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merged 4 commits into from
Jun 4, 2024
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CLN: Plotting tests 2 #58910

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3f8ae1b
Refactor test_converter
mroeschke Jun 2, 2024
f0e179c
clean test_boxplot method
mroeschke Jun 2, 2024
c722f1b
cleann test_hist_method
mroeschke Jun 2, 2024
cf7f248
Merge remote-tracking branch 'upstream/main' into cln/tests/plotting2
mroeschke Jun 3, 2024
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29 changes: 11 additions & 18 deletions pandas/tests/plotting/test_boxplot_method.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -38,9 +38,7 @@ def _check_ax_limits(col, ax):
class TestDataFramePlots:
def test_stacked_boxplot_set_axis(self):
# GH2980
import matplotlib.pyplot as plt

n = 80
n = 30
df = DataFrame(
{
"Clinical": np.random.default_rng(2).choice([0, 1, 2, 3], n),
Expand All @@ -51,10 +49,10 @@ def test_stacked_boxplot_set_axis(self):
)
ax = df.plot(kind="bar", stacked=True)
assert [int(x.get_text()) for x in ax.get_xticklabels()] == df.index.to_list()
ax.set_xticks(np.arange(0, 80, 10))
ax.set_xticks(np.arange(0, n, 10))
plt.draw() # Update changes
assert [int(x.get_text()) for x in ax.get_xticklabels()] == list(
np.arange(0, 80, 10)
np.arange(0, n, 10)
)

@pytest.mark.slow
Expand Down Expand Up @@ -227,12 +225,12 @@ def test_boxplot_numeric_data(self):
# GH 22799
df = DataFrame(
{
"a": date_range("2012-01-01", periods=100),
"b": np.random.default_rng(2).standard_normal(100),
"c": np.random.default_rng(2).standard_normal(100) + 2,
"d": date_range("2012-01-01", periods=100).astype(str),
"e": date_range("2012-01-01", periods=100, tz="UTC"),
"f": timedelta_range("1 days", periods=100),
"a": date_range("2012-01-01", periods=10),
"b": np.random.default_rng(2).standard_normal(10),
"c": np.random.default_rng(2).standard_normal(10) + 2,
"d": date_range("2012-01-01", periods=10).astype(str),
"e": date_range("2012-01-01", periods=10, tz="UTC"),
"f": timedelta_range("1 days", periods=10),
}
)
ax = df.plot(kind="box")
Expand Down Expand Up @@ -282,8 +280,6 @@ def test_color_kwd(self, colors_kwd, expected):
def test_colors_in_theme(self, scheme, expected):
# GH: 40769
df = DataFrame(np.random.default_rng(2).random((10, 2)))
import matplotlib.pyplot as plt

plt.style.use(scheme)
result = df.plot.box(return_type="dict")
for k, v in expected.items():
Expand Down Expand Up @@ -334,8 +330,8 @@ def test_plot_xlabel_ylabel(self, vert):
def test_plot_box(self, vert):
# GH 54941
rng = np.random.default_rng(2)
df1 = DataFrame(rng.integers(0, 100, size=(100, 4)), columns=list("ABCD"))
df2 = DataFrame(rng.integers(0, 100, size=(100, 4)), columns=list("ABCD"))
df1 = DataFrame(rng.integers(0, 100, size=(10, 4)), columns=list("ABCD"))
df2 = DataFrame(rng.integers(0, 100, size=(10, 4)), columns=list("ABCD"))

xlabel, ylabel = "x", "y"
_, axs = plt.subplots(ncols=2, figsize=(10, 7), sharey=True)
Expand All @@ -344,7 +340,6 @@ def test_plot_box(self, vert):
for ax in axs:
assert ax.get_xlabel() == xlabel
assert ax.get_ylabel() == ylabel
mpl.pyplot.close()

@pytest.mark.parametrize("vert", [True, False])
def test_boxplot_xlabel_ylabel(self, vert):
Expand Down Expand Up @@ -374,7 +369,6 @@ def test_boxplot_group_xlabel_ylabel(self, vert):
for subplot in ax:
assert subplot.get_xlabel() == xlabel
assert subplot.get_ylabel() == ylabel
mpl.pyplot.close()

