FM / generic

/usr/local/lib64/python3.6/site-packages/pandas/tests/generic/

/usr/local/lib64/python3.6/site-packages/pandas/tests/generic

Name	Size	Mode	Actions
methods/	-	0755	rm
__pycache__/	-	0755	rm
test_finalize.py	27578	0644	edit dl rm
test_frame.py	7703	0644	edit dl rm
test_generic.py	30202	0644	edit dl rm
test_label_or_level_utils.py	9968	0644	edit dl rm
test_series.py	5945	0644	edit dl rm
test_to_xarray.py	4587	0644	edit dl rm
__init__.py	0	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/pandas/tests/generic/test_label_or_level_utils.py (9968B)

import pytest

from pandas.core.dtypes.missing import array_equivalent

import pandas as pd

# Fixtures
# ========
@pytest.fixture
def df():
    """DataFrame with columns 'L1', 'L2', and 'L3' """
    return pd.DataFrame({"L1": [1, 2, 3], "L2": [11, 12, 13], "L3": ["A", "B", "C"]})

@pytest.fixture(params=[[], ["L1"], ["L1", "L2"], ["L1", "L2", "L3"]])
def df_levels(request, df):
    """DataFrame with columns or index levels 'L1', 'L2', and 'L3' """
    levels = request.param

if levels:
        df = df.set_index(levels)

return df

@pytest.fixture
def df_ambig(df):
    """DataFrame with levels 'L1' and 'L2' and labels 'L1' and 'L3' """
    df = df.set_index(["L1", "L2"])

df["L1"] = df["L3"]

return df

@pytest.fixture
def df_duplabels(df):
    """DataFrame with level 'L1' and labels 'L2', 'L3', and 'L2' """
    df = df.set_index(["L1"])
    df = pd.concat([df, df["L2"]], axis=1)

return df

# Test is label/level reference
# =============================
def get_labels_levels(df_levels):
    expected_labels = list(df_levels.columns)
    expected_levels = [name for name in df_levels.index.names if name is not None]
    return expected_labels, expected_levels

def assert_label_reference(frame, labels, axis):
    for label in labels:
        assert frame._is_label_reference(label, axis=axis)
        assert not frame._is_level_reference(label, axis=axis)
        assert frame._is_label_or_level_reference(label, axis=axis)

def assert_level_reference(frame, levels, axis):
    for level in levels:
        assert frame._is_level_reference(level, axis=axis)
        assert not frame._is_label_reference(level, axis=axis)
        assert frame._is_label_or_level_reference(level, axis=axis)

# DataFrame
# ---------
def test_is_level_or_label_reference_df_simple(df_levels, axis):

# Compute expected labels and levels
    expected_labels, expected_levels = get_labels_levels(df_levels)

# Transpose frame if axis == 1
    if axis in {1, "columns"}:
        df_levels = df_levels.T

# Perform checks
    assert_level_reference(df_levels, expected_levels, axis=axis)
    assert_label_reference(df_levels, expected_labels, axis=axis)

def test_is_level_reference_df_ambig(df_ambig, axis):

# Transpose frame if axis == 1
    if axis in {1, "columns"}:
        df_ambig = df_ambig.T

# df has both an on-axis level and off-axis label named L1
    # Therefore L1 should reference the label, not the level
    assert_label_reference(df_ambig, ["L1"], axis=axis)

# df has an on-axis level named L2 and it is not ambiguous
    # Therefore L2 is an level reference
    assert_level_reference(df_ambig, ["L2"], axis=axis)

# df has a column named L3 and it not an level reference
    assert_label_reference(df_ambig, ["L3"], axis=axis)

# Series
# ------
def test_is_level_reference_series_simple_axis0(df):

# Make series with L1 as index
    s = df.set_index("L1").L2
    assert_level_reference(s, ["L1"], axis=0)
    assert not s._is_level_reference("L2")

# Make series with L1 and L2 as index
    s = df.set_index(["L1", "L2"]).L3
    assert_level_reference(s, ["L1", "L2"], axis=0)
    assert not s._is_level_reference("L3")

def test_is_level_reference_series_axis1_error(df):

# Make series with L1 as index
    s = df.set_index("L1").L2

with pytest.raises(ValueError, match="No axis named 1"):
        s._is_level_reference("L1", axis=1)

# Test _check_label_or_level_ambiguity_df
# =======================================

# DataFrame
# ---------
def test_check_label_or_level_ambiguity_df(df_ambig, axis):

# Transpose frame if axis == 1
    if axis in {1, "columns"}:
        df_ambig = df_ambig.T

if axis in {0, "index"}:
        msg = "'L1' is both an index level and a column label"
    else:
        msg = "'L1' is both a column level and an index label"

# df_ambig has both an on-axis level and off-axis label named L1
    # Therefore, L1 is ambiguous.
    with pytest.raises(ValueError, match=msg):
        df_ambig._check_label_or_level_ambiguity("L1", axis=axis)

# df_ambig has an on-axis level named L2,, and it is not ambiguous.
    df_ambig._check_label_or_level_ambiguity("L2", axis=axis)

# df_ambig has an off-axis label named L3, and it is not ambiguous
    assert not df_ambig._check_label_or_level_ambiguity("L3", axis=axis)

# Series
# ------
def test_check_label_or_level_ambiguity_series(df):

# A series has no columns and therefore references are never ambiguous

# Make series with L1 as index
    s = df.set_index("L1").L2
    s._check_label_or_level_ambiguity("L1", axis=0)
    s._check_label_or_level_ambiguity("L2", axis=0)

