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FIX: fix cleanup warnings for errorbar timeseries #36982

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181 changes: 101 additions & 80 deletions pandas/tests/plotting/test_frame.py
Original file line number Diff line number Diff line change
Expand Up @@ -2658,67 +2658,84 @@ def test_pie_df_nan(self):

@pytest.mark.slow
def test_errorbar_plot(self):
with warnings.catch_warnings():
d = {"x": np.arange(12), "y": np.arange(12, 0, -1)}
df = DataFrame(d)
d_err = {"x": np.ones(12) * 0.2, "y": np.ones(12) * 0.4}
df_err = DataFrame(d_err)
d = {"x": np.arange(12), "y": np.arange(12, 0, -1)}
df = DataFrame(d)
d_err = {"x": np.ones(12) * 0.2, "y": np.ones(12) * 0.4}
df_err = DataFrame(d_err)

# check line plots
ax = _check_plot_works(df.plot, yerr=df_err, logy=True)
self._check_has_errorbars(ax, xerr=0, yerr=2)
ax = _check_plot_works(df.plot, yerr=df_err, logx=True, logy=True)
self._check_has_errorbars(ax, xerr=0, yerr=2)
ax = _check_plot_works(df.plot, yerr=df_err, loglog=True)
self._check_has_errorbars(ax, xerr=0, yerr=2)
# check line plots
ax = _check_plot_works(df.plot, yerr=df_err, logy=True)
self._check_has_errorbars(ax, xerr=0, yerr=2)

kinds = ["line", "bar", "barh"]
for kind in kinds:
ax = _check_plot_works(df.plot, yerr=df_err["x"], kind=kind)
self._check_has_errorbars(ax, xerr=0, yerr=2)
ax = _check_plot_works(df.plot, yerr=d_err, kind=kind)
self._check_has_errorbars(ax, xerr=0, yerr=2)
ax = _check_plot_works(df.plot, yerr=df_err, xerr=df_err, kind=kind)
self._check_has_errorbars(ax, xerr=2, yerr=2)
ax = _check_plot_works(
df.plot, yerr=df_err["x"], xerr=df_err["x"], kind=kind
)
self._check_has_errorbars(ax, xerr=2, yerr=2)
ax = _check_plot_works(df.plot, xerr=0.2, yerr=0.2, kind=kind)
self._check_has_errorbars(ax, xerr=2, yerr=2)

# _check_plot_works adds an ax so catch warning. see GH #13188
axes = _check_plot_works(
df.plot, yerr=df_err, xerr=df_err, subplots=True, kind=kind
)
self._check_has_errorbars(axes, xerr=1, yerr=1)

ax = _check_plot_works(
(df + 1).plot, yerr=df_err, xerr=df_err, kind="bar", log=True
)
self._check_has_errorbars(ax, xerr=2, yerr=2)
ax = _check_plot_works(df.plot, yerr=df_err, logx=True, logy=True)
self._check_has_errorbars(ax, xerr=0, yerr=2)

# yerr is raw error values
ax = _check_plot_works(df["y"].plot, yerr=np.ones(12) * 0.4)
self._check_has_errorbars(ax, xerr=0, yerr=1)
ax = _check_plot_works(df.plot, yerr=np.ones((2, 12)) * 0.4)
ax = _check_plot_works(df.plot, yerr=df_err, loglog=True)
self._check_has_errorbars(ax, xerr=0, yerr=2)

ax = _check_plot_works(
(df + 1).plot, yerr=df_err, xerr=df_err, kind="bar", log=True
)
self._check_has_errorbars(ax, xerr=2, yerr=2)

# yerr is raw error values
ax = _check_plot_works(df["y"].plot, yerr=np.ones(12) * 0.4)
self._check_has_errorbars(ax, xerr=0, yerr=1)

ax = _check_plot_works(df.plot, yerr=np.ones((2, 12)) * 0.4)
self._check_has_errorbars(ax, xerr=0, yerr=2)

# yerr is column name
for yerr in ["yerr", "誤差"]:
s_df = df.copy()
s_df[yerr] = np.ones(12) * 0.2

ax = _check_plot_works(s_df.plot, yerr=yerr)
self._check_has_errorbars(ax, xerr=0, yerr=2)

# yerr is column name
for yerr in ["yerr", "誤差"]:
s_df = df.copy()
s_df[yerr] = np.ones(12) * 0.2
ax = _check_plot_works(s_df.plot, yerr=yerr)
self._check_has_errorbars(ax, xerr=0, yerr=2)
ax = _check_plot_works(s_df.plot, y="y", x="x", yerr=yerr)
self._check_has_errorbars(ax, xerr=0, yerr=1)
ax = _check_plot_works(s_df.plot, y="y", x="x", yerr=yerr)
self._check_has_errorbars(ax, xerr=0, yerr=1)

with pytest.raises(ValueError):
df.plot(yerr=np.random.randn(11))
with pytest.raises(ValueError):
df.plot(yerr=np.random.randn(11))

df_err = DataFrame({"x": ["zzz"] * 12, "y": ["zzz"] * 12})
with pytest.raises((ValueError, TypeError)):
df.plot(yerr=df_err)
df_err = DataFrame({"x": ["zzz"] * 12, "y": ["zzz"] * 12})
with pytest.raises((ValueError, TypeError)):
df.plot(yerr=df_err)

