FM / reshape

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

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

Name	Size	Mode	Actions
merge/	-	0755	rm
__pycache__/	-	0755	rm
test_concat.py	104885	0644	edit dl rm
test_crosstab.py	25412	0644	edit dl rm
test_cut.py	20198	0644	edit dl rm
test_get_dummies.py	23290	0644	edit dl rm
test_melt.py	37162	0644	edit dl rm
test_pivot.py	70218	0644	edit dl rm
test_pivot_multilevel.py	5818	0644	edit dl rm
test_qcut.py	8205	0644	edit dl rm
test_union_categoricals.py	14321	0644	edit dl rm
test_util.py	2441	0644	edit dl rm
__init__.py	0	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/pandas/tests/reshape/test_pivot_multilevel.py (5818B)

import numpy as np
import pytest

import pandas as pd
from pandas import Index, MultiIndex
import pandas._testing as tm

@pytest.mark.parametrize(
    "input_index, input_columns, input_values, "
    "expected_values, expected_columns, expected_index",
    [
        (
            ["lev4"],
            "lev3",
            "values",
            [
                [0.0, np.nan],
                [np.nan, 1.0],
                [2.0, np.nan],
                [np.nan, 3.0],
                [4.0, np.nan],
                [np.nan, 5.0],
                [6.0, np.nan],
                [np.nan, 7.0],
            ],
            Index([1, 2], name="lev3"),
            Index([1, 2, 3, 4, 5, 6, 7, 8], name="lev4"),
        ),
        (
            ["lev4"],
            "lev3",
            None,
            [
                [1.0, np.nan, 1.0, np.nan, 0.0, np.nan],
                [np.nan, 1.0, np.nan, 1.0, np.nan, 1.0],
                [1.0, np.nan, 2.0, np.nan, 2.0, np.nan],
                [np.nan, 1.0, np.nan, 2.0, np.nan, 3.0],
                [2.0, np.nan, 1.0, np.nan, 4.0, np.nan],
                [np.nan, 2.0, np.nan, 1.0, np.nan, 5.0],
                [2.0, np.nan, 2.0, np.nan, 6.0, np.nan],
                [np.nan, 2.0, np.nan, 2.0, np.nan, 7.0],
            ],
            MultiIndex.from_tuples(
                [
                    ("lev1", 1),
                    ("lev1", 2),
                    ("lev2", 1),
                    ("lev2", 2),
                    ("values", 1),
                    ("values", 2),
                ],
                names=[None, "lev3"],
            ),
            Index([1, 2, 3, 4, 5, 6, 7, 8], name="lev4"),
        ),
        (
            ["lev1", "lev2"],
            "lev3",
            "values",
            [[0, 1], [2, 3], [4, 5], [6, 7]],
            Index([1, 2], name="lev3"),
            MultiIndex.from_tuples(
                [(1, 1), (1, 2), (2, 1), (2, 2)], names=["lev1", "lev2"]
            ),
        ),
        (
            ["lev1", "lev2"],
            "lev3",
            None,
            [[1, 2, 0, 1], [3, 4, 2, 3], [5, 6, 4, 5], [7, 8, 6, 7]],
            MultiIndex.from_tuples(
                [("lev4", 1), ("lev4", 2), ("values", 1), ("values", 2)],
                names=[None, "lev3"],
            ),
            MultiIndex.from_tuples(
                [(1, 1), (1, 2), (2, 1), (2, 2)], names=["lev1", "lev2"]
            ),
        ),
    ],
)
def test_pivot_list_like_index(
    input_index,
    input_columns,
    input_values,
    expected_values,
    expected_columns,
    expected_index,
):
    # GH 21425, test when index is given a list
    df = pd.DataFrame(
        {
            "lev1": [1, 1, 1, 1, 2, 2, 2, 2],
            "lev2": [1, 1, 2, 2, 1, 1, 2, 2],
            "lev3": [1, 2, 1, 2, 1, 2, 1, 2],
            "lev4": [1, 2, 3, 4, 5, 6, 7, 8],
            "values": [0, 1, 2, 3, 4, 5, 6, 7],
        }
    )

result = df.pivot(index=input_index, columns=input_columns, values=input_values)
    expected = pd.DataFrame(
        expected_values, columns=expected_columns, index=expected_index
    )
    tm.assert_frame_equal(result, expected)

