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Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍 https://github.com/madlabunimib/PyCTBN
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PyCTBN/venv/lib/python3.9/site-packages/pandas/tests/indexing/test_callable.py

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import numpy as np
import pandas as pd
import pandas._testing as tm
class TestIndexingCallable:
def test_frame_loc_callable(self):
# GH 11485
df = pd.DataFrame({"A": [1, 2, 3, 4], "B": list("aabb"), "C": [1, 2, 3, 4]})
# iloc cannot use boolean Series (see GH3635)
# return bool indexer
res = df.loc[lambda x: x.A > 2]
tm.assert_frame_equal(res, df.loc[df.A > 2])
res = df.loc[lambda x: x.A > 2]
tm.assert_frame_equal(res, df.loc[df.A > 2])
res = df.loc[
lambda x: x.A > 2,
] # noqa: E231
tm.assert_frame_equal(res, df.loc[df.A > 2,]) # noqa: E231
res = df.loc[
lambda x: x.A > 2,
] # noqa: E231
tm.assert_frame_equal(res, df.loc[df.A > 2,]) # noqa: E231
res = df.loc[lambda x: x.B == "b", :]
tm.assert_frame_equal(res, df.loc[df.B == "b", :])
res = df.loc[lambda x: x.B == "b", :]
tm.assert_frame_equal(res, df.loc[df.B == "b", :])
res = df.loc[lambda x: x.A > 2, lambda x: x.columns == "B"]
tm.assert_frame_equal(res, df.loc[df.A > 2, [False, True, False]])
res = df.loc[lambda x: x.A > 2, lambda x: x.columns == "B"]
tm.assert_frame_equal(res, df.loc[df.A > 2, [False, True, False]])
res = df.loc[lambda x: x.A > 2, lambda x: "B"]
tm.assert_series_equal(res, df.loc[df.A > 2, "B"])
res = df.loc[lambda x: x.A > 2, lambda x: "B"]
tm.assert_series_equal(res, df.loc[df.A > 2, "B"])
res = df.loc[lambda x: x.A > 2, lambda x: ["A", "B"]]
tm.assert_frame_equal(res, df.loc[df.A > 2, ["A", "B"]])
res = df.loc[lambda x: x.A > 2, lambda x: ["A", "B"]]
tm.assert_frame_equal(res, df.loc[df.A > 2, ["A", "B"]])
res = df.loc[lambda x: x.A == 2, lambda x: ["A", "B"]]
tm.assert_frame_equal(res, df.loc[df.A == 2, ["A", "B"]])
res = df.loc[lambda x: x.A == 2, lambda x: ["A", "B"]]
tm.assert_frame_equal(res, df.loc[df.A == 2, ["A", "B"]])
# scalar
res = df.loc[lambda x: 1, lambda x: "A"]
assert res == df.loc[1, "A"]
res = df.loc[lambda x: 1, lambda x: "A"]
assert res == df.loc[1, "A"]
def test_frame_loc_callable_mixture(self):
# GH 11485
df = pd.DataFrame({"A": [1, 2, 3, 4], "B": list("aabb"), "C": [1, 2, 3, 4]})
res = df.loc[lambda x: x.A > 2, ["A", "B"]]
tm.assert_frame_equal(res, df.loc[df.A > 2, ["A", "B"]])
res = df.loc[lambda x: x.A > 2, ["A", "B"]]
tm.assert_frame_equal(res, df.loc[df.A > 2, ["A", "B"]])
res = df.loc[[2, 3], lambda x: ["A", "B"]]
tm.assert_frame_equal(res, df.loc[[2, 3], ["A", "B"]])
res = df.loc[[2, 3], lambda x: ["A", "B"]]
tm.assert_frame_equal(res, df.loc[[2, 3], ["A", "B"]])
res = df.loc[3, lambda x: ["A", "B"]]
tm.assert_series_equal(res, df.loc[3, ["A", "B"]])
res = df.loc[3, lambda x: ["A", "B"]]
tm.assert_series_equal(res, df.loc[3, ["A", "B"]])
def test_frame_loc_callable_labels(self):
# GH 11485
df = pd.DataFrame({"X": [1, 2, 3, 4], "Y": list("aabb")}, index=list("ABCD"))
# return label
res = df.loc[lambda x: ["A", "C"]]
tm.assert_frame_equal(res, df.loc[["A", "C"]])
res = df.loc[
lambda x: ["A", "C"],
] # noqa: E231
tm.assert_frame_equal(res, df.loc[["A", "C"],]) # noqa: E231
res = df.loc[lambda x: ["A", "C"], :]
tm.assert_frame_equal(res, df.loc[["A", "C"], :])
res = df.loc[lambda x: ["A", "C"], lambda x: "X"]
tm.assert_series_equal(res, df.loc[["A", "C"], "X"])
res = df.loc[lambda x: ["A", "C"], lambda x: ["X"]]
tm.assert_frame_equal(res, df.loc[["A", "C"], ["X"]])
# mixture
res = df.loc[["A", "C"], lambda x: "X"]
