ai-content-maker/.venv/Lib/site-packages/pandas/tests/generic/test_generic.py

488 lines
16 KiB
Python

from copy import (
copy,
deepcopy,
)
import numpy as np
import pytest
from pandas.core.dtypes.common import is_scalar
from pandas import (
DataFrame,
Series,
)
import pandas._testing as tm
# ----------------------------------------------------------------------
# Generic types test cases
def construct(box, shape, value=None, dtype=None, **kwargs):
"""
construct an object for the given shape
if value is specified use that if its a scalar
if value is an array, repeat it as needed
"""
if isinstance(shape, int):
shape = tuple([shape] * box._AXIS_LEN)
if value is not None:
if is_scalar(value):
if value == "empty":
arr = None
dtype = np.float64
# remove the info axis
kwargs.pop(box._info_axis_name, None)
else:
arr = np.empty(shape, dtype=dtype)
arr.fill(value)
else:
fshape = np.prod(shape)
arr = value.ravel()
new_shape = fshape / arr.shape[0]
if fshape % arr.shape[0] != 0:
raise Exception("invalid value passed in construct")
arr = np.repeat(arr, new_shape).reshape(shape)
else:
arr = np.random.randn(*shape)
return box(arr, dtype=dtype, **kwargs)
class Generic:
@pytest.mark.parametrize(
"func",
[
str.lower,
{x: x.lower() for x in list("ABCD")},
Series({x: x.lower() for x in list("ABCD")}),
],
)
def test_rename(self, frame_or_series, func):
# single axis
idx = list("ABCD")
for axis in frame_or_series._AXIS_ORDERS:
kwargs = {axis: idx}
obj = construct(4, **kwargs)
# rename a single axis
result = obj.rename(**{axis: func})
expected = obj.copy()
setattr(expected, axis, list("abcd"))
tm.assert_equal(result, expected)
def test_get_numeric_data(self, frame_or_series):
n = 4
kwargs = {
frame_or_series._get_axis_name(i): list(range(n))
for i in range(frame_or_series._AXIS_LEN)
}
# get the numeric data
o = construct(n, **kwargs)
result = o._get_numeric_data()
tm.assert_equal(result, o)
# non-inclusion
result = o._get_bool_data()
expected = construct(n, value="empty", **kwargs)
if isinstance(o, DataFrame):
# preserve columns dtype
expected.columns = o.columns[:0]
tm.assert_equal(result, expected)
# get the bool data
arr = np.array([True, True, False, True])
o = construct(n, value=arr, **kwargs)
result = o._get_numeric_data()
tm.assert_equal(result, o)
def test_nonzero(self, frame_or_series):
# GH 4633
# look at the boolean/nonzero behavior for objects
obj = construct(frame_or_series, shape=4)
msg = f"The truth value of a {frame_or_series.__name__} is ambiguous"
with pytest.raises(ValueError, match=msg):
bool(obj == 0)
with pytest.raises(ValueError, match=msg):
bool(obj == 1)
with pytest.raises(ValueError, match=msg):
bool(obj)
obj = construct(frame_or_series, shape=4, value=1)
with pytest.raises(ValueError, match=msg):
bool(obj == 0)
with pytest.raises(ValueError, match=msg):
bool(obj == 1)
with pytest.raises(ValueError, match=msg):
bool(obj)
obj = construct(frame_or_series, shape=4, value=np.nan)
with pytest.raises(ValueError, match=msg):
bool(obj == 0)
with pytest.raises(ValueError, match=msg):
bool(obj == 1)
with pytest.raises(ValueError, match=msg):
bool(obj)
# empty
obj = construct(frame_or_series, shape=0)
with pytest.raises(ValueError, match=msg):
bool(obj)
# invalid behaviors
obj1 = construct(frame_or_series, shape=4, value=1)
obj2 = construct(frame_or_series, shape=4, value=1)
with pytest.raises(ValueError, match=msg):
if obj1:
pass
with pytest.raises(ValueError, match=msg):
obj1 and obj2
with pytest.raises(ValueError, match=msg):
obj1 or obj2
with pytest.raises(ValueError, match=msg):
not obj1
def test_frame_or_series_compound_dtypes(self, frame_or_series):