@pytest.mark.parametrize(
    "input_index, input_columns, input_values, "
    "expected_values, expected_columns, expected_index",
    [
        (
            "lev4",
            ["lev3"],
            "values",
            [
                [0.0, np.nan],
                [np.nan, 1.0],
                [2.0, np.nan],
                [np.nan, 3.0],
                [4.0, np.nan],
                [np.nan, 5.0],
                [6.0, np.nan],
                [np.nan, 7.0],
            ],
            Index([1, 2], name="lev3"),
            Index([1, 2, 3, 4, 5, 6, 7, 8], name="lev4"),
        ),
        (
            ["lev1", "lev2"],
            ["lev3"],
            "values",
            [[0, 1], [2, 3], [4, 5], [6, 7]],
            Index([1, 2], name="lev3"),
            MultiIndex.from_tuples(
                [(1, 1), (1, 2), (2, 1), (2, 2)], names=["lev1", "lev2"]
            ),
        ),
        (
            ["lev1"],
            ["lev2", "lev3"],
            "values",
            [[0, 1, 2, 3], [4, 5, 6, 7]],
            MultiIndex.from_tuples(
                [(1, 1), (1, 2), (2, 1), (2, 2)], names=["lev2", "lev3"]
            ),
            Index([1, 2], name="lev1"),
        ),
        (
            ["lev1", "lev2"],
            ["lev3", "lev4"],
            "values",
            [
                [0.0, 1.0, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan],
                [np.nan, np.nan, 2.0, 3.0, np.nan, np.nan, np.nan, np.nan],
                [np.nan, np.nan, np.nan, np.nan, 4.0, 5.0, np.nan, np.nan],
                [np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, 6.0, 7.0],
            ],
            MultiIndex.from_tuples(
                [(1, 1), (2, 2), (1, 3), (2, 4), (1, 5), (2, 6), (1, 7), (2, 8)],
                names=["lev3", "lev4"],
            ),
            MultiIndex.from_tuples(
                [(1, 1), (1, 2), (2, 1), (2, 2)], names=["lev1", "lev2"]
            ),
        ),
    ],
)
def test_pivot_list_like_columns(
    input_index,
    input_columns,
    input_values,
    expected_values,
    expected_columns,
    expected_index,
):
    # GH 21425, test when columns is given a list
    df = pd.DataFrame(
        {
            "lev1": [1, 1, 1, 1, 2, 2, 2, 2],
            "lev2": [1, 1, 2, 2, 1, 1, 2, 2],
            "lev3": [1, 2, 1, 2, 1, 2, 1, 2],
            "lev4": [1, 2, 3, 4, 5, 6, 7, 8],
            "values": [0, 1, 2, 3, 4, 5, 6, 7],
        }
    )