tm.assert_series_equal(res, df.loc[["A", "C"], "X"])
res = df.loc[["A", "C"], lambda x: ["X"]]
tm.assert_frame_equal(res, df.loc[["A", "C"], ["X"]])
res = df.loc[lambda x: ["A", "C"], "X"]
tm.assert_series_equal(res, df.loc[["A", "C"], "X"])
res = df.loc[lambda x: ["A", "C"], ["X"]]
tm.assert_frame_equal(res, df.loc[["A", "C"], ["X"]])
def test_frame_loc_callable_setitem(self):
# GH 11485
df = pd.DataFrame({"X": [1, 2, 3, 4], "Y": list("aabb")}, index=list("ABCD"))
# return label
res = df.copy()
res.loc[lambda x: ["A", "C"]] = -20
exp = df.copy()
exp.loc[["A", "C"]] = -20
tm.assert_frame_equal(res, exp)
res = df.copy()
res.loc[lambda x: ["A", "C"], :] = 20
exp = df.copy()
exp.loc[["A", "C"], :] = 20
tm.assert_frame_equal(res, exp)
res = df.copy()
res.loc[lambda x: ["A", "C"], lambda x: "X"] = -1
exp = df.copy()
exp.loc[["A", "C"], "X"] = -1
tm.assert_frame_equal(res, exp)
res = df.copy()
res.loc[lambda x: ["A", "C"], lambda x: ["X"]] = [5, 10]
exp = df.copy()
exp.loc[["A", "C"], ["X"]] = [5, 10]
tm.assert_frame_equal(res, exp)
# mixture
res = df.copy()
res.loc[["A", "C"], lambda x: "X"] = np.array([-1, -2])
exp = df.copy()
exp.loc[["A", "C"], "X"] = np.array([-1, -2])
tm.assert_frame_equal(res, exp)
res = df.copy()
res.loc[["A", "C"], lambda x: ["X"]] = 10
exp = df.copy()
exp.loc[["A", "C"], ["X"]] = 10
tm.assert_frame_equal(res, exp)
res = df.copy()
res.loc[lambda x: ["A", "C"], "X"] = -2
exp = df.copy()
exp.loc[["A", "C"], "X"] = -2
tm.assert_frame_equal(res, exp)
res = df.copy()
res.loc[lambda x: ["A", "C"], ["X"]] = -4
exp = df.copy()
exp.loc[["A", "C"], ["X"]] = -4
tm.assert_frame_equal(res, exp)
def test_frame_iloc_callable(self):
# GH 11485
df = pd.DataFrame({"X": [1, 2, 3, 4], "Y": list("aabb")}, index=list("ABCD"))
# return location
res = df.iloc[lambda x: [1, 3]]
tm.assert_frame_equal(res, df.iloc[[1, 3]])
res = df.iloc[lambda x: [1, 3], :]
tm.assert_frame_equal(res, df.iloc[[1, 3], :])
res = df.iloc[lambda x: [1, 3], lambda x: 0]
tm.assert_series_equal(res, df.iloc[[1, 3], 0])
res = df.iloc[lambda x: [1, 3], lambda x: [0]]
tm.assert_frame_equal(res, df.iloc[[1, 3], [0]])
# mixture
res = df.iloc[[1, 3], lambda x: 0]
tm.assert_series_equal(res, df.iloc[[1, 3], 0])
res = df.iloc[[1, 3], lambda x: [0]]
tm.assert_frame_equal(res, df.iloc[[1, 3], [0]])
res = df.iloc[lambda x: [1, 3], 0]
tm.assert_series_equal(res, df.iloc[[1, 3], 0])
res = df.iloc[lambda x: [1, 3], [0]]
tm.assert_frame_equal(res, df.iloc[[1, 3], [0]])
def test_frame_iloc_callable_setitem(self):
# GH 11485
df = pd.DataFrame({"X": [1, 2, 3, 4], "Y": list("aabb")}, index=list("ABCD"))
# return location
res = df.copy()
res.iloc[lambda x: [1, 3]] = 0
exp = df.copy()
exp.iloc[[1, 3]] = 0
tm.assert_frame_equal(res, exp)
res = df.copy()
res.iloc[lambda x: [1, 3], :] = -1
exp = df.copy()
exp.iloc[[1, 3], :] = -1
tm.assert_frame_equal(res, exp)
res = df.copy()
res.iloc[lambda x: [1, 3], lambda x: 0] = 5
exp = df.copy()
exp.iloc[[1, 3], 0] = 5
tm.assert_frame_equal(res, exp)
res = df.copy()
res.iloc[lambda x: [1, 3], lambda x: [0]] = 25
exp = df.copy()
exp.iloc[[1, 3], [0]] = 25
tm.assert_frame_equal(res, exp)
# mixture
res = df.copy()
res.iloc[[1, 3], lambda x: 0] = -3
exp = df.copy()
exp.iloc[[1, 3], 0] = -3
tm.assert_frame_equal(res, exp)
res = df.copy()
res.iloc[[1, 3], lambda x: [0]] = -5
exp = df.copy()
exp.iloc[[1, 3], [0]] = -5
tm.assert_frame_equal(res, exp)
res = df.copy()
res.iloc[lambda x: [1, 3], 0] = 10
exp = df.copy()
exp.iloc[[1, 3], 0] = 10
tm.assert_frame_equal(res, exp)
res = df.copy()
res.iloc[lambda x: [1, 3], [0]] = [-5, -5]
exp = df.copy()
exp.iloc[[1, 3], [0]] = [-5, -5]
tm.assert_frame_equal(res, exp)