Traktor/myenv/Lib/site-packages/pandas/tests/frame/test_npfuncs.py

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2024-05-23 01:57:24 +02:00
"""
Tests for np.foo applied to DataFrame, not necessarily ufuncs.
"""
import numpy as np
from pandas import (
Categorical,
DataFrame,
)
import pandas._testing as tm
class TestAsArray:
def test_asarray_homogeneous(self):
df = DataFrame({"A": Categorical([1, 2]), "B": Categorical([1, 2])})
result = np.asarray(df)
# may change from object in the future
expected = np.array([[1, 1], [2, 2]], dtype="object")
tm.assert_numpy_array_equal(result, expected)
def test_np_sqrt(self, float_frame):
with np.errstate(all="ignore"):
result = np.sqrt(float_frame)
assert isinstance(result, type(float_frame))
assert result.index.is_(float_frame.index)
assert result.columns.is_(float_frame.columns)
tm.assert_frame_equal(result, float_frame.apply(np.sqrt))
def test_sum_deprecated_axis_behavior(self):
# GH#52042 deprecated behavior of df.sum(axis=None), which gets
# called when we do np.sum(df)
arr = np.random.default_rng(2).standard_normal((4, 3))
df = DataFrame(arr)
msg = "The behavior of DataFrame.sum with axis=None is deprecated"
with tm.assert_produces_warning(
FutureWarning, match=msg, check_stacklevel=False
):
res = np.sum(df)
with tm.assert_produces_warning(FutureWarning, match=msg):
expected = df.sum(axis=None)
tm.assert_series_equal(res, expected)
def test_np_ravel(self):
# GH26247
arr = np.array(
[
[0.11197053, 0.44361564, -0.92589452],
[0.05883648, -0.00948922, -0.26469934],
]
)
result = np.ravel([DataFrame(batch.reshape(1, 3)) for batch in arr])
expected = np.array(
[
0.11197053,
0.44361564,
-0.92589452,
0.05883648,
-0.00948922,
-0.26469934,
]
)
tm.assert_numpy_array_equal(result, expected)
result = np.ravel(DataFrame(arr[0].reshape(1, 3), columns=["x1", "x2", "x3"]))
expected = np.array([0.11197053, 0.44361564, -0.92589452])
tm.assert_numpy_array_equal(result, expected)
result = np.ravel(
[
DataFrame(batch.reshape(1, 3), columns=["x1", "x2", "x3"])
for batch in arr
]
)
expected = np.array(
[
0.11197053,
0.44361564,
-0.92589452,
0.05883648,
-0.00948922,
-0.26469934,
]
)
tm.assert_numpy_array_equal(result, expected)