@pytest.mark.parametrize("vert", [True, False])
def test_boxplot_group_no_xlabel_ylabel(self, vert):
Expand All @@ -389,7 +383,6 @@ def test_boxplot_group_no_xlabel_ylabel(self, vert):
for subplot in ax:
target_label = subplot.get_xlabel() if vert else subplot.get_ylabel()
assert target_label == pprint_thing(["group"])
mpl.pyplot.close()


class TestDataFrameGroupByPlots:
Expand Down
28 changes: 5 additions & 23 deletions pandas/tests/plotting/test_converter.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -34,15 +34,11 @@
Second,
)

try:
from pandas.plotting._matplotlib import converter
except ImportError:
# try / except, rather than skip, to avoid internal refactoring
# causing an improper skip
pass

pytest.importorskip("matplotlib.pyplot")
plt = pytest.importorskip("matplotlib.pyplot")
dates = pytest.importorskip("matplotlib.dates")
units = pytest.importorskip("matplotlib.units")

from pandas.plotting._matplotlib import converter


@pytest.mark.single_cpu
Expand Down Expand Up @@ -79,30 +75,22 @@ def test_dont_register_by_default(self):
assert subprocess.check_call(call) == 0

def test_registering_no_warning(self):
plt = pytest.importorskip("matplotlib.pyplot")
s = Series(range(12), index=date_range("2017", periods=12))
_, ax = plt.subplots()

# Set to the "warn" state, in case this isn't the first test run
register_matplotlib_converters()
ax.plot(s.index, s.values)
plt.close()

def test_pandas_plots_register(self):
plt = pytest.importorskip("matplotlib.pyplot")
s = Series(range(12), index=date_range("2017", periods=12))
# Set to the "warn" state, in case this isn't the first test run
with tm.assert_produces_warning(None) as w:
s.plot()

try:
assert len(w) == 0
finally:
plt.close()
assert len(w) == 0

def test_matplotlib_formatters(self):
units = pytest.importorskip("matplotlib.units")

# Can't make any assertion about the start state.
# We we check that toggling converters off removes it, and toggling it
# on restores it.
Expand All @@ -113,8 +101,6 @@ def test_matplotlib_formatters(self):
assert Timestamp in units.registry

def test_option_no_warning(self):
pytest.importorskip("matplotlib.pyplot")
plt = pytest.importorskip("matplotlib.pyplot")
s = Series(range(12), index=date_range("2017", periods=12))
_, ax = plt.subplots()

Expand All @@ -126,12 +112,8 @@ def test_option_no_warning(self):
register_matplotlib_converters()
with cf.option_context("plotting.matplotlib.register_converters", False):
ax.plot(s.index, s.values)
plt.close()

def test_registry_resets(self):
units = pytest.importorskip("matplotlib.units")
dates = pytest.importorskip("matplotlib.dates")

# make a copy, to reset to
original = dict(units.registry)

Expand Down
71 changes: 28 additions & 43 deletions pandas/tests/plotting/test_hist_method.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,9 @@
)

mpl = pytest.importorskip("matplotlib")
plt = pytest.importorskip("matplotlib.pyplot")

from pandas.plotting._matplotlib.hist import _grouped_hist


@pytest.fixture
Expand Down Expand Up @@ -119,18 +122,13 @@ def test_hist_layout_with_by_shape(self, hist_df):
_check_axes_shape(axes, axes_num=4, layout=(4, 2), figsize=(12, 7))

def test_hist_no_overlap(self):
from matplotlib.pyplot import (
gcf,
subplot,
)

x = Series(np.random.default_rng(2).standard_normal(2))
y = Series(np.random.default_rng(2).standard_normal(2))
subplot(121)
plt.subplot(121)
x.hist()
subplot(122)
plt.subplot(122)
y.hist()
fig = gcf()
fig = plt.gcf()
axes = fig.axes
assert len(axes) == 2

Expand All @@ -140,10 +138,8 @@ def test_hist_by_no_extra_plots(self, hist_df):
assert len(mpl.pyplot.get_fignums()) == 1

def test_plot_fails_when_ax_differs_from_figure(self, ts):
from pylab import figure

fig1 = figure()
fig2 = figure()
fig1 = plt.figure(1)
fig2 = plt.figure(2)
ax1 = fig1.add_subplot(111)
msg = "passed axis not bound to passed figure"
with pytest.raises(AssertionError, match=msg):
Expand All @@ -169,8 +165,8 @@ def test_histtype_argument(self, histtype, expected):
)
def test_hist_with_legend(self, by, expected_axes_num, expected_layout):
# GH 6279 - Series histogram can have a legend
index = 15 * ["1"] + 15 * ["2"]
s = Series(np.random.default_rng(2).standard_normal(30), index=index, name="a")
index = 5 * ["1"] + 5 * ["2"]
s = Series(np.random.default_rng(2).standard_normal(10), index=index, name="a")
s.index.name = "b"