@pytest.mark.slow
@pytest.mark.parametrize("kind", ["line", "bar", "barh"])
def test_errorbar_plot_different_kinds(self, kind):
d = {"x": np.arange(12), "y": np.arange(12, 0, -1)}
df = DataFrame(d)
d_err = {"x": np.ones(12) * 0.2, "y": np.ones(12) * 0.4}
df_err = DataFrame(d_err)

ax = _check_plot_works(df.plot, yerr=df_err["x"], kind=kind)
self._check_has_errorbars(ax, xerr=0, yerr=2)

ax = _check_plot_works(df.plot, yerr=d_err, kind=kind)
self._check_has_errorbars(ax, xerr=0, yerr=2)

ax = _check_plot_works(df.plot, yerr=df_err, xerr=df_err, kind=kind)
self._check_has_errorbars(ax, xerr=2, yerr=2)

ax = _check_plot_works(df.plot, yerr=df_err["x"], xerr=df_err["x"], kind=kind)
self._check_has_errorbars(ax, xerr=2, yerr=2)

ax = _check_plot_works(df.plot, xerr=0.2, yerr=0.2, kind=kind)
self._check_has_errorbars(ax, xerr=2, yerr=2)

with tm.assert_produces_warning(UserWarning):
# _check_plot_works creates subplots inside,
# which leads to warnings like this:
# UserWarning: To output multiple subplots,
# the figure containing the passed axes is being cleared
# Similar warnings were observed in GH #13188
axes = _check_plot_works(
df.plot, yerr=df_err, xerr=df_err, subplots=True, kind=kind
)
self._check_has_errorbars(axes, xerr=1, yerr=1)

@pytest.mark.xfail(reason="Iterator is consumed", raises=ValueError)
@pytest.mark.slow
Expand Down Expand Up @@ -2765,35 +2782,39 @@ def test_errorbar_with_partial_columns(self):
self._check_has_errorbars(ax, xerr=0, yerr=1)

@pytest.mark.slow
def test_errorbar_timeseries(self):
@pytest.mark.parametrize("kind", ["line", "bar", "barh"])
def test_errorbar_timeseries(self, kind):
d = {"x": np.arange(12), "y": np.arange(12, 0, -1)}
d_err = {"x": np.ones(12) * 0.2, "y": np.ones(12) * 0.4}

with warnings.catch_warnings():
d = {"x": np.arange(12), "y": np.arange(12, 0, -1)}
d_err = {"x": np.ones(12) * 0.2, "y": np.ones(12) * 0.4}
# check time-series plots
ix = date_range("1/1/2000", "1/1/2001", freq="M")
tdf = DataFrame(d, index=ix)
tdf_err = DataFrame(d_err, index=ix)

# check time-series plots
ix = date_range("1/1/2000", "1/1/2001", freq="M")
tdf = DataFrame(d, index=ix)
tdf_err = DataFrame(d_err, index=ix)
ax = _check_plot_works(tdf.plot, yerr=tdf_err, kind=kind)
self._check_has_errorbars(ax, xerr=0, yerr=2)

kinds = ["line", "bar", "barh"]
for kind in kinds:
ax = _check_plot_works(tdf.plot, yerr=tdf_err, kind=kind)
self._check_has_errorbars(ax, xerr=0, yerr=2)
ax = _check_plot_works(tdf.plot, yerr=d_err, kind=kind)
self._check_has_errorbars(ax, xerr=0, yerr=2)
ax = _check_plot_works(tdf.plot, y="y", yerr=tdf_err["x"], kind=kind)
self._check_has_errorbars(ax, xerr=0, yerr=1)
ax = _check_plot_works(tdf.plot, y="y", yerr="x", kind=kind)
self._check_has_errorbars(ax, xerr=0, yerr=1)
ax = _check_plot_works(tdf.plot, yerr=tdf_err, kind=kind)
self._check_has_errorbars(ax, xerr=0, yerr=2)

# _check_plot_works adds an ax so catch warning. see GH #13188
axes = _check_plot_works(
tdf.plot, kind=kind, yerr=tdf_err, subplots=True
)
self._check_has_errorbars(axes, xerr=0, yerr=1)
ax = _check_plot_works(tdf.plot, yerr=d_err, kind=kind)
self._check_has_errorbars(ax, xerr=0, yerr=2)

ax = _check_plot_works(tdf.plot, y="y", yerr=tdf_err["x"], kind=kind)
self._check_has_errorbars(ax, xerr=0, yerr=1)

ax = _check_plot_works(tdf.plot, y="y", yerr="x", kind=kind)
self._check_has_errorbars(ax, xerr=0, yerr=1)

ax = _check_plot_works(tdf.plot, yerr=tdf_err, kind=kind)
self._check_has_errorbars(ax, xerr=0, yerr=2)

with tm.assert_produces_warning(UserWarning):
# _check_plot_works creates subplots inside,
# which leads to warnings like this:
# UserWarning: To output multiple subplots,
# the figure containing the passed axes is being cleared
# Similar warnings were observed in GH #13188
axes = _check_plot_works(tdf.plot, kind=kind, yerr=tdf_err, subplots=True)
self._check_has_errorbars(axes, xerr=0, yerr=1)

def test_errorbar_asymmetrical(self):

Expand Down