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Merged
merged 24 commits into from
Jul 12, 2021
Merged

CLN TST: Refactor Styler.bar tests through parametrisation #42472

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0de9cd1
change styler bar code
attack68 Jun 28, 2021
9addb86
width centralised
attack68 Jun 28, 2021
54a7813
align with existing tests
attack68 Jun 28, 2021
50eff0f
fix formattimg and tests
attack68 Jun 28, 2021
bcd4914
documentation and amended tests
attack68 Jun 28, 2021
e711c7d
documentation, refactor, and amended tests
attack68 Jun 29, 2021
debec3e
tests explicit
attack68 Jun 29, 2021
444b0e9
mypy fix and black
attack68 Jun 29, 2021
e677f06
add tests for new cases
attack68 Jun 29, 2021
6970a03
whats new
attack68 Jun 29, 2021
db18100
simplify
attack68 Jun 30, 2021
e3d00f4
Merge remote-tracking branch 'upstream/master' into styler_bar_fix
attack68 Jul 3, 2021
f473a42
fix docs after deprecation of args
attack68 Jul 3, 2021
8cc79ed
Merge remote-tracking branch 'upstream/master' into styler_bar_fix
attack68 Jul 5, 2021
cc409ef
Merge branch 'styler_bar_fix' into styler_bar_tests_improve
attack68 Jul 5, 2021
9f940e5
Merge remote-tracking branch 'upstream/master' into styler_bar_fix
attack68 Jul 8, 2021
bf71486
Merge branch 'styler_bar_fix' into styler_bar_tests_improve
attack68 Jul 8, 2021
b82111a
Merge remote-tracking branch 'upstream/master' into styler_bar_tests_…
attack68 Jul 9, 2021
6e763dc
refactor tests
attack68 Jul 9, 2021
51814f3
refactor tests
attack68 Jul 9, 2021
8a81f00
refactor tests
attack68 Jul 9, 2021
83cd259
refactor tests
attack68 Jul 9, 2021
97daab7
refactor tests
attack68 Jul 9, 2021
44d1661
refactor tests
attack68 Jul 9, 2021
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350 changes: 104 additions & 246 deletions pandas/tests/io/formats/style/test_align.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,258 +23,20 @@ def no_bar():
return bar_grad()


def bar_to(x):
return bar_grad(f" #d65f5f {x:.1f}%", f" transparent {x:.1f}%")
def bar_to(x, color="#d65f5f"):
return bar_grad(f" {color} {x:.1f}%", f" transparent {x:.1f}%")


def bar_from_to(x, y):
def bar_from_to(x, y, color="#d65f5f"):
return bar_grad(
f" transparent {x:.1f}%",
f" #d65f5f {x:.1f}%",
f" #d65f5f {y:.1f}%",
f" {color} {x:.1f}%",
f" {color} {y:.1f}%",
f" transparent {y:.1f}%",
)


class TestStylerBarAlign:
def test_bar_align_left(self):
df = DataFrame({"A": [0, 1, 2]})
result = df.style.bar(align="left")._compute().ctx
expected = {
(0, 0): bar_grad(),
(1, 0): bar_grad(" #d65f5f 50.0%", " transparent 50.0%"),
(2, 0): bar_grad(" #d65f5f 100.0%", " transparent 100.0%"),
}
assert result == expected

result = df.style.bar(color="red", width=50, align="left")._compute().ctx
expected = {
(0, 0): bar_grad(),
(1, 0): bar_grad(" red 25.0%", " transparent 25.0%"),
(2, 0): bar_grad(" red 50.0%", " transparent 50.0%"),
}
assert result == expected

df["C"] = ["a"] * len(df)
result = df.style.bar(color="red", width=50, align="left")._compute().ctx
assert result == expected
df["C"] = df["C"].astype("category")
result = df.style.bar(color="red", width=50, align="left")._compute().ctx
assert result == expected

def test_bar_align_left_0points(self):
df = DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
result = df.style.bar(align="left")._compute().ctx
expected = {
(0, 0): bar_grad(),
(0, 1): bar_grad(),
(0, 2): bar_grad(),
(1, 0): bar_grad(" #d65f5f 50.0%", " transparent 50.0%"),
(1, 1): bar_grad(" #d65f5f 50.0%", " transparent 50.0%"),
(1, 2): bar_grad(" #d65f5f 50.0%", " transparent 50.0%"),
(2, 0): bar_grad(" #d65f5f 100.0%", " transparent 100.0%"),
(2, 1): bar_grad(" #d65f5f 100.0%", " transparent 100.0%"),
(2, 2): bar_grad(" #d65f5f 100.0%", " transparent 100.0%"),
}
assert result == expected