# Use default_axes=True when plotting method generate subplots itself
Expand All @@ -181,8 +177,8 @@ def test_hist_with_legend(self, by, expected_axes_num, expected_layout):
@pytest.mark.parametrize("by", [None, "b"])
def test_hist_with_legend_raises(self, by):
# GH 6279 - Series histogram with legend and label raises
index = 15 * ["1"] + 15 * ["2"]
s = Series(np.random.default_rng(2).standard_normal(30), index=index, name="a")
index = 5 * ["1"] + 5 * ["2"]
s = Series(np.random.default_rng(2).standard_normal(10), index=index, name="a")
s.index.name = "b"

with pytest.raises(ValueError, match="Cannot use both legend and label"):
Expand Down Expand Up @@ -331,12 +327,10 @@ def test_hist_df_legacy_layout_labelsize_rot(self, frame_or_series):

@pytest.mark.slow
def test_hist_df_legacy_rectangles(self):
from matplotlib.patches import Rectangle

ser = Series(range(10))
ax = ser.hist(cumulative=True, bins=4, density=True)
# height of last bin (index 5) must be 1.0
rects = [x for x in ax.get_children() if isinstance(x, Rectangle)]
rects = [x for x in ax.get_children() if isinstance(x, mpl.patches.Rectangle)]
tm.assert_almost_equal(rects[-1].get_height(), 1.0)

@pytest.mark.slow
Expand Down Expand Up @@ -431,12 +425,12 @@ def test_hist_layout_error(self):

# GH 9351
def test_tight_layout(self):
df = DataFrame(np.random.default_rng(2).standard_normal((100, 2)))
df = DataFrame(np.random.default_rng(2).standard_normal((10, 2)))
df[2] = to_datetime(
np.random.default_rng(2).integers(
812419200000000000,
819331200000000000,
size=100,
size=10,
dtype=np.int64,
)
)
Expand Down Expand Up @@ -504,7 +498,7 @@ def test_hist_column_order_unchanged(self, column, expected):
def test_histtype_argument(self, histtype, expected):
# GH23992 Verify functioning of histtype argument
df = DataFrame(
np.random.default_rng(2).integers(1, 10, size=(100, 2)), columns=["a", "b"]
np.random.default_rng(2).integers(1, 10, size=(10, 2)), columns=["a", "b"]
)
ax = df.hist(histtype=histtype)
_check_patches_all_filled(ax, filled=expected)
Expand All @@ -519,9 +513,9 @@ def test_hist_with_legend(self, by, column):
if by is not None:
expected_labels = [expected_labels] * 2

index = Index(15 * ["1"] + 15 * ["2"], name="c")
index = Index(5 * ["1"] + 5 * ["2"], name="c")
df = DataFrame(
np.random.default_rng(2).standard_normal((30, 2)),
np.random.default_rng(2).standard_normal((10, 2)),
index=index,
columns=["a", "b"],
)
Expand All @@ -545,9 +539,9 @@ def test_hist_with_legend(self, by, column):
@pytest.mark.parametrize("column", [None, "b"])
def test_hist_with_legend_raises(self, by, column):
# GH 6279 - DataFrame histogram with legend and label raises
index = Index(15 * ["1"] + 15 * ["2"], name="c")
index = Index(5 * ["1"] + 5 * ["2"], name="c")
df = DataFrame(
np.random.default_rng(2).standard_normal((30, 2)),
np.random.default_rng(2).standard_normal((10, 2)),
index=index,
columns=["a", "b"],
)
Expand Down Expand Up @@ -586,7 +580,7 @@ def test_hist_df_with_nonnumerics_no_bins(self):
def test_hist_secondary_legend(self):
# GH 9610
df = DataFrame(
np.random.default_rng(2).standard_normal((30, 4)), columns=list("abcd")
np.random.default_rng(2).standard_normal((10, 4)), columns=list("abcd")
)

