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| import numpy as np
| import pytest
|
| from pandas._libs import lib
|
| 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",
| lib.NoDefault,
| [
| [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",
| lib.NoDefault,
| [[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)
|
|
| def test_pivot_multiindexed_rows_and_cols(using_array_manager):
| # GH 36360
|
| df = pd.DataFrame(
| data=np.arange(12).reshape(4, 3),
| columns=MultiIndex.from_tuples(
| [(0, 0), (0, 1), (0, 2)], names=["col_L0", "col_L1"]
| ),
| index=MultiIndex.from_tuples(
| [(0, 0, 0), (0, 0, 1), (1, 1, 1), (1, 0, 0)],
| names=["idx_L0", "idx_L1", "idx_L2"],
| ),
| )
|
| res = df.pivot_table(
| index=["idx_L0"],
| columns=["idx_L1"],
| values=[(0, 1)],
| aggfunc=lambda col: col.values.sum(),
| )
|
| expected = pd.DataFrame(
| data=[[5, np.nan], [10, 7.0]],
| columns=MultiIndex.from_tuples(
| [(0, 1, 0), (0, 1, 1)], names=["col_L0", "col_L1", "idx_L1"]
| ),
| index=Index([0, 1], dtype="int64", name="idx_L0"),
| )
| if not using_array_manager:
| # BlockManager does not preserve the dtypes
| expected = expected.astype("float64")
|
| tm.assert_frame_equal(res, expected)
|
|
| def test_pivot_df_multiindex_index_none():
| # GH 23955
| df = pd.DataFrame(
| [
| ["A", "A1", "label1", 1],
| ["A", "A2", "label2", 2],
| ["B", "A1", "label1", 3],
| ["B", "A2", "label2", 4],
| ],
| columns=["index_1", "index_2", "label", "value"],
| )
| df = df.set_index(["index_1", "index_2"])
|
| result = df.pivot(columns="label", values="value")
| expected = pd.DataFrame(
| [[1.0, np.nan], [np.nan, 2.0], [3.0, np.nan], [np.nan, 4.0]],
| index=df.index,
| columns=Index(["label1", "label2"], name="label"),
| )
| tm.assert_frame_equal(result, expected)
|
|
