370 lines
11 KiB
Python
370 lines
11 KiB
Python
|
# Tests specifically aimed at detecting bad arguments.
|
||
|
|
# This file is organized by reason for exception.
|
||
|
|
# 1. always invalid argument values
|
||
|
|
# 2. missing column(s)
|
||
|
|
# 3. incompatible ops/dtype/args/kwargs
|
||
|
|
# 4. invalid result shape/type
|
||
|
|
# If your test does not fit into one of these categories, add to this list.
|
||
|
|
|
||
|
|
from itertools import chain
|
||
|
|
import re
|
||
|
|
|
||
|
|
import numpy as np
|
||
|
|
import pytest
|
||
|
|
|
||
|
|
from pandas.errors import SpecificationError
|
||
|
|
|
||
|
|
from pandas import (
|
||
|
|
Categorical,
|
||
|
|
DataFrame,
|
||
|
|
Series,
|
||
|
|
date_range,
|
||
|
|
notna,
|
||
|
|
)
|
||
|
|
import pandas._testing as tm
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("result_type", ["foo", 1])
|
||
|
|
def test_result_type_error(result_type, int_frame_const_col):
|
||
|
|
# allowed result_type
|
||
|
|
df = int_frame_const_col
|
||
|
|
|
||
|
|
msg = (
|
||
|
|
"invalid value for result_type, must be one of "
|
||
|
|
"{None, 'reduce', 'broadcast', 'expand'}"
|
||
|
|
)
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
df.apply(lambda x: [1, 2, 3], axis=1, result_type=result_type)
|
||
|
|
|
||
|
|
|
||
|
|
def test_apply_invalid_axis_value():
|
||
|
|
df = DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]], index=["a", "a", "c"])
|
||
|
|
msg = "No axis named 2 for object type DataFrame"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
df.apply(lambda x: x, 2)
|
||
|
|
|
||
|
|
|
||
|
|
def test_applymap_invalid_na_action(float_frame):
|
||
|
|
# GH 23803
|
||
|
|
with pytest.raises(ValueError, match="na_action must be .*Got 'abc'"):
|
||
|
|
float_frame.applymap(lambda x: len(str(x)), na_action="abc")
|
||
|
|
|
||
|
|
|
||
|
|
def test_agg_raises():
|
||
|
|
# GH 26513
|
||
|
|
df = DataFrame({"A": [0, 1], "B": [1, 2]})
|
||
|
|
msg = "Must provide"
|
||
|
|
|
||
|
|
with pytest.raises(TypeError, match=msg):
|
||
|
|
df.agg()
|
||
|
|
|
||
|
|
|
||
|
|
def test_map_with_invalid_na_action_raises():
|
||
|
|
# https://github.com/pandas-dev/pandas/issues/32815
|
||
|
|
s = Series([1, 2, 3])
|
||
|
|
msg = "na_action must either be 'ignore' or None"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
s.map(lambda x: x, na_action="____")
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("input_na_action", ["____", True])
|
||
|
|
def test_map_arg_is_dict_with_invalid_na_action_raises(input_na_action):
|
||
|
|
# https://github.com/pandas-dev/pandas/issues/46588
|
||
|
|
s = Series([1, 2, 3])
|
||
|
|
msg = f"na_action must either be 'ignore' or None, {input_na_action} was passed"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
s.map({1: 2}, na_action=input_na_action)
|
||
|
|
|
||
|
|
|
||
|
|
def test_map_categorical_na_action():
|
||
|
|
values = Categorical(list("ABBABCD"), categories=list("DCBA"), ordered=True)
|
||
|
|
s = Series(values, name="XX", index=list("abcdefg"))
|
||
|
|
with pytest.raises(NotImplementedError, match=tm.EMPTY_STRING_PATTERN):
|
||
|
|
s.map(lambda x: x, na_action="ignore")
