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from collections.abc import Callable
import copy
from datetime import datetime
import operator
import re
import numpy as np
import pytest
from pandas._libs.properties import cache_readonly
import pandas as pd
import pandas._testing as tm
from pandas.api.typing import Expression
from pandas.tests.test_register_accessor import ensure_removed
@pytest.mark.parametrize(
("expr", "expected_values", "expected_str"),
[
(pd.col("a"), [1, 2], "col('a')"),
(pd.col("a") * 2, [2, 4], "col('a') * 2"),
(pd.col("a").sum(), [3, 3], "col('a').sum()"),
(pd.col("a") + 1, [2, 3], "col('a') + 1"),
(1 + pd.col("a"), [2, 3], "1 + col('a')"),
(pd.col("a") - 1, [0, 1], "col('a') - 1"),
(1 - pd.col("a"), [0, -1], "1 - col('a')"),
(pd.col("a") * 1, [1, 2], "col('a') * 1"),
(1 * pd.col("a"), [1, 2], "1 * col('a')"),
(2 ** pd.col("a"), [2, 4], "2 ** col('a')"),
(pd.col("a") ** 2, [1, 4], "col('a') ** 2"),
(pd.col("a") / 1, [1.0, 2.0], "col('a') / 1"),
(1 / pd.col("a"), [1.0, 0.5], "1 / col('a')"),
(pd.col("a") // 1, [1, 2], "col('a') // 1"),
(1 // pd.col("a"), [1, 0], "1 // col('a')"),
(pd.col("a") % 1, [0, 0], "col('a') % 1"),
(1 % pd.col("a"), [0, 1], "1 % col('a')"),
(pd.col("a") > 1, [False, True], "col('a') > 1"),
(pd.col("a") >= 1, [True, True], "col('a') >= 1"),
(pd.col("a") < 1, [False, False], "col('a') < 1"),
(pd.col("a") <= 1, [True, False], "col('a') <= 1"),
(pd.col("a") == 1, [True, False], "col('a') == 1"),
(np.power(pd.col("a"), 2), [1, 4], "power(col('a'), 2)"),
(np.divide(pd.col("a"), pd.col("a")), [1.0, 1.0], "divide(col('a'), col('a'))"),
(
(pd.col("a") + 1) * (pd.col("b") + 2),
[10, 18],
"(col('a') + 1) * (col('b') + 2)",
),
(
(pd.col("a") - 1).astype("bool"),
[False, True],
"(col('a') - 1).astype('bool')",
),
# Unary operators
(-pd.col("a"), [-1, -2], "-col('a')"),
(+pd.col("a"), [1, 2], "+col('a')"),
(-(pd.col("a") + 1), [-2, -3], "-(col('a') + 1)"),
(-pd.col("a") * 2, [-2, -4], "(-col('a')) * 2"),
(abs(pd.col("a")), [1, 2], "abs(col('a'))"),
(abs(pd.col("a") - 2), [1, 0], "abs(col('a') - 2)"),
],
)
def test_col_simple(
expr: Expression, expected_values: list[object], expected_str: str
) -> None:
# https://github.com/pandas-dev/pandas/pull/64267
df = pd.DataFrame({"a": [1, 2], "b": [3, 4]})
result = df.assign(c=expr)
expected = pd.DataFrame({"a": [1, 2], "b": [3, 4], "c": expected_values})
tm.assert_frame_equal(result, expected)
assert str(expr) == expected_str
@pytest.mark.parametrize(
("op", "expected_values", "expected_str"),
[
(operator.iadd, [3, 4], "col('a') + 2"),
(operator.iand, [0, 2], "col('a') & 2"),
(operator.ifloordiv, [0, 1], "col('a') // 2"),
(operator.imod, [1, 0], "col('a') % 2"),
(operator.imul, [2, 4], "col('a') * 2"),
(operator.ior, [3, 2], "col('a') | 2"),
(operator.ipow, [1, 4], "col('a') ** 2"),
(operator.isub, [-1, 0], "col('a') - 2"),
(operator.itruediv, [0.5, 1.0], "col('a') / 2"),
(operator.ixor, [3, 0], "col('a') ^ 2"),
],
)
def test_inplace_ops(
op: Callable, expected_values: list[object], expected_str: str
) -> None:
# https://github.com/pandas-dev/pandas/pull/64267
df = pd.DataFrame({"a": [1, 2]})
expr = pd.col("a")
expr = op(expr, 2)
result = df.assign(c=expr)
expected = pd.DataFrame({"a": [1, 2], "c": expected_values})
tm.assert_frame_equal(result, expected)
assert str(expr) == expected_str
def test_matmul():
# https://github.com/pandas-dev/pandas/pull/64267
df = pd.DataFrame({"a": [1, 2]})
expr = pd.col("a") @ [3, 4]
result = df.assign(c=expr)
expected = pd.DataFrame({"a": [1, 2], "c": [11, 11]})
tm.assert_frame_equal(result, expected)
assert str(expr) == "col('a') @ [3, 4]"
expr = [3, 4] @ pd.col("a")
result = df.assign(c=expr)