# see gh-5191
# Compound dtypes should raise NotImplementedError.
def f(dtype):
return construct(frame_or_series, shape=3, value=1, dtype=dtype)
msg = (
"compound dtypes are not implemented "
f"in the {frame_or_series.__name__} frame_or_series"
)
with pytest.raises(NotImplementedError, match=msg):
f([("A", "datetime64[h]"), ("B", "str"), ("C", "int32")])
# these work (though results may be unexpected)
f("int64")
f("float64")
f("M8[ns]")
def test_metadata_propagation(self, frame_or_series):
# check that the metadata matches up on the resulting ops
o = construct(frame_or_series, shape=3)
o.name = "foo"
o2 = construct(frame_or_series, shape=3)
o2.name = "bar"
# ----------
# preserving
# ----------
# simple ops with scalars
for op in ["__add__", "__sub__", "__truediv__", "__mul__"]:
result = getattr(o, op)(1)
tm.assert_metadata_equivalent(o, result)
# ops with like
for op in ["__add__", "__sub__", "__truediv__", "__mul__"]:
result = getattr(o, op)(o)
tm.assert_metadata_equivalent(o, result)
# simple boolean
for op in ["__eq__", "__le__", "__ge__"]:
v1 = getattr(o, op)(o)
tm.assert_metadata_equivalent(o, v1)
tm.assert_metadata_equivalent(o, v1 & v1)
tm.assert_metadata_equivalent(o, v1 | v1)
# combine_first
result = o.combine_first(o2)
tm.assert_metadata_equivalent(o, result)
# ---------------------------
# non-preserving (by default)
# ---------------------------
# add non-like
result = o + o2
tm.assert_metadata_equivalent(result)
# simple boolean
for op in ["__eq__", "__le__", "__ge__"]:
# this is a name matching op
v1 = getattr(o, op)(o)
v2 = getattr(o, op)(o2)
tm.assert_metadata_equivalent(v2)
tm.assert_metadata_equivalent(v1 & v2)
tm.assert_metadata_equivalent(v1 | v2)
def test_size_compat(self, frame_or_series):
# GH8846
# size property should be defined
o = construct(frame_or_series, shape=10)
assert o.size == np.prod(o.shape)
assert o.size == 10 ** len(o.axes)
def test_split_compat(self, frame_or_series):
# xref GH8846
o = construct(frame_or_series, shape=10)
assert len(np.array_split(o, 5)) == 5
assert len(np.array_split(o, 2)) == 2
# See gh-12301
def test_stat_unexpected_keyword(self, frame_or_series):
obj = construct(frame_or_series, 5)
starwars = "Star Wars"
errmsg = "unexpected keyword"
with pytest.raises(TypeError, match=errmsg):
obj.max(epic=starwars) # stat_function
with pytest.raises(TypeError, match=errmsg):
obj.var(epic=starwars) # stat_function_ddof
with pytest.raises(TypeError, match=errmsg):
obj.sum(epic=starwars) # cum_function
with pytest.raises(TypeError, match=errmsg):
obj.any(epic=starwars) # logical_function
@pytest.mark.parametrize("func", ["sum", "cumsum", "any", "var"])
def test_api_compat(self, func, frame_or_series):
# GH 12021
# compat for __name__, __qualname__
obj = (frame_or_series, 5)
f = getattr(obj, func)
assert f.__name__ == func
assert f.__qualname__.endswith(func)
def test_stat_non_defaults_args(self, frame_or_series):
obj = construct(frame_or_series, 5)
out = np.array([0])
errmsg = "the 'out' parameter is not supported"
with pytest.raises(ValueError, match=errmsg):
obj.max(out=out) # stat_function
with pytest.raises(ValueError, match=errmsg):
obj.var(out=out) # stat_function_ddof
with pytest.raises(ValueError, match=errmsg):
