69 lines
1.6 KiB
Python
69 lines
1.6 KiB
Python
|
import numpy as np
|
||
|
import pytest
|
||
|
|
||
|
import pandas as pd
|
||
|
from pandas.core.arrays.integer import (
|
||
|
Int8Dtype,
|
||
|
Int16Dtype,
|
||
|
Int32Dtype,
|
||
|
Int64Dtype,
|
||
|
UInt8Dtype,
|
||
|
UInt16Dtype,
|
||
|
UInt32Dtype,
|
||
|
UInt64Dtype,
|
||
|
)
|
||
|
|
||
|
|
||
|
def test_dtypes(dtype):
|
||
|
# smoke tests on auto dtype construction
|
||
|
|
||
|
if dtype.is_signed_integer:
|
||
|
assert np.dtype(dtype.type).kind == "i"
|
||
|
else:
|
||
|
assert np.dtype(dtype.type).kind == "u"
|
||
|
assert dtype.name is not None
|
||
|
|
||
|
|
||
|
@pytest.mark.parametrize(
|
||
|
"dtype, expected",
|
||
|
[
|
||
|
(Int8Dtype(), "Int8Dtype()"),
|
||
|
(Int16Dtype(), "Int16Dtype()"),
|
||
|
(Int32Dtype(), "Int32Dtype()"),
|
||
|
(Int64Dtype(), "Int64Dtype()"),
|
||
|
(UInt8Dtype(), "UInt8Dtype()"),
|
||
|
(UInt16Dtype(), "UInt16Dtype()"),
|
||
|
(UInt32Dtype(), "UInt32Dtype()"),
|
||
|
(UInt64Dtype(), "UInt64Dtype()"),
|
||
|
],
|
||
|
)
|
||
|
def test_repr_dtype(dtype, expected):
|
||
|
assert repr(dtype) == expected
|
||
|
|
||
|
|
||
|
def test_repr_array():
|
||
|
result = repr(pd.array([1, None, 3]))
|
||
|
expected = "<IntegerArray>\n[1, <NA>, 3]\nLength: 3, dtype: Int64"
|
||
|
assert result == expected
|
||
|
|
||
|
|
||
|
def test_repr_array_long():
|
||
|
data = pd.array([1, 2, None] * 1000)
|
||
|
expected = (
|
||
|
"<IntegerArray>\n"
|
||
|
"[ 1, 2, <NA>, 1, 2, <NA>, 1, 2, <NA>, 1,\n"
|
||
|
" ...\n"
|
||
|
" <NA>, 1, 2, <NA>, 1, 2, <NA>, 1, 2, <NA>]\n"
|
||
|
"Length: 3000, dtype: Int64"
|
||
|
)
|
||
|
result = repr(data)
|
||
|
assert result == expected
|
||
|
|
||
|
|
||
|
def test_frame_repr(data_missing):
|
||
|
|
||
|
df = pd.DataFrame({"A": data_missing})
|
||
|
result = repr(df)
|
||
|
expected = " A\n0 <NA>\n1 1"
|
||
|
assert result == expected
|