|
||
|
|
|
||
|
|
|
||
|
|
def test_map_datetimetz_na_action():
|
||
|
|
values = date_range("2011-01-01", "2011-01-02", freq="H").tz_localize("Asia/Tokyo")
|
||
|
|
s = Series(values, name="XX")
|
||
|
|
with pytest.raises(NotImplementedError, match=tm.EMPTY_STRING_PATTERN):
|
||
|
|
s.map(lambda x: x, na_action="ignore")
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("box", [DataFrame, Series])
|
||
|
|
@pytest.mark.parametrize("method", ["apply", "agg", "transform"])
|
||
|
|
@pytest.mark.parametrize("func", [{"A": {"B": "sum"}}, {"A": {"B": ["sum"]}}])
|
||
|
|
def test_nested_renamer(box, method, func):
|
||
|
|
# GH 35964
|
||
|
|
obj = box({"A": [1]})
|
||
|
|
match = "nested renamer is not supported"
|
||
|
|
with pytest.raises(SpecificationError, match=match):
|
||
|
|
getattr(obj, method)(func)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"renamer",
|
||
|
|
[{"foo": ["min", "max"]}, {"foo": ["min", "max"], "bar": ["sum", "mean"]}],
|
||
|
|
)
|
||
|
|
def test_series_nested_renamer(renamer):
|
||
|
|
s = Series(range(6), dtype="int64", name="series")
|
||
|
|
msg = "nested renamer is not supported"
|
||
|
|
with pytest.raises(SpecificationError, match=msg):
|
||
|
|
s.agg(renamer)
|
||
|
|
|
||
|
|
|
||
|
|
def test_apply_dict_depr():
|
||
|
|
|
||
|
|
tsdf = DataFrame(
|
||
|
|
np.random.randn(10, 3),
|
||
|
|
columns=["A", "B", "C"],
|
||
|
|
index=date_range("1/1/2000", periods=10),
|
||
|
|
)
|
||
|
|
msg = "nested renamer is not supported"
|
||
|
|
with pytest.raises(SpecificationError, match=msg):
|
||
|
|
tsdf.A.agg({"foo": ["sum", "mean"]})
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("method", ["agg", "transform"])
|
||
|
|
def test_dict_nested_renaming_depr(method):
|
||
|
|
|
||
|
|
df = DataFrame({"A": range(5), "B": 5})
|
||
|
|
|
||
|
|
# nested renaming
|
||
|
|
msg = r"nested renamer is not supported"
|
||
|
|
with pytest.raises(SpecificationError, match=msg):
|
||
|
|
getattr(df, method)({"A": {"foo": "min"}, "B": {"bar": "max"}})
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("method", ["apply", "agg", "transform"])
|
||
|
|
@pytest.mark.parametrize("func", [{"B": "sum"}, {"B": ["sum"]}])
|
||
|
|
def test_missing_column(method, func):
|
||
|
|
# GH 40004
|
||
|
|
obj = DataFrame({"A": [1]})
|
||
|
|
match = re.escape("Column(s) ['B'] do not exist")
|
||
|
|
with pytest.raises(KeyError, match=match):
|
||
|
|
getattr(obj, method)(func)
|
||
|
|
|
||
|
|
|
||
|
|
def test_transform_mixed_column_name_dtypes():
|
||
|
|
# GH39025
|
||
|
|
df = DataFrame({"a": ["1"]})
|
||
|
|
msg = r"Column\(s\) \[1, 'b'\] do not exist"
|
||
|
|
with pytest.raises(KeyError, match=msg):
|
||
|
|
df.transform({"a": int, 1: str, "b": int})
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"how, args", [("pct_change", ()), ("nsmallest", (1, ["a", "b"])), ("tail", 1)]
|
||
|
|
)
|
||
|
|
def test_apply_str_axis_1_raises(how, args):
|
||
|
|
# GH 39211 - some ops don't support axis=1
|
||
|
|
df = DataFrame({"a": [1, 2], "b": [3, 4]})
|
||
|
|
msg = f"Operation {how} does not support axis=1"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