obj.sum(out=out) # cum_function
with pytest.raises(ValueError, match=errmsg):
obj.any(out=out) # logical_function
def test_truncate_out_of_bounds(self, frame_or_series):
# GH11382
# small
shape = [2000] + ([1] * (frame_or_series._AXIS_LEN - 1))
small = construct(frame_or_series, shape, dtype="int8", value=1)
tm.assert_equal(small.truncate(), small)
tm.assert_equal(small.truncate(before=0, after=3e3), small)
tm.assert_equal(small.truncate(before=-1, after=2e3), small)
# big
shape = [2_000_000] + ([1] * (frame_or_series._AXIS_LEN - 1))
big = construct(frame_or_series, shape, dtype="int8", value=1)
tm.assert_equal(big.truncate(), big)
tm.assert_equal(big.truncate(before=0, after=3e6), big)
tm.assert_equal(big.truncate(before=-1, after=2e6), big)
@pytest.mark.parametrize(
"func",
[copy, deepcopy, lambda x: x.copy(deep=False), lambda x: x.copy(deep=True)],
)
@pytest.mark.parametrize("shape", [0, 1, 2])
def test_copy_and_deepcopy(self, frame_or_series, shape, func):
# GH 15444
obj = construct(frame_or_series, shape)
obj_copy = func(obj)
assert obj_copy is not obj
tm.assert_equal(obj_copy, obj)
class TestNDFrame:
# tests that don't fit elsewhere
@pytest.mark.parametrize(
"ser", [tm.makeFloatSeries(), tm.makeStringSeries(), tm.makeObjectSeries()]
)
def test_squeeze_series_noop(self, ser):
# noop
tm.assert_series_equal(ser.squeeze(), ser)
def test_squeeze_frame_noop(self):
# noop
df = tm.makeTimeDataFrame()
tm.assert_frame_equal(df.squeeze(), df)
def test_squeeze_frame_reindex(self):
# squeezing
df = tm.makeTimeDataFrame().reindex(columns=["A"])
tm.assert_series_equal(df.squeeze(), df["A"])
def test_squeeze_0_len_dim(self):
# don't fail with 0 length dimensions GH11229 & GH8999
empty_series = Series([], name="five", dtype=np.float64)
empty_frame = DataFrame([empty_series])
tm.assert_series_equal(empty_series, empty_series.squeeze())
tm.assert_series_equal(empty_series, empty_frame.squeeze())
def test_squeeze_axis(self):
# axis argument
df = tm.makeTimeDataFrame(nper=1).iloc[:, :1]
assert df.shape == (1, 1)
tm.assert_series_equal(df.squeeze(axis=0), df.iloc[0])
tm.assert_series_equal(df.squeeze(axis="index"), df.iloc[0])
tm.assert_series_equal(df.squeeze(axis=1), df.iloc[:, 0])
tm.assert_series_equal(df.squeeze(axis="columns"), df.iloc[:, 0])
assert df.squeeze() == df.iloc[0, 0]
msg = "No axis named 2 for object type DataFrame"
with pytest.raises(ValueError, match=msg):
df.squeeze(axis=2)
msg = "No axis named x for object type DataFrame"
with pytest.raises(ValueError, match=msg):
df.squeeze(axis="x")
def test_squeeze_axis_len_3(self):
df = tm.makeTimeDataFrame(3)
tm.assert_frame_equal(df.squeeze(axis=0), df)
def test_numpy_squeeze(self):
s = tm.makeFloatSeries()
tm.assert_series_equal(np.squeeze(s), s)
df = tm.makeTimeDataFrame().reindex(columns=["A"])
tm.assert_series_equal(np.squeeze(df), df["A"])
@pytest.mark.parametrize(
"ser", [tm.makeFloatSeries(), tm.makeStringSeries(), tm.makeObjectSeries()]
)
def test_transpose_series(self, ser):
# calls implementation in pandas/core/base.py
tm.assert_series_equal(ser.transpose(), ser)
def test_transpose_frame(self):
df = tm.makeTimeDataFrame()
tm.assert_frame_equal(df.transpose().transpose(), df)
