(index=['foo', 'goo'])
        assert result.index.names == ['foo', 'goo']

        with pytest.raises(TypeError, match='unexpected'):
            s.rename_axis(columns='wrong') 

# 需要導入模塊: from pandas import MultiIndex [as 別名]
# 或者: from pandas.MultiIndex import from_product [as 別名]
def test_cat_on_filtered_index(self):
        df = DataFrame(index=MultiIndex.from_product(
            [[2011, 2012], [1, 2, 3]], names=['year', 'month']))

        df = df.reset_index()
        df = df[df.month > 1]

        str_year = df.year.astype('str')
        str_month = df.month.astype('str')
        str_both = str_year.str.cat(str_month, sep=' ')

        assert str_both.loc[1] == '2011 2'

        str_multiple = str_year.str.cat([str_month, str_month], sep=' ')

        assert str_multiple.loc[1] == '2011 2 2' 

# 需要導入模塊: from pandas import MultiIndex [as 別名]
# 或者: from pandas.MultiIndex import from_product [as 別名]
def test_delitem_multiindex(self):
        midx = MultiIndex.from_product([['A', 'B'], [1, 2]])
        df = DataFrame(np.random.randn(4, 4), columns=midx)
        assert len(df.columns) == 4
        assert ('A', ) in df.columns
        assert 'A' in df.columns

        result = df['A']
        assert isinstance(result, DataFrame)
        del df['A']

        assert len(df.columns) == 2

        # A still in the levels, BUT get a KeyError if trying
        # to delete
        assert ('A', ) not in df.columns
        with pytest.raises(KeyError):
            del df[('A',)]

        # behavior of dropped/deleted MultiIndex levels changed from
        # GH 2770 to GH 19027: MultiIndex no longer '.__contains__'
        # levels which are dropped/deleted
        assert 'A' not in df.columns
        with pytest.raises(KeyError):
            del df['A'] 

# 需要導入模塊: from pandas import MultiIndex [as 別名]
# 或者: from pandas.MultiIndex import from_product [as 別名]
def test_cat_on_filtered_index(self):
        df = DataFrame(index=MultiIndex.from_product(
            [[2011, 2012], [1, 2, 3]], names=['year', 'month']))

        df = df.reset_index()
        df = df[df.month > 1]

        str_year = df.year.astype('str')
        str_month = df.month.astype('str')
        str_both = str_year.str.cat(str_month, sep=' ', join='left')

        assert str_both.loc[1] == '2011 2'

        str_multiple = str_year.str.cat([str_month, str_month],
                                        sep=' ', join='left')

        assert str_multiple.loc[1] == '2011 2 2' 

# 需要導入模塊: from pandas import MultiIndex [as 別名]
# 或者: from pandas.MultiIndex import from_product [as 別名]
def test_repeat():
    reps = 2
    numbers = [1, 2, 3]
    names = np.array(['foo', 'bar'])

    m = MultiIndex.from_product([
        numbers, names], names=names)
    expected = MultiIndex.from_product([
        numbers, names.repeat(reps)], names=names)
    tm.assert_index_equal(m.repeat(reps), expected) 

# 需要導入模塊: from pandas import MultiIndex [as 別名]
# 或者: from pandas.MultiIndex import from_product [as 別名]
def test_repr_roundtrip():

    mi = MultiIndex.from_product([list('ab'), range(3)],
                                 names=['first', 'second'])
    str(mi)

    if PY3:
        tm.assert_index_equal(eval(repr(mi)), mi, exact=True)
    else:
        result = eval(repr(mi))
        # string coerces to unicode
        tm.assert_index_equal(result, mi, exact=False)
        assert mi.get_level_values('first').inferred_type == 'string'
        assert result.get_level_values('first').inferred_type == 'unicode'

    mi_u = MultiIndex.from_product(
        [list(u'ab'), range(3)], names=['first', 'second'])
    result = eval(repr(mi_u))
    tm.assert_index_equal(result, mi_u, exact=True)

    # formatting
    if PY3:
        str(mi)
    else:
        compat.text_type(mi)

    # long format
    mi = MultiIndex.from_product([list('abcdefg'), range(10)],
                                 names=['first', 'second'])

    if PY3:
        tm.assert_index_equal(eval(repr(mi)), mi, exact=True)
    else:
        result = eval(repr(mi))
        # string coerces to unicode
        tm.assert_index_equal(result, mi, exact=False)
        assert mi.get_level_values('first').inferred_type == 'string'
        assert result.get_level_values('first').inferred_type == 'unicode'

    result = eval(repr(mi_u))
    tm.assert_index_equal(result, mi_u, exact=True) 

# 需要導入模塊: from pandas import MultiIndex [as 別名]
# 或者: from pandas.MultiIndex import from_product [as 別名]
def test_roundtrip_pickle_with_tz():
    return

    # GH 8367
    # round-trip of timezone
    index = MultiIndex.from_product(
        [[1, 2], ['a', 'b'], date_range('20130101', periods=3,
                                        tz='US/Eastern')
         ], names=['one', 'two', 'three'])
    unpickled = tm.round_trip_pickle(index)
    assert index.equal_levels(unpickled) 

# 需要導入模塊: from pandas import MultiIndex [as 別名]
# 或者: from pandas.MultiIndex import from_product [as 別名]
def test_contains_top_level():
    midx = MultiIndex.from_product([['A', 'B'], [1, 2]])
    assert 'A' in midx
    assert 'A' not in midx._engine