expected = pd.DataFrame({"a": [1, 2], "c": [11, 11]})
tm.assert_frame_equal(result, expected)
assert str(expr) == "[3, 4] @ col('a')"
def test_frame_getitem() -> None:
# https://github.com/pandas-dev/pandas/pull/63439
df = pd.DataFrame({"a": [1, 2], "b": [3, 4]})
expr = pd.col("a") == 2
result = df[expr]
expected = df.iloc[[1]]
tm.assert_frame_equal(result, expected)
def test_frame_setitem() -> None:
# https://github.com/pandas-dev/pandas/pull/63439
df = pd.DataFrame({"a": [1, 2], "b": [3, 4]})
expr = pd.col("a") == 2
result = df.copy()
result[expr] = 100
expected = pd.DataFrame({"a": [1, 100], "b": [3, 100]})
tm.assert_frame_equal(result, expected)
def test_frame_loc() -> None:
# https://github.com/pandas-dev/pandas/pull/63439
df = pd.DataFrame({"a": [1, 2], "b": [3, 4]})
expr = pd.col("a") == 2
result = df.copy()
result.loc[expr, "b"] = 100
expected = pd.DataFrame({"a": [1, 2], "b": [3, 100]})
tm.assert_frame_equal(result, expected)
def test_frame_iloc() -> None:
# https://github.com/pandas-dev/pandas/pull/63439
df = pd.DataFrame({"a": [1, 2], "b": [3, 4]})
expr = pd.col("a") == 2
result = df.copy()
result.iloc[expr, 1] = 100
expected = pd.DataFrame({"a": [1, 2], "b": [3, 100]})
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize(
("expr", "expected_values", "expected_str"),
[
(pd.col("a").dt.year, [2020], "col('a').dt.year"),
(pd.col("a").dt.strftime("%B"), ["January"], "col('a').dt.strftime('%B')"),
(pd.col("b").str.upper(), ["FOO"], "col('b').str.upper()"),
],
)
def test_namespaces(
expr: Expression, expected_values: list[object], expected_str: str
) -> None:
df = pd.DataFrame({"a": [datetime(2020, 1, 1)], "b": ["foo"]})
result = df.assign(c=expr)
expected = pd.DataFrame(
{"a": [datetime(2020, 1, 1)], "b": ["foo"], "c": expected_values}
)
tm.assert_frame_equal(result, expected, check_dtype=False)
assert str(expr) == expected_str
def test_invalid() -> None:
df = pd.DataFrame({"a": [1, 2], "b": [3, 4]})
with pytest.raises(ValueError, match=r"did you mean one of \['a', 'b'\] instead"):
df.assign(c=pd.col("c").mean())
df = pd.DataFrame({f"col_{i}": [0] for i in range(11)})
msg = (
"did you mean one of "
r"\['col_0', 'col_1', 'col_2', 'col_3', "
"'col_4', 'col_5', 'col_6', 'col_7', "
r"'col_8', 'col_9',\.\.\.\] instead"
)
""
with pytest.raises(ValueError, match=msg):
df.assign(c=pd.col("c").mean())
def test_custom_accessor() -> None:
df = pd.DataFrame({"a": [1, 2, 3]})
class XYZAccessor:
def __init__(self, pandas_obj):
self._obj = pandas_obj
def mean(self):
return self._obj.mean()
with ensure_removed(pd.Series, "xyz"):
pd.api.extensions.register_series_accessor("xyz")(XYZAccessor)
result = df.assign(b=pd.col("a").xyz.mean())
expected = pd.DataFrame({"a": [1, 2, 3], "b": [2.0, 2.0, 2.0]})
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize(
("expr", "expected_values", "expected_str"),
[
(
pd.col("a") & pd.col("b"),
[False, False, True, False],
"col('a') & col('b')",
),
(
pd.col("a") & True,
[True, False, True, False],
"col('a') & True",
),
(
pd.col("a") | pd.col("b"),
[True, True, True, True],
"col('a') | col('b')",
),
(
pd.col("a") | False,
[True, False, True, False],
"col('a') | False",
),
(
pd.col("a") ^ pd.col("b"),
[True, True, False, True],
"col('a') ^ col('b')",
),
(
pd.col("a") ^ True,
[False, True, False, True],
"col('a') ^ True",
),
(
~pd.col("a"),
[False, True, False, True],
"~col('a')",
),
],
)
def test_col_logical_ops(
expr: Expression, expected_values: list[bool], expected_str: str
) -> None:
# https://github.com/pandas-dev/pandas/issues/63322
df = pd.DataFrame({"a": [True, False, True, False], "b": [False, True, True, True]})
result = df.assign(c=expr)
expected = pd.DataFrame(
{
