Skip to content
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
51 changes: 27 additions & 24 deletions pandas/tests/series/test_quantile.py
Original file line number Diff line number Diff line change
Expand Up @@ -8,24 +8,22 @@
from pandas.core.indexes.datetimes import Timestamp
import pandas.util.testing as tm

from .common import TestData

class TestSeriesQuantile:
def test_quantile(self, datetime_series):

class TestSeriesQuantile(TestData):
def test_quantile(self):
q = datetime_series.quantile(0.1)
assert q == np.percentile(datetime_series.dropna(), 10)

q = self.ts.quantile(0.1)
assert q == np.percentile(self.ts.dropna(), 10)

q = self.ts.quantile(0.9)
assert q == np.percentile(self.ts.dropna(), 90)
q = datetime_series.quantile(0.9)
assert q == np.percentile(datetime_series.dropna(), 90)

# object dtype
q = Series(self.ts, dtype=object).quantile(0.9)
assert q == np.percentile(self.ts.dropna(), 90)
q = Series(datetime_series, dtype=object).quantile(0.9)
assert q == np.percentile(datetime_series.dropna(), 90)

# datetime64[ns] dtype
dts = self.ts.index.to_series()
dts = datetime_series.index.to_series()
q = dts.quantile(0.2)
assert q == Timestamp("2000-01-10 19:12:00")

Expand All @@ -41,20 +39,23 @@ def test_quantile(self):
msg = "percentiles should all be in the interval \\[0, 1\\]"
for invalid in [-1, 2, [0.5, -1], [0.5, 2]]:
with pytest.raises(ValueError, match=msg):
self.ts.quantile(invalid)
datetime_series.quantile(invalid)

def test_quantile_multi(self):
def test_quantile_multi(self, datetime_series):

qs = [0.1, 0.9]
result = self.ts.quantile(qs)
result = datetime_series.quantile(qs)
expected = pd.Series(
[np.percentile(self.ts.dropna(), 10), np.percentile(self.ts.dropna(), 90)],
[
np.percentile(datetime_series.dropna(), 10),
np.percentile(datetime_series.dropna(), 90),
],
index=qs,
name=self.ts.name,
name=datetime_series.name,
)
tm.assert_series_equal(result, expected)

dts = self.ts.index.to_series()
dts = datetime_series.index.to_series()
dts.name = "xxx"
result = dts.quantile((0.2, 0.2))
expected = Series(
Expand All @@ -64,18 +65,20 @@ def test_quantile_multi(self):
)
tm.assert_series_equal(result, expected)

result = self.ts.quantile([])
expected = pd.Series([], name=self.ts.name, index=Index([], dtype=float))
result = datetime_series.quantile([])
expected = pd.Series(
[], name=datetime_series.name, index=Index([], dtype=float)
)
tm.assert_series_equal(result, expected)

def test_quantile_interpolation(self):
def test_quantile_interpolation(self, datetime_series):
# see gh-10174

# interpolation = linear (default case)
q = self.ts.quantile(0.1, interpolation="linear")
assert q == np.percentile(self.ts.dropna(), 10)
q1 = self.ts.quantile(0.1)
assert q1 == np.percentile(self.ts.dropna(), 10)
q = datetime_series.quantile(0.1, interpolation="linear")
assert q == np.percentile(datetime_series.dropna(), 10)
q1 = datetime_series.quantile(0.1)
assert q1 == np.percentile(datetime_series.dropna(), 10)

# test with and without interpolation keyword
assert q == q1
Expand Down