result = df.style.bar(axis=1, align="left")._compute().ctx
expected = {
(0, 0): bar_grad(),
(0, 1): bar_grad(" #d65f5f 50.0%", " transparent 50.0%"),
(0, 2): bar_grad(" #d65f5f 100.0%", " transparent 100.0%"),
(1, 0): bar_grad(),
(1, 1): bar_grad(" #d65f5f 50.0%", " transparent 50.0%"),
(1, 2): bar_grad(" #d65f5f 100.0%", " transparent 100.0%"),
(2, 0): bar_grad(),
(2, 1): bar_grad(" #d65f5f 50.0%", " transparent 50.0%"),
(2, 2): bar_grad(" #d65f5f 100.0%", " transparent 100.0%"),
}
assert result == expected

def test_bar_align_mid_pos_and_neg(self):
df = DataFrame({"A": [-10, 0, 20, 90]})
result = df.style.bar(align="mid", color=["#d65f5f", "#5fba7d"])._compute().ctx
expected = {
(0, 0): bar_grad(
" #d65f5f 10.0%",
" transparent 10.0%",
),
(1, 0): bar_grad(),
(2, 0): bar_grad(
" transparent 10.0%",
" #5fba7d 10.0%",
" #5fba7d 30.0%",
" transparent 30.0%",
),
(3, 0): bar_grad(
" transparent 10.0%",
" #5fba7d 10.0%",
" #5fba7d 100.0%",
" transparent 100.0%",
),
}
assert result == expected

def test_bar_align_mid_all_pos(self):
df = DataFrame({"A": [10, 20, 50, 100]})

result = df.style.bar(align="mid", color=["#d65f5f", "#5fba7d"])._compute().ctx

expected = {
(0, 0): bar_grad(
" #5fba7d 10.0%",
" transparent 10.0%",
),
(1, 0): bar_grad(
" #5fba7d 20.0%",
" transparent 20.0%",
),
(2, 0): bar_grad(
" #5fba7d 50.0%",
" transparent 50.0%",
),
(3, 0): bar_grad(
" #5fba7d 100.0%",
" transparent 100.0%",
),
}

assert result == expected

def test_bar_align_mid_all_neg(self):
df = DataFrame({"A": [-100, -60, -30, -20]})

result = df.style.bar(align="mid", color=["#d65f5f", "#5fba7d"])._compute().ctx

expected = {
(0, 0): bar_grad(
" #d65f5f 100.0%",
" transparent 100.0%",
),
(1, 0): bar_grad(
" transparent 40.0%",
" #d65f5f 40.0%",
" #d65f5f 100.0%",
" transparent 100.0%",
),
(2, 0): bar_grad(
" transparent 70.0%",
" #d65f5f 70.0%",
" #d65f5f 100.0%",
" transparent 100.0%",
),
(3, 0): bar_grad(
" transparent 80.0%",
" #d65f5f 80.0%",
" #d65f5f 100.0%",
" transparent 100.0%",
),
}
assert result == expected

def test_bar_align_zero_pos_and_neg(self):
# See https://github.com/pandas-dev/pandas/pull/14757
df = DataFrame({"A": [-10, 0, 20, 90]})

result = (
df.style.bar(align="zero", color=["#d65f5f", "#5fba7d"], width=90)
._compute()
.ctx
)
expected = {
(0, 0): bar_grad(
" transparent 40.0%",
" #d65f5f 40.0%",
" #d65f5f 45.0%",
" transparent 45.0%",
),
(1, 0): bar_grad(),
(2, 0): bar_grad(
" transparent 45.0%",
" #5fba7d 45.0%",
" #5fba7d 55.0%",
" transparent 55.0%",
),
(3, 0): bar_grad(
" transparent 45.0%",
" #5fba7d 45.0%",
" #5fba7d 90.0%",
" transparent 90.0%",
),
}
assert result == expected

def test_bar_align_left_axis_none(self):
df = DataFrame({"A": [0, 1], "B": [2, 4]})
result = df.style.bar(axis=None, align="left")._compute().ctx
expected = {
(0, 0): bar_grad(),
(1, 0): bar_grad(
" #d65f5f 25.0%",
" transparent 25.0%",
),
(0, 1): bar_grad(
" #d65f5f 50.0%",
" transparent 50.0%",
),
(1, 1): bar_grad(
" #d65f5f 100.0%",
" transparent 100.0%",
),
}
assert result == expected

def test_bar_align_zero_axis_none(self):
df = DataFrame({"A": [0, 1], "B": [-2, 4]})
result = df.style.bar(align="zero", axis=None)._compute().ctx
expected = {
(0, 0): bar_grad(),
(1, 0): bar_grad(
" transparent 50.0%",
" #d65f5f 50.0%",
" #d65f5f 62.5%",
" transparent 62.5%",
),
(0, 1): bar_grad(
" transparent 25.0%",
" #d65f5f 25.0%",
" #d65f5f 50.0%",
" transparent 50.0%",
),
(1, 1): bar_grad(
" transparent 50.0%",
" #d65f5f 50.0%",
" #d65f5f 100.0%",
" transparent 100.0%",
),
}
assert result == expected