import numpy as np import pytest import pandas as pd from pandas import Index, MultiIndex import pandas._testing as tm @pytest.mark.parametrize( "input_index, input_columns, input_values, " "expected_values, expected_columns, expected_index", [ ( ["lev4"], "lev3", "values", [ [0.0, np.nan], [np.nan, 1.0], [2.0, np.nan], [np.nan, 3.0], [4.0, np.nan], [np.nan, 5.0], [6.0, np.nan], [np.nan, 7.0], ], Index([1, 2], name="lev3"), Index([1, 2, 3, 4, 5, 6, 7, 8], name="lev4"), ), ( ["lev4"], "lev3", None, [ [1.0, np.nan, 1.0, np.nan, 0.0, np.nan], [np.nan, 1.0, np.nan, 1.0, np.nan, 1.0], [1.0, np.nan, 2.0, np.nan, 2.0, np.nan], [np.nan, 1.0, np.nan, 2.0, np.nan, 3.0], [2.0, np.nan, 1.0, np.nan, 4.0, np.nan], [np.nan, 2.0, np.nan, 1.0, np.nan, 5.0], [2.0, np.nan, 2.0, np.nan, 6.0, np.nan], [np.nan, 2.0, np.nan, 2.0, np.nan, 7.0], ], MultiIndex.from_tuples( [ ("lev1", 1), ("lev1", 2), ("lev2", 1), ("lev2", 2), ("values", 1), ("values", 2), ], names=[None, "lev3"], ), Index([1, 2, 3, 4, 5, 6, 7, 8], name="lev4"), ), ( ["lev1", "lev2"], "lev3", "values", [[0, 1], [2, 3], [4, 5], [6, 7]], Index([1, 2], name="lev3"), MultiIndex.from_tuples( [(1, 1), (1, 2), (2, 1), (2, 2)], names=["lev1", "lev2"] ), ), ( ["lev1", "lev2"], "lev3", None, [[1, 2, 0, 1], [3, 4, 2, 3], [5, 6, 4, 5], [7, 8, 6, 7]], MultiIndex.from_tuples( [("lev4", 1), ("lev4", 2), ("values", 1), ("values", 2)], names=[None, "lev3"], ), MultiIndex.from_tuples( [(1, 1), (1, 2), (2, 1), (2, 2)], names=["lev1", "lev2"] ), ), ], ) def test_pivot_list_like_index( input_index, input_columns, input_values, expected_values, expected_columns, expected_index, ): # GH 21425, test when index is given a list df = pd.DataFrame( { "lev1": [1, 1, 1, 1, 2, 2, 2, 2], "lev2": [1, 1, 2, 2, 1, 1, 2, 2], "lev3": [1, 2, 1, 2, 1, 2, 1, 2], "lev4": [1, 2, 3, 4, 5, 6, 7, 8], "values": [0, 1, 2, 3, 4, 5, 6, 7], } ) result = df.pivot(index=input_index, columns=input_columns, values=input_values) expected = pd.DataFrame( expected_values, columns=expected_columns, index=expected_index ) tm.assert_frame_equal(result, expected) @pytest.mark.parametrize( "input_index, input_columns, input_values, " "expected_values, expected_columns, expected_index", [ ( "lev4", ["lev3"], "values", [ [0.0, np.nan], [np.nan, 1.0], [2.0, np.nan], [np.nan, 3.0], [4.0, np.nan], [np.nan, 5.0], [6.0, np.nan], [np.nan, 7.0], ], Index([1, 2], name="lev3"), Index([1, 2, 3, 4, 5, 6, 7, 8], name="lev4"), ), ( ["lev1", "lev2"], ["lev3"], "values", [[0, 1], [2, 3], [4, 5], [6, 7]], Index([1, 2], name="lev3"), MultiIndex.from_tuples( [(1, 1), (1, 2), (2, 1), (2, 2)], names=["lev1", "lev2"] ), ), ( ["lev1"], ["lev2", "lev3"], "values", [[0, 1, 2, 3], [4, 5, 6, 7]], MultiIndex.from_tuples( [(1, 1), (1, 2), (2, 1), (2, 2)], names=["lev2", "lev3"] ), Index([1, 2], name="lev1"), ), ( ["lev1", "lev2"], ["lev3", "lev4"], "values", [ [0.0, 1.0, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan], [np.nan, np.nan, 2.0, 3.0, np.nan, np.nan, np.nan, np.nan], [np.nan, np.nan, np.nan, np.nan, 4.0, 5.0, np.nan, np.nan], [np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, 6.0, 7.0], ], MultiIndex.from_tuples( [(1, 1), (2, 2), (1, 3), (2, 4), (1, 5), (2, 6), (1, 7), (2, 8)], names=["lev3", "lev4"], ), MultiIndex.from_tuples( [(1, 1), (1, 2), (2, 1), (2, 2)], names=["lev1", "lev2"] ), ), ], ) def test_pivot_list_like_columns( input_index, input_columns, input_values, expected_values, expected_columns, expected_index, ): # GH 21425, test when columns is given a list df = pd.DataFrame( { "lev1": [1, 1, 1, 1, 2, 2, 2, 2], "lev2": [1, 1, 2, 2, 1, 1, 2, 2], "lev3": [1, 2, 1, 2, 1, 2, 1, 2], "lev4": [1, 2, 3, 4, 5, 6, 7, 8], "values": [0, 1, 2, 3, 4, 5, 6, 7], } ) result = df.pivot(index=input_index, columns=input_columns, values=input_values) expected = pd.DataFrame( expected_values, columns=expected_columns, index=expected_index ) tm.assert_frame_equal(result, expected)