df.apply(how, axis=1, args=args)
|
||
|
|
|
||
|
|
|
||
|
|
def test_transform_axis_1_raises():
|
||
|
|
# GH 35964
|
||
|
|
msg = "No axis named 1 for object type Series"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
Series([1]).transform("sum", axis=1)
|
||
|
|
|
||
|
|
|
||
|
|
def test_apply_modify_traceback():
|
||
|
|
data = DataFrame(
|
||
|
|
{
|
||
|
|
"A": [
|
||
|
|
"foo",
|
||
|
|
"foo",
|
||
|
|
"foo",
|
||
|
|
"foo",
|
||
|
|
"bar",
|
||
|
|
"bar",
|
||
|
|
"bar",
|
||
|
|
"bar",
|
||
|
|
"foo",
|
||
|
|
"foo",
|
||
|
|
"foo",
|
||
|
|
],
|
||
|
|
"B": [
|
||
|
|
"one",
|
||
|
|
"one",
|
||
|
|
"one",
|
||
|
|
"two",
|
||
|
|
"one",
|
||
|
|
"one",
|
||
|
|
"one",
|
||
|
|
"two",
|
||
|
|
"two",
|
||
|
|
"two",
|
||
|
|
"one",
|
||
|
|
],
|
||
|
|
"C": [
|
||
|
|
"dull",
|
||
|
|
"dull",
|
||
|
|
"shiny",
|
||
|
|
"dull",
|
||
|
|
"dull",
|
||
|
|
"shiny",
|
||
|
|
"shiny",
|
||
|
|
"dull",
|
||
|
|
"shiny",
|
||
|
|
"shiny",
|
||
|
|
"shiny",
|
||
|
|
],
|
||
|
|
"D": np.random.randn(11),
|
||
|
|
"E": np.random.randn(11),
|
||
|
|
"F": np.random.randn(11),
|
||
|
|
}
|
||
|
|
)
|
||
|
|
|
||
|
|
data.loc[4, "C"] = np.nan
|
||
|
|
|
||
|
|
def transform(row):
|
||
|
|
if row["C"].startswith("shin") and row["A"] == "foo":
|
||
|
|
row["D"] = 7
|
||
|
|
return row
|
||
|
|
|
||
|
|
def transform2(row):
|
||
|
|
if notna(row["C"]) and row["C"].startswith("shin") and row["A"] == "foo":
|
||
|
|
row["D"] = 7
|
||
|
|
return row
|
||
|
|
|
||
|
|
msg = "'float' object has no attribute 'startswith'"
|
||
|
|
with pytest.raises(AttributeError, match=msg):
|
||
|
|
data.apply(transform, axis=1)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"df, func, expected",
|
||
|
|
tm.get_cython_table_params(
|
||
|
|
DataFrame([["a", "b"], ["b", "a"]]), [["cumprod", TypeError]]
|
||
|
|
),
|
||
|
|
)
|
||
|
|
def test_agg_cython_table_raises_frame(df, func, expected, axis):
|
||
|
|
# GH 21224
|
||
|
|
msg = "can't multiply sequence by non-int of type 'str'"
|
||
|
|
with pytest.raises(expected, match=msg):
|
||
|
|
df.agg(func, axis=axis)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"series, func, expected",
|
||
|
|
chain(
|
||
|
|
tm.get_cython_table_params(
|
||
|
|
Series("a b c".split()),
|
||
|
|
[
|
||
|
|
("mean", TypeError), # mean raises TypeError
|
||
|
|
("prod", TypeError),
|
||
|
|
("std", TypeError),
|
||
|
|
("var", TypeError),
|
||
|
|
("median", TypeError),
|
||
|
|
("cumprod", TypeError),
|
||
|
|
],
|
||
|
|
)
|
||
|
|
),
|
||
|
|
)
|
||
|
|
def test_agg_cython_table_raises_series(series, func, expected):
|
||
|
|
# GH21224
|
||
|
|
msg = r"[Cc]ould not convert|can't multiply sequence by non-int of type"
|
||
|
|
with pytest.raises(expected, match=msg):
|
||
|
|
# e.g. Series('a b'.split()).cumprod() will raise
|
||
|
|
series.agg(func)
|
||
|
|
|
||
|
|
|
||
|
|
def test_agg_none_to_type():
|
||
|
|
# GH 40543
|
||
|
|
df = DataFrame({"a": [None]})
|
||
|
|
msg = re.escape("int() argument must be a string")
|
||
|
|
with pytest.raises(TypeError, match=msg):
|
||
|
|
df.agg({"a": int})
|
||
|
|
|
||
|
|
|
||
|
|
def test_transform_none_to_type():