def test_bar_align_mid_axis_none(self):
df = DataFrame({"A": [0, 1], "B": [-2, 4]})
result = df.style.bar(align="mid", axis=None)._compute().ctx
expected = {
(0, 0): bar_grad(),
(1, 0): bar_grad(
" transparent 33.3%",
" #d65f5f 33.3%",
" #d65f5f 50.0%",
" transparent 50.0%",
),
(0, 1): bar_grad(
" #d65f5f 33.3%",
" transparent 33.3%",
),
(1, 1): bar_grad(
" transparent 33.3%",
" #d65f5f 33.3%",
" #d65f5f 100.0%",
" transparent 100.0%",
),
}
assert result == expected

def test_bar_align_mid_vmin(self):
df = DataFrame({"A": [0, 1], "B": [-2, 4]})
result = df.style.bar(align="mid", axis=None, vmin=-6)._compute().ctx
Expand Down Expand Up @@ -438,7 +200,7 @@ def test_bar_bad_align_raises(self):
(np.median, [bar_to(50), no_bar(), bar_from_to(50, 100)]),
],
)
def test_bar_align_positive_cases(align, exp):
def test_align_positive_cases(align, exp):
# test different align cases for all positive values
data = DataFrame([[1], [2], [3]])
result = data.style.bar(align=align)._compute().ctx
Expand All @@ -458,7 +220,7 @@ def test_bar_align_positive_cases(align, exp):
(np.median, [bar_from_to(50, 100), no_bar(), bar_to(50)]),
],
)
def test_bar_align_negative_cases(align, exp):
def test_align_negative_cases(align, exp):
# test different align cases for all negative values
data = DataFrame([[-1], [-2], [-3]])
result = data.style.bar(align=align)._compute().ctx
Expand All @@ -478,9 +240,105 @@ def test_bar_align_negative_cases(align, exp):
(np.median, [bar_to(50), no_bar(), bar_from_to(50, 62.5)]),
],
)
def test_bar_align_mixed_cases(align, exp):
def test_align_mixed_cases(align, exp):
# test different align cases for mixed positive and negative values
data = DataFrame([[-3], [1], [2]])
result = data.style.bar(align=align)._compute().ctx
expected = {(0, 0): exp[0], (1, 0): exp[1], (2, 0): exp[2]}
assert result == expected


@pytest.mark.parametrize(
"align, exp",
[
(
"left",
{
"index": [[no_bar(), no_bar()], [bar_to(100), bar_to(100)]],
"columns": [[no_bar(), bar_to(100)], [no_bar(), bar_to(100)]],
"none": [[no_bar(), bar_to(33.33)], [bar_to(66.66), bar_to(100)]],
},
),
(
"mid",
{
"index": [[bar_to(33.33), bar_to(50)], [bar_to(100), bar_to(100)]],
"columns": [[bar_to(50), bar_to(100)], [bar_to(75), bar_to(100)]],
"none": [[bar_to(25), bar_to(50)], [bar_to(75), bar_to(100)]],
},
),
(
"zero",
{
"index": [
[bar_from_to(50, 66.66), bar_from_to(50, 75)],
[bar_from_to(50, 100), bar_from_to(50, 100)],
],
"columns": [
[bar_from_to(50, 75), bar_from_to(50, 100)],
[bar_from_to(50, 87.5), bar_from_to(50, 100)],
],
"none": [
[bar_from_to(50, 62.5), bar_from_to(50, 75)],
[bar_from_to(50, 87.5), bar_from_to(50, 100)],
],
},
),
(
2,
{
"index": [
[bar_to(50), no_bar()],
[bar_from_to(50, 100), bar_from_to(50, 100)],
],
"columns": [
[bar_to(50), no_bar()],
[bar_from_to(50, 75), bar_from_to(50, 100)],
],
"none": [
[bar_from_to(25, 50), no_bar()],
[bar_from_to(50, 75), bar_from_to(50, 100)],
],
},
),
],
)
@pytest.mark.parametrize("axis", ["index", "columns", "none"])
def test_align_axis(align, exp, axis):
# test all axis combinations with positive values and different aligns
data = DataFrame([[1, 2], [3, 4]])
result = (
data.style.bar(align=align, axis=None if axis == "none" else axis)
._compute()
.ctx
)
expected = {
(0, 0): exp[axis][0][0],
(0, 1): exp[axis][0][1],
(1, 0): exp[axis][1][0],
(1, 1): exp[axis][1][1],
}
assert result == expected


def test_numerics():
# test data is pre-selected for numeric values
data = DataFrame([[1, "a"], [2, "b"]])
result = data.style.bar()._compute().ctx
assert (0, 1) not in result
assert (1, 1) not in result


@pytest.mark.parametrize(
"align, exp",
[
("left", [no_bar(), bar_to(100, "green")]),
("right", [bar_to(100, "red"), no_bar()]),
("mid", [bar_to(25, "red"), bar_from_to(25, 100, "green")]),
("zero", [bar_from_to(33.33, 50, "red"), bar_from_to(50, 100, "green")]),
],
)
def test_colors_mixed(align, exp):
data = DataFrame([[-1], [3]])
result = data.style.bar(align=align, color=["red", "green"])._compute().ctx
assert result == {(0, 0): exp[0], (1, 0): exp[1]}