Alle Dateien aus dem Pythonkurs
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

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)