ai-content-maker/.venv/Lib/site-packages/pandas/tests/series/methods/test_update.py

134 lines
4.6 KiB
Python
Raw Permalink Normal View History

2024-05-03 04:18:51 +03:00
import numpy as np
import pytest
import pandas.util._test_decorators as td
from pandas import (
CategoricalDtype,
DataFrame,
NaT,
Series,
Timestamp,
)
import pandas._testing as tm
class TestUpdate:
def test_update(self, using_copy_on_write):
s = Series([1.5, np.nan, 3.0, 4.0, np.nan])
s2 = Series([np.nan, 3.5, np.nan, 5.0])
s.update(s2)
expected = Series([1.5, 3.5, 3.0, 5.0, np.nan])
tm.assert_series_equal(s, expected)
# GH 3217
df = DataFrame([{"a": 1}, {"a": 3, "b": 2}])
df["c"] = np.nan
df_orig = df.copy()
df["c"].update(Series(["foo"], index=[0]))
if using_copy_on_write:
expected = df_orig
else:
expected = DataFrame(
[[1, np.nan, "foo"], [3, 2.0, np.nan]], columns=["a", "b", "c"]
)
tm.assert_frame_equal(df, expected)
@pytest.mark.parametrize(
"other, dtype, expected",
[
# other is int
([61, 63], "int32", Series([10, 61, 12], dtype="int32")),
([61, 63], "int64", Series([10, 61, 12])),
([61, 63], float, Series([10.0, 61.0, 12.0])),
([61, 63], object, Series([10, 61, 12], dtype=object)),
# other is float, but can be cast to int
([61.0, 63.0], "int32", Series([10, 61, 12], dtype="int32")),
([61.0, 63.0], "int64", Series([10, 61, 12])),
([61.0, 63.0], float, Series([10.0, 61.0, 12.0])),
([61.0, 63.0], object, Series([10, 61.0, 12], dtype=object)),
# others is float, cannot be cast to int
([61.1, 63.1], "int32", Series([10.0, 61.1, 12.0])),
([61.1, 63.1], "int64", Series([10.0, 61.1, 12.0])),
([61.1, 63.1], float, Series([10.0, 61.1, 12.0])),
([61.1, 63.1], object, Series([10, 61.1, 12], dtype=object)),
# other is object, cannot be cast
([(61,), (63,)], "int32", Series([10, (61,), 12])),
([(61,), (63,)], "int64", Series([10, (61,), 12])),
([(61,), (63,)], float, Series([10.0, (61,), 12.0])),
([(61,), (63,)], object, Series([10, (61,), 12])),
],
)
def test_update_dtypes(self, other, dtype, expected):
ser = Series([10, 11, 12], dtype=dtype)
other = Series(other, index=[1, 3])
ser.update(other)
tm.assert_series_equal(ser, expected)
@pytest.mark.parametrize(
"series, other, expected",
[
# update by key
(
Series({"a": 1, "b": 2, "c": 3, "d": 4}),
{"b": 5, "c": np.nan},
Series({"a": 1, "b": 5, "c": 3, "d": 4}),
),
# update by position
(Series([1, 2, 3, 4]), [np.nan, 5, 1], Series([1, 5, 1, 4])),
],
)
def test_update_from_non_series(self, series, other, expected):
# GH 33215
series.update(other)
tm.assert_series_equal(series, expected)
@pytest.mark.parametrize(
"data, other, expected, dtype",
[
(["a", None], [None, "b"], ["a", "b"], "string[python]"),
pytest.param(
["a", None],
[None, "b"],
["a", "b"],
"string[pyarrow]",
marks=td.skip_if_no("pyarrow", min_version="1.0.0"),
),
([1, None], [None, 2], [1, 2], "Int64"),
([True, None], [None, False], [True, False], "boolean"),
(
["a", None],
[None, "b"],
["a", "b"],
CategoricalDtype(categories=["a", "b"]),
),
(
[Timestamp(year=2020, month=1, day=1, tz="Europe/London"), NaT],
[NaT, Timestamp(year=2020, month=1, day=1, tz="Europe/London")],
[Timestamp(year=2020, month=1, day=1, tz="Europe/London")] * 2,
"datetime64[ns, Europe/London]",
),
],
)
def test_update_extension_array_series(self, data, other, expected, dtype):
result = Series(data, dtype=dtype)
other = Series(other, dtype=dtype)
expected = Series(expected, dtype=dtype)
result.update(other)
tm.assert_series_equal(result, expected)
def test_update_with_categorical_type(self):
# GH 25744
dtype = CategoricalDtype(["a", "b", "c", "d"])
s1 = Series(["a", "b", "c"], index=[1, 2, 3], dtype=dtype)
s2 = Series(["b", "a"], index=[1, 2], dtype=dtype)
s1.update(s2)
result = s1
expected = Series(["b", "a", "c"], index=[1, 2, 3], dtype=dtype)
tm.assert_series_equal(result, expected)