Addition of a Series[int] with a complex returns Series[unknown]

[loicdiridollou]

import pandas as pd

c = 1 + 1j
s = pd.Series([1.0, 2.0, 3.0])

check(assert_type(s + c, "pd.Series[complex]"), pd.Series) ■ "assert_type" mismatch: expected "Series[complex]" but received "Series[unknown]"

Please complete the following information:

OS: Darwin
OS Version [e.g. 22]: 15.2
python version: 3.12.7
version of type checker: mypy latest
version of installed pandas-stubs: latest
Additional context

version of pandas: 2.2.3
mypy option: strict=False

[Dr-Irv]

Need to update the various operators to handle arguments that are complex

[loicdiridollou]

Also another issue about the __sub__ and __mul__ operators between two Series[int]:

s = pd.Series([0, 1, -10])
s2 = pd.Series([7, -5, 10])

check(assert_type(s - s2, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s * s2,  "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s / s2, "pd.Series[float]"), pd.Series, np.float64)

[loicdiridollou]

s1 = pd.Series([0, 1, 2, 3])
s2 = pd.Series([-1, 2, -3, 4])
df1 = pd.DataFrame([[0, 1], [-2, 3], [4, -5], [6, 7]])
n1 = np.array([[0, 1], [1, 2], [-1, -1], [2, 0]])
check(assert_type(s1.dot(s2), Scalar), np.int64)
check(assert_type(s1 @ s2, Scalar), np.int64)
check(assert_type(s1.dot(df1), "pd.Series[int]"), pd.Series, np.int64)
check(assert_type(s1.dot(s2), Scalar), np.integer)
check(assert_type(s1 @ s2, Scalar), np.integer)
check(assert_type(s1.dot(df1), "pd.Series[int]"), pd.Series, np.integer)  # should be float here as we don't know the type of the df