def test_numpy_transpose(self, frame_or_series):
obj = tm.makeTimeDataFrame()
obj = tm.get_obj(obj, frame_or_series)
if frame_or_series is Series:
# 1D -> np.transpose is no-op
tm.assert_series_equal(np.transpose(obj), obj)
# round-trip preserved
tm.assert_equal(np.transpose(np.transpose(obj)), obj)
msg = "the 'axes' parameter is not supported"
with pytest.raises(ValueError, match=msg):
np.transpose(obj, axes=1)
@pytest.mark.parametrize(
"ser", [tm.makeFloatSeries(), tm.makeStringSeries(), tm.makeObjectSeries()]
)
def test_take_series(self, ser):
indices = [1, 5, -2, 6, 3, -1]
out = ser.take(indices)
expected = Series(
data=ser.values.take(indices),
index=ser.index.take(indices),
dtype=ser.dtype,
)
tm.assert_series_equal(out, expected)
def test_take_frame(self):
indices = [1, 5, -2, 6, 3, -1]
df = tm.makeTimeDataFrame()
out = df.take(indices)
expected = DataFrame(
data=df.values.take(indices, axis=0),
index=df.index.take(indices),
columns=df.columns,
)
tm.assert_frame_equal(out, expected)
def test_take_invalid_kwargs(self, frame_or_series):
indices = [-3, 2, 0, 1]
obj = tm.makeTimeDataFrame()
obj = tm.get_obj(obj, frame_or_series)
msg = r"take\(\) got an unexpected keyword argument 'foo'"
with pytest.raises(TypeError, match=msg):
obj.take(indices, foo=2)
msg = "the 'out' parameter is not supported"
with pytest.raises(ValueError, match=msg):
obj.take(indices, out=indices)
msg = "the 'mode' parameter is not supported"
with pytest.raises(ValueError, match=msg):
obj.take(indices, mode="clip")
@pytest.mark.parametrize("is_copy", [True, False])
def test_depr_take_kwarg_is_copy(self, is_copy, frame_or_series):
# GH 27357
obj = DataFrame({"A": [1, 2, 3]})
obj = tm.get_obj(obj, frame_or_series)
msg = (
"is_copy is deprecated and will be removed in a future version. "
"'take' always returns a copy, so there is no need to specify this."
)
with tm.assert_produces_warning(FutureWarning) as w:
obj.take([0, 1], is_copy=is_copy)
assert w[0].message.args[0] == msg
def test_axis_classmethods(self, frame_or_series):
box = frame_or_series
obj = box(dtype=object)
values = box._AXIS_TO_AXIS_NUMBER.keys()
for v in values:
assert obj._get_axis_number(v) == box._get_axis_number(v)
assert obj._get_axis_name(v) == box._get_axis_name(v)
assert obj._get_block_manager_axis(v) == box._get_block_manager_axis(v)
def test_axis_names_deprecated(self, frame_or_series):
# GH33637
box = frame_or_series
obj = box(dtype=object)
msg = "_AXIS_NAMES has been deprecated"
with tm.assert_produces_warning(FutureWarning, match=msg):
obj._AXIS_NAMES
def test_axis_numbers_deprecated(self, frame_or_series):
# GH33637
box = frame_or_series
obj = box(dtype=object)
msg = "_AXIS_NUMBERS has been deprecated"
with tm.assert_produces_warning(FutureWarning, match=msg):
obj._AXIS_NUMBERS
def test_flags_identity(self, frame_or_series):
obj = Series([1, 2])
if frame_or_series is DataFrame:
obj = obj.to_frame()
assert obj.flags is obj.flags
obj2 = obj.copy()
assert obj2.flags is not obj.flags
def test_slice_shift_deprecated(self, frame_or_series):
# GH 37601
obj = DataFrame({"A": [1, 2, 3, 4]})
obj = tm.get_obj(obj, frame_or_series)
with tm.assert_produces_warning(FutureWarning):
obj.slice_shift()