|
||
|
|
# GH#34377
|
||
|
|
df = DataFrame({"a": [None]})
|
||
|
|
msg = "Transform function failed"
|
||
|
|
with pytest.raises(TypeError, match=msg):
|
||
|
|
df.transform({"a": int})
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"func",
|
||
|
|
[
|
||
|
|
lambda x: np.array([1, 2]).reshape(-1, 2),
|
||
|
|
lambda x: [1, 2],
|
||
|
|
lambda x: Series([1, 2]),
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_apply_broadcast_error(int_frame_const_col, func):
|
||
|
|
df = int_frame_const_col
|
||
|
|
|
||
|
|
# > 1 ndim
|
||
|
|
msg = "too many dims to broadcast|cannot broadcast result"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
df.apply(func, axis=1, result_type="broadcast")
|
||
|
|
|
||
|
|
|
||
|
|
def test_transform_and_agg_err_agg(axis, float_frame):
|
||
|
|
# cannot both transform and agg
|
||
|
|
msg = "cannot combine transform and aggregation operations"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
with np.errstate(all="ignore"):
|
||
|
|
float_frame.agg(["max", "sqrt"], axis=axis)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"func, msg",
|
||
|
|
[
|
||
|
|
(["sqrt", "max"], "cannot combine transform and aggregation"),
|
||
|
|
(
|
||
|
|
{"foo": np.sqrt, "bar": "sum"},
|
||
|
|
"cannot perform both aggregation and transformation",
|
||
|
|
),
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_transform_and_agg_err_series(string_series, func, msg):
|
||
|
|
# we are trying to transform with an aggregator
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
with np.errstate(all="ignore"):
|
||
|
|
string_series.agg(func)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("func", [["max", "min"], ["max", "sqrt"]])
|
||
|
|
def test_transform_wont_agg_frame(axis, float_frame, func):
|
||
|
|
# GH 35964
|
||
|
|
# cannot both transform and agg
|
||
|
|
msg = "Function did not transform"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
float_frame.transform(func, axis=axis)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("func", [["min", "max"], ["sqrt", "max"]])
|
||
|
|
def test_transform_wont_agg_series(string_series, func):
|
||
|
|
# GH 35964
|
||
|
|
# we are trying to transform with an aggregator
|
||
|
|
msg = "Function did not transform"
|
||
|
|
|
||
|
|
warn = RuntimeWarning if func[0] == "sqrt" else None
|
||
|
|
warn_msg = "invalid value encountered in sqrt"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
with tm.assert_produces_warning(warn, match=warn_msg):
|
||
|
|
string_series.transform(func)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"op_wrapper", [lambda x: x, lambda x: [x], lambda x: {"A": x}, lambda x: {"A": [x]}]
|
||
|
|
)
|
||
|
|
@pytest.mark.filterwarnings("ignore:.*Select only valid:FutureWarning")
|
||
|
|
def test_transform_reducer_raises(all_reductions, frame_or_series, op_wrapper):
|
||
|
|
# GH 35964
|
||
|
|
op = op_wrapper(all_reductions)
|
||
|
|
|
||
|
|
obj = DataFrame({"A": [1, 2, 3]})
|
||
|
|
obj = tm.get_obj(obj, frame_or_series)
|
||
|
|
|
||
|
|
msg = "Function did not transform"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
obj.transform(op)
|