# primary -> secondary
Expand All @@ -602,7 +596,7 @@ def test_hist_secondary_legend(self):
def test_hist_secondary_secondary(self):
# GH 9610
df = DataFrame(
np.random.default_rng(2).standard_normal((30, 4)), columns=list("abcd")
np.random.default_rng(2).standard_normal((10, 4)), columns=list("abcd")
)
# secondary -> secondary
_, ax = mpl.pyplot.subplots()
Expand All @@ -617,7 +611,7 @@ def test_hist_secondary_secondary(self):
def test_hist_secondary_primary(self):
# GH 9610
df = DataFrame(
np.random.default_rng(2).standard_normal((30, 4)), columns=list("abcd")
np.random.default_rng(2).standard_normal((10, 4)), columns=list("abcd")
)
# secondary -> primary
_, ax = mpl.pyplot.subplots()
Expand All @@ -632,7 +626,6 @@ def test_hist_secondary_primary(self):

def test_hist_with_nans_and_weights(self):
# GH 48884
mpl_patches = pytest.importorskip("matplotlib.patches")
df = DataFrame(
[[np.nan, 0.2, 0.3], [0.4, np.nan, np.nan], [0.7, 0.8, 0.9]],
columns=list("abc"),
Expand All @@ -643,12 +636,12 @@ def test_hist_with_nans_and_weights(self):

_, ax0 = mpl.pyplot.subplots()
df.plot.hist(ax=ax0, weights=weights)
rects = [x for x in ax0.get_children() if isinstance(x, mpl_patches.Rectangle)]
rects = [x for x in ax0.get_children() if isinstance(x, mpl.patches.Rectangle)]
heights = [rect.get_height() for rect in rects]
_, ax1 = mpl.pyplot.subplots()
no_nan_df.plot.hist(ax=ax1, weights=no_nan_weights)
no_nan_rects = [
x for x in ax1.get_children() if isinstance(x, mpl_patches.Rectangle)
x for x in ax1.get_children() if isinstance(x, mpl.patches.Rectangle)
]
no_nan_heights = [rect.get_height() for rect in no_nan_rects]
assert all(h0 == h1 for h0, h1 in zip(heights, no_nan_heights))
Expand All @@ -663,8 +656,6 @@ def test_hist_with_nans_and_weights(self):

class TestDataFrameGroupByPlots:
def test_grouped_hist_legacy(self):
from pandas.plotting._matplotlib.hist import _grouped_hist

rs = np.random.default_rng(10)
df = DataFrame(rs.standard_normal((10, 1)), columns=["A"])
df["B"] = to_datetime(
Expand Down Expand Up @@ -716,10 +707,6 @@ def test_grouped_hist_legacy_single_key(self):
_check_ticks_props(axes, xrot=30)

def test_grouped_hist_legacy_grouped_hist_kwargs(self):
from matplotlib.patches import Rectangle

from pandas.plotting._matplotlib.hist import _grouped_hist

rs = np.random.default_rng(2)
df = DataFrame(rs.standard_normal((10, 1)), columns=["A"])
df["B"] = to_datetime(
Expand Down Expand Up @@ -748,14 +735,14 @@ def test_grouped_hist_legacy_grouped_hist_kwargs(self):
)
# height of last bin (index 5) must be 1.0
for ax in axes.ravel():
rects = [x for x in ax.get_children() if isinstance(x, Rectangle)]
rects = [
x for x in ax.get_children() if isinstance(x, mpl.patches.Rectangle)
]
height = rects[-1].get_height()
tm.assert_almost_equal(height, 1.0)
_check_ticks_props(axes, xlabelsize=xf, xrot=xrot, ylabelsize=yf, yrot=yrot)

def test_grouped_hist_legacy_grouped_hist(self):
from pandas.plotting._matplotlib.hist import _grouped_hist

rs = np.random.default_rng(2)
df = DataFrame(rs.standard_normal((10, 1)), columns=["A"])
df["B"] = to_datetime(
Expand All @@ -773,8 +760,6 @@ def test_grouped_hist_legacy_grouped_hist(self):
_check_ax_scales(axes, yaxis="log")

def test_grouped_hist_legacy_external_err(self):
from pandas.plotting._matplotlib.hist import _grouped_hist

rs = np.random.default_rng(2)
df = DataFrame(rs.standard_normal((10, 1)), columns=["A"])
df["B"] = to_datetime(
Expand Down