You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
103 lines
3.1 KiB
103 lines
3.1 KiB
import numpy as np
|
|
import pytest
|
|
|
|
from pandas._libs.parsers import (
|
|
_maybe_upcast,
|
|
na_values,
|
|
)
|
|
|
|
import pandas as pd
|
|
from pandas import NA
|
|
import pandas._testing as tm
|
|
from pandas.core.arrays import (
|
|
ArrowStringArray,
|
|
BooleanArray,
|
|
FloatingArray,
|
|
IntegerArray,
|
|
StringArray,
|
|
)
|
|
|
|
|
|
def test_maybe_upcast(any_real_numpy_dtype):
|
|
# GH#36712
|
|
|
|
dtype = np.dtype(any_real_numpy_dtype)
|
|
na_value = na_values[dtype]
|
|
arr = np.array([1, 2, na_value], dtype=dtype)
|
|
result = _maybe_upcast(arr, use_dtype_backend=True)
|
|
|
|
expected_mask = np.array([False, False, True])
|
|
if issubclass(dtype.type, np.integer):
|
|
expected = IntegerArray(arr, mask=expected_mask)
|
|
else:
|
|
expected = FloatingArray(arr, mask=expected_mask)
|
|
|
|
tm.assert_extension_array_equal(result, expected)
|
|
|
|
|
|
def test_maybe_upcast_no_na(any_real_numpy_dtype):
|
|
# GH#36712
|
|
arr = np.array([1, 2, 3], dtype=any_real_numpy_dtype)
|
|
result = _maybe_upcast(arr, use_dtype_backend=True)
|
|
|
|
expected_mask = np.array([False, False, False])
|
|
if issubclass(np.dtype(any_real_numpy_dtype).type, np.integer):
|
|
expected = IntegerArray(arr, mask=expected_mask)
|
|
else:
|
|
expected = FloatingArray(arr, mask=expected_mask)
|
|
|
|
tm.assert_extension_array_equal(result, expected)
|
|
|
|
|
|
def test_maybe_upcaste_bool():
|
|
# GH#36712
|
|
dtype = np.bool_
|
|
na_value = na_values[dtype]
|
|
arr = np.array([True, False, na_value], dtype="uint8").view(dtype)
|
|
result = _maybe_upcast(arr, use_dtype_backend=True)
|
|
|
|
expected_mask = np.array([False, False, True])
|
|
expected = BooleanArray(arr, mask=expected_mask)
|
|
tm.assert_extension_array_equal(result, expected)
|
|
|
|
|
|
def test_maybe_upcaste_bool_no_nan():
|
|
# GH#36712
|
|
dtype = np.bool_
|
|
arr = np.array([True, False, False], dtype="uint8").view(dtype)
|
|
result = _maybe_upcast(arr, use_dtype_backend=True)
|
|
|
|
expected_mask = np.array([False, False, False])
|
|
expected = BooleanArray(arr, mask=expected_mask)
|
|
tm.assert_extension_array_equal(result, expected)
|
|
|
|
|
|
def test_maybe_upcaste_all_nan():
|
|
# GH#36712
|
|
dtype = np.int64
|
|
na_value = na_values[dtype]
|
|
arr = np.array([na_value, na_value], dtype=dtype)
|
|
result = _maybe_upcast(arr, use_dtype_backend=True)
|
|
|
|
expected_mask = np.array([True, True])
|
|
expected = IntegerArray(arr, mask=expected_mask)
|
|
tm.assert_extension_array_equal(result, expected)
|
|
|
|
|
|
@pytest.mark.parametrize("val", [na_values[np.object_], "c"])
|
|
def test_maybe_upcast_object(val, string_storage):
|
|
# GH#36712
|
|
pa = pytest.importorskip("pyarrow")
|
|
|
|
with pd.option_context("mode.string_storage", string_storage):
|
|
arr = np.array(["a", "b", val], dtype=np.object_)
|
|
result = _maybe_upcast(arr, use_dtype_backend=True)
|
|
|
|
if string_storage == "python":
|
|
exp_val = "c" if val == "c" else NA
|
|
expected = StringArray(np.array(["a", "b", exp_val], dtype=np.object_))
|
|
else:
|
|
exp_val = "c" if val == "c" else None
|
|
expected = ArrowStringArray(pa.array(["a", "b", exp_val]))
|
|
tm.assert_extension_array_equal(result, expected)
|