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TST: update frame method quantile tests #59875

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merged 4 commits into from
Oct 31, 2024
Merged

TST: update frame method quantile tests #59875

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bd563e0
TST (string dtype): update frame method quantile tests
jorisvandenbossche Sep 23, 2024
96d7202
Merge remote-tracking branch 'upstream/main' into string-dtype-tests-…
jorisvandenbossche Oct 30, 2024
348e3dc
fixup
jorisvandenbossche Oct 30, 2024
5fa24d2
Merge remote-tracking branch 'upstream/main' into string-dtype-tests-…
jorisvandenbossche Oct 31, 2024
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35 changes: 18 additions & 17 deletions pandas/tests/frame/methods/test_quantile.py
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Original file line number Diff line number Diff line change
@@ -1,8 +1,6 @@
import numpy as np
import pytest

from pandas._config import using_string_dtype

import pandas as pd
from pandas import (
DataFrame,
Expand Down Expand Up @@ -326,7 +324,6 @@ def test_quantile_multi_empty(self, interp_method):
)
tm.assert_frame_equal(result, expected)

@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
def test_quantile_datetime(self, unit):
dti = pd.to_datetime(["2010", "2011"]).as_unit(unit)
df = DataFrame({"a": dti, "b": [0, 5]})
Expand Down Expand Up @@ -373,14 +370,13 @@ def test_quantile_datetime(self, unit):

# empty when numeric_only=True
result = df[["a", "c"]].quantile(0.5, numeric_only=True)
expected = Series([], index=[], dtype=np.float64, name=0.5)
expected = Series([], index=Index([], dtype="str"), dtype=np.float64, name=0.5)
tm.assert_series_equal(result, expected)

result = df[["a", "c"]].quantile([0.5], numeric_only=True)
expected = DataFrame(index=[0.5], columns=[])
expected = DataFrame(index=[0.5], columns=Index([], dtype="str"))
tm.assert_frame_equal(result, expected)

@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
@pytest.mark.parametrize(
"dtype",
[
Expand All @@ -398,7 +394,7 @@ def test_quantile_dt64_empty(self, dtype, interp_method):
res = df.quantile(
0.5, axis=1, numeric_only=False, interpolation=interpolation, method=method
)
expected = Series([], index=[], name=0.5, dtype=dtype)
expected = Series([], index=Index([], dtype="str"), name=0.5, dtype=dtype)
tm.assert_series_equal(res, expected)

# no columns in result, so no dtype preservation
Expand All @@ -409,7 +405,7 @@ def test_quantile_dt64_empty(self, dtype, interp_method):
interpolation=interpolation,
method=method,
)
expected = DataFrame(index=[0.5], columns=[])
expected = DataFrame(index=[0.5], columns=Index([], dtype="str"))
tm.assert_frame_equal(res, expected)

@pytest.mark.parametrize("invalid", [-1, 2, [0.5, -1], [0.5, 2]])
Expand Down Expand Up @@ -645,7 +641,6 @@ def test_quantile_nat(self, interp_method, unit):
)
tm.assert_frame_equal(res, exp)

@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
def test_quantile_empty_no_rows_floats(self, interp_method):
interpolation, method = interp_method

Expand All @@ -660,11 +655,11 @@ def test_quantile_empty_no_rows_floats(self, interp_method):
tm.assert_frame_equal(res, exp)

res = df.quantile(0.5, axis=1, interpolation=interpolation, method=method)
exp = Series([], index=[], dtype="float64", name=0.5)
exp = Series([], index=Index([], dtype="str"), dtype="float64", name=0.5)
tm.assert_series_equal(res, exp)

res = df.quantile([0.5], axis=1, interpolation=interpolation, method=method)
exp = DataFrame(columns=[], index=[0.5])
exp = DataFrame(columns=Index([], dtype="str"), index=[0.5])
tm.assert_frame_equal(res, exp)

def test_quantile_empty_no_rows_ints(self, interp_method):
Expand Down Expand Up @@ -874,7 +869,6 @@ def test_quantile_ea_scalar(self, request, obj, index):
else:
tm.assert_series_equal(result, expected)

@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
@pytest.mark.parametrize(
"dtype, expected_data, expected_index, axis",
[
Expand All @@ -889,11 +883,13 @@ def test_empty_numeric(self, dtype, expected_data, expected_index, axis):
df = DataFrame(columns=["a", "b"], dtype=dtype)
result = df.quantile(0.5, axis=axis)
expected = Series(
expected_data, name=0.5, index=Index(expected_index), dtype="float64"
expected_data,
name=0.5,
index=Index(expected_index, dtype="str"),
dtype="float64",
)
tm.assert_series_equal(result, expected)

@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
@pytest.mark.parametrize(
"dtype, expected_data, expected_index, axis, expected_dtype",
[
Expand All @@ -908,11 +904,13 @@ def test_empty_datelike(
df = DataFrame(columns=["a", "b"], dtype=dtype)
result = df.quantile(0.5, axis=axis, numeric_only=False)
expected = Series(
expected_data, name=0.5, index=Index(expected_index), dtype=expected_dtype
expected_data,
name=0.5,
index=Index(expected_index, dtype="str"),
dtype=expected_dtype,
)
tm.assert_series_equal(result, expected)

@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
@pytest.mark.parametrize(
"expected_data, expected_index, axis",
[
Expand All @@ -931,7 +929,10 @@ def test_datelike_numeric_only(self, expected_data, expected_index, axis):
)
result = df[["a", "c"]].quantile(0.5, axis=axis, numeric_only=True)
expected = Series(
expected_data, name=0.5, index=Index(expected_index), dtype=np.float64
expected_data,
name=0.5,
index=Index(expected_index, dtype="str" if axis == 0 else "int64"),
dtype=np.float64,
)
tm.assert_series_equal(result, expected)

Expand Down
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