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130 lines
3.4 KiB
130 lines
3.4 KiB
import numpy as np
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import pandas as pd
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import pandas._testing as tm
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def test_mutate_groups():
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# GH3380
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df = pd.DataFrame(
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{
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"cat1": ["a"] * 8 + ["b"] * 6,
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"cat2": ["c"] * 2
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+ ["d"] * 2
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+ ["e"] * 2
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+ ["f"] * 2
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+ ["c"] * 2
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+ ["d"] * 2
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+ ["e"] * 2,
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"cat3": [f"g{x}" for x in range(1, 15)],
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"val": np.random.randint(100, size=14),
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}
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)
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def f_copy(x):
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x = x.copy()
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x["rank"] = x.val.rank(method="min")
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return x.groupby("cat2")["rank"].min()
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def f_no_copy(x):
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x["rank"] = x.val.rank(method="min")
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return x.groupby("cat2")["rank"].min()
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grpby_copy = df.groupby("cat1").apply(f_copy)
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grpby_no_copy = df.groupby("cat1").apply(f_no_copy)
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tm.assert_series_equal(grpby_copy, grpby_no_copy)
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def test_no_mutate_but_looks_like():
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# GH 8467
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# first show's mutation indicator
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# second does not, but should yield the same results
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df = pd.DataFrame({"key": [1, 1, 1, 2, 2, 2, 3, 3, 3], "value": range(9)})
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result1 = df.groupby("key", group_keys=True).apply(lambda x: x[:].key)
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result2 = df.groupby("key", group_keys=True).apply(lambda x: x.key)
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tm.assert_series_equal(result1, result2)
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def test_apply_function_with_indexing():
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# GH: 33058
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df = pd.DataFrame(
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{"col1": ["A", "A", "A", "B", "B", "B"], "col2": [1, 2, 3, 4, 5, 6]}
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)
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def fn(x):
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x.col2[x.index[-1]] = 0
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return x.col2
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result = df.groupby(["col1"], as_index=False).apply(fn)
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expected = pd.Series(
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[1, 2, 0, 4, 5, 0],
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index=pd.MultiIndex.from_tuples(
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[(0, 0), (0, 1), (0, 2), (1, 3), (1, 4), (1, 5)]
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),
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name="col2",
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)
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tm.assert_series_equal(result, expected)
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def test_apply_mutate_columns_multiindex():
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# GH 12652
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df = pd.DataFrame(
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{
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("C", "julian"): [1, 2, 3],
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("B", "geoffrey"): [1, 2, 3],
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("A", "julian"): [1, 2, 3],
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("B", "julian"): [1, 2, 3],
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("A", "geoffrey"): [1, 2, 3],
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("C", "geoffrey"): [1, 2, 3],
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},
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columns=pd.MultiIndex.from_tuples(
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[
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("A", "julian"),
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("A", "geoffrey"),
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("B", "julian"),
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("B", "geoffrey"),
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("C", "julian"),
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("C", "geoffrey"),
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]
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),
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)
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def add_column(grouped):
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name = grouped.columns[0][1]
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grouped["sum", name] = grouped.sum(axis=1)
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return grouped
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result = df.groupby(level=1, axis=1).apply(add_column)
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expected = pd.DataFrame(
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[
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[1, 1, 1, 3, 1, 1, 1, 3],
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[2, 2, 2, 6, 2, 2, 2, 6],
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[
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3,
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3,
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3,
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9,
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3,
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3,
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3,
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9,
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],
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],
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columns=pd.MultiIndex.from_tuples(
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[
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("geoffrey", "A", "geoffrey"),
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("geoffrey", "B", "geoffrey"),
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("geoffrey", "C", "geoffrey"),
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("geoffrey", "sum", "geoffrey"),
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("julian", "A", "julian"),
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("julian", "B", "julian"),
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("julian", "C", "julian"),
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("julian", "sum", "julian"),
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]
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),
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)
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tm.assert_frame_equal(result, expected)
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