48 lines
1.1 KiB
Python
48 lines
1.1 KiB
Python
import numpy as np
|
|
import pytest
|
|
|
|
import pandas as pd
|
|
from pandas.core.arrays.floating import (
|
|
Float32Dtype,
|
|
Float64Dtype,
|
|
)
|
|
|
|
|
|
def test_dtypes(dtype):
|
|
# smoke tests on auto dtype construction
|
|
|
|
np.dtype(dtype.type).kind == "f"
|
|
assert dtype.name is not None
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"dtype, expected",
|
|
[(Float32Dtype(), "Float32Dtype()"), (Float64Dtype(), "Float64Dtype()")],
|
|
)
|
|
def test_repr_dtype(dtype, expected):
|
|
assert repr(dtype) == expected
|
|
|
|
|
|
def test_repr_array():
|
|
result = repr(pd.array([1.0, None, 3.0]))
|
|
expected = "<FloatingArray>\n[1.0, <NA>, 3.0]\nLength: 3, dtype: Float64"
|
|
assert result == expected
|
|
|
|
|
|
def test_repr_array_long():
|
|
data = pd.array([1.0, 2.0, None] * 1000)
|
|
expected = """<FloatingArray>
|
|
[ 1.0, 2.0, <NA>, 1.0, 2.0, <NA>, 1.0, 2.0, <NA>, 1.0,
|
|
...
|
|
<NA>, 1.0, 2.0, <NA>, 1.0, 2.0, <NA>, 1.0, 2.0, <NA>]
|
|
Length: 3000, dtype: Float64"""
|
|
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 0.1"
|
|
assert result == expected
|