Alle Dateien aus dem Pythonkurs
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import numpy as np
import pytest
from pandas.core.dtypes.common import is_integer_dtype
import pandas as pd
import pandas._testing as tm
arrays = [pd.array([1, 2, 3, None], dtype=dtype) for dtype in tm.ALL_INT_EA_DTYPES]
arrays += [
pd.array([0.141, -0.268, 5.895, None], dtype=dtype) for dtype in tm.FLOAT_EA_DTYPES
]
@pytest.fixture(params=arrays, ids=[a.dtype.name for a in arrays])
def data(request):
"""
Fixture returning parametrized 'data' array with different integer and
floating point types
"""
return request.param
@pytest.fixture()
def numpy_dtype(data):
"""
Fixture returning numpy dtype from 'data' input array.
"""
# For integer dtype, the numpy conversion must be done to float
if is_integer_dtype(data):
numpy_dtype = float
else:
numpy_dtype = data.dtype.type
return numpy_dtype
def test_round(data, numpy_dtype):
# No arguments
result = data.round()
expected = pd.array(
np.round(data.to_numpy(dtype=numpy_dtype, na_value=None)), dtype=data.dtype
)
tm.assert_extension_array_equal(result, expected)
# Decimals argument
result = data.round(decimals=2)
expected = pd.array(
np.round(data.to_numpy(dtype=numpy_dtype, na_value=None), decimals=2),
dtype=data.dtype,
)
tm.assert_extension_array_equal(result, expected)
def test_tolist(data):
result = data.tolist()
expected = list(data)
tm.assert_equal(result, expected)