"a": [True, False, True, False],
"b": [False, True, True, True],
"c": expected_values,
}
)
tm.assert_frame_equal(result, expected)
assert str(expr) == expected_str
# Test that the expression works with .loc
result = df.loc[expr]
expected = df[expected_values]
tm.assert_frame_equal(result, expected)
def test_expression_getitem() -> None:
# https://github.com/pandas-dev/pandas/pull/63439
df = pd.DataFrame({"a": [1, 2, 3]})
expr = pd.col("a")[1]
expected_str = "col('a')[1]"
assert str(expr) == expected_str
result = df.assign(b=expr)
expected = pd.DataFrame({"a": [1, 2, 3], "b": [2, 2, 2]})
tm.assert_frame_equal(result, expected)
def test_property() -> None:
# https://github.com/pandas-dev/pandas/pull/63439
df = pd.DataFrame({"a": [1, 2, 3]})
expr = pd.col("a").index
expected_str = "col('a').index"
assert str(expr) == expected_str
result = df.assign(b=expr)
expected = pd.DataFrame({"a": [1, 2, 3], "b": [0, 1, 2]})
tm.assert_frame_equal(result, expected)
def test_cached_property() -> None:
# https://github.com/pandas-dev/pandas/pull/63439
# Ensure test is valid
assert isinstance(pd.Index.dtype, cache_readonly)
df = pd.DataFrame({"a": [1, 2, 3]})
expr = pd.col("a").index.dtype
expected_str = "col('a').index.dtype"
assert str(expr) == expected_str
result = df.assign(b=expr)
expected = pd.DataFrame({"a": [1, 2, 3], "b": np.int64})
tm.assert_frame_equal(result, expected)
def test_qcut() -> None:
# https://github.com/pandas-dev/pandas/pull/63439
df = pd.DataFrame({"a": [1, 2, 3]})
expr = pd.qcut(pd.col("a"), 3)
expected_str = "qcut(x=col('a'), q=3, labels=None, retbins=False, precision=3)"
assert str(expr) == expected_str, str(expr)
result = df.assign(b=expr)
expected = pd.DataFrame({"a": [1, 2, 3], "b": pd.qcut(df["a"], 3)})
tm.assert_frame_equal(result, expected)
def test_where() -> None:
# https://github.com/pandas-dev/pandas/pull/63439
df = pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]})
expr = pd.col("a").where(pd.col("b") == 5, 100)
expected_str = "col('a').where(col('b') == 5, 100)"
assert str(expr) == expected_str, str(expr)
result = df.assign(c=expr)
expected = pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6], "c": [100, 2, 100]})
tm.assert_frame_equal(result, expected)
expr = pd.col("a").where(pd.col("b") == 5, pd.col("a") + 1)
expected_str = "col('a').where(col('b') == 5, col('a') + 1)"
assert str(expr) == expected_str, str(expr)
result = df.assign(c=expr)
expected = pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6], "c": [2, 2, 4]})
tm.assert_frame_equal(result, expected)
# Unsupported ops
def test_bool():
with pytest.raises(TypeError, match="boolean value of an expression is ambiguous"):
bool(pd.col("a"))
def test_iter():
with pytest.raises(TypeError, match="Expression objects are not iterable"):
iter(pd.col("a"))
def test_contains():
# Python 3.14 changes the message from "is not iterable" to
# "is not a container or iterable"
with pytest.raises(
TypeError, match="argument of type 'Expression' is not .*iterable"
):
1 in pd.col("a")
def test_copy():
with pytest.raises(TypeError, match="Expression objects are not copiable"):
copy.copy(pd.col("a"))
def test_deepcopy():
with pytest.raises(TypeError, match="Expression objects are not copiable"):
copy.deepcopy(pd.col("a"))
def test_divmod():
msg = re.escape("unsupported operand type(s) for divmod(): 'Expression' and 'int'")
with pytest.raises(TypeError, match=msg):
divmod(pd.col("a"), 2)
def test_len():
with pytest.raises(TypeError, match="object of type 'Expression' has no len()"):
len(pd.col("a"))
def test_round():
msg = "type Expression doesn't define __round__ method"
with pytest.raises(TypeError, match=msg):
round(pd.col("a"), 2)