# Make series with L1 and L2 as index
    s = df.set_index(["L1", "L2"]).L3
    s._check_label_or_level_ambiguity("L1", axis=0)
    s._check_label_or_level_ambiguity("L2", axis=0)
    s._check_label_or_level_ambiguity("L3", axis=0)

def test_check_label_or_level_ambiguity_series_axis1_error(df):

# Make series with L1 as index
    s = df.set_index("L1").L2

with pytest.raises(ValueError, match="No axis named 1"):
        s._check_label_or_level_ambiguity("L1", axis=1)

# Test _get_label_or_level_values
# ===============================
def assert_label_values(frame, labels, axis):
    for label in labels:
        if axis in {0, "index"}:
            expected = frame[label]._values
        else:
            expected = frame.loc[label]._values

result = frame._get_label_or_level_values(label, axis=axis)
        assert array_equivalent(expected, result)

def assert_level_values(frame, levels, axis):
    for level in levels:
        if axis in {0, "index"}:
            expected = frame.index.get_level_values(level=level)._values
        else:
            expected = frame.columns.get_level_values(level=level)._values

result = frame._get_label_or_level_values(level, axis=axis)
        assert array_equivalent(expected, result)

# DataFrame
# ---------
def test_get_label_or_level_values_df_simple(df_levels, axis):

# Compute expected labels and levels
    expected_labels, expected_levels = get_labels_levels(df_levels)

# Transpose frame if axis == 1
    if axis in {1, "columns"}:
        df_levels = df_levels.T

# Perform checks
    assert_label_values(df_levels, expected_labels, axis=axis)
    assert_level_values(df_levels, expected_levels, axis=axis)

def test_get_label_or_level_values_df_ambig(df_ambig, axis):

# Transpose frame if axis == 1
    if axis in {1, "columns"}:
        df_ambig = df_ambig.T

# df has an on-axis level named L2, and it is not ambiguous.
    assert_level_values(df_ambig, ["L2"], axis=axis)

# df has an off-axis label named L3, and it is not ambiguous.
    assert_label_values(df_ambig, ["L3"], axis=axis)

def test_get_label_or_level_values_df_duplabels(df_duplabels, axis):

# Transpose frame if axis == 1
    if axis in {1, "columns"}:
        df_duplabels = df_duplabels.T

# df has unambiguous level 'L1'
    assert_level_values(df_duplabels, ["L1"], axis=axis)

# df has unique label 'L3'
    assert_label_values(df_duplabels, ["L3"], axis=axis)

# df has duplicate labels 'L2'
    if axis in {0, "index"}:
        expected_msg = "The column label 'L2' is not unique"
    else:
        expected_msg = "The index label 'L2' is not unique"

with pytest.raises(ValueError, match=expected_msg):
        assert_label_values(df_duplabels, ["L2"], axis=axis)

# Series
# ------
def test_get_label_or_level_values_series_axis0(df):

# Make series with L1 as index
    s = df.set_index("L1").L2
    assert_level_values(s, ["L1"], axis=0)

# Make series with L1 and L2 as index
    s = df.set_index(["L1", "L2"]).L3
    assert_level_values(s, ["L1", "L2"], axis=0)

def test_get_label_or_level_values_series_axis1_error(df):

# Make series with L1 as index
    s = df.set_index("L1").L2

with pytest.raises(ValueError, match="No axis named 1"):
        s._get_label_or_level_values("L1", axis=1)

# Test _drop_labels_or_levels
# ===========================
def assert_labels_dropped(frame, labels, axis):
    for label in labels:
        df_dropped = frame._drop_labels_or_levels(label, axis=axis)

if axis in {0, "index"}:
            assert label in frame.columns
            assert label not in df_dropped.columns
        else:
            assert label in frame.index
            assert label not in df_dropped.index

def assert_levels_dropped(frame, levels, axis):
    for level in levels:
        df_dropped = frame._drop_labels_or_levels(level, axis=axis)

if axis in {0, "index"}:
            assert level in frame.index.names
            assert level not in df_dropped.index.names
        else:
            assert level in frame.columns.names
            assert level not in df_dropped.columns.names

# DataFrame
# ---------
def test_drop_labels_or_levels_df(df_levels, axis):

# Compute expected labels and levels
    expected_labels, expected_levels = get_labels_levels(df_levels)

# Transpose frame if axis == 1
    if axis in {1, "columns"}:
        df_levels = df_levels.T

# Perform checks
    assert_labels_dropped(df_levels, expected_labels, axis=axis)
    assert_levels_dropped(df_levels, expected_levels, axis=axis)

with pytest.raises(ValueError, match="not valid labels or levels"):
        df_levels._drop_labels_or_levels("L4", axis=axis)

# Series
# ------
def test_drop_labels_or_levels_series(df):

# Make series with L1 as index
    s = df.set_index("L1").L2
    assert_levels_dropped(s, ["L1"], axis=0)

with pytest.raises(ValueError, match="not valid labels or levels"):
        s._drop_labels_or_levels("L4", axis=0)

# Make series with L1 and L2 as index
    s = df.set_index(["L1", "L2"]).L3
    assert_levels_dropped(s, ["L1", "L2"], axis=0)

with pytest.raises(ValueError, match="not valid labels or levels"):
        s._drop_labels_or_levels("L4", axis=0)

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