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Fix automatic xlims in line plots #16600

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Merged
merged 7 commits into from
Sep 19, 2017
Merged

Fix automatic xlims in line plots #16600

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6a9eb51
TST: Add lineplot tests with unsorted x data
nmartensen Jun 10, 2017
603b5f1
BUG: set correct xlims for lines (#11471, #11310)
nmartensen Jun 5, 2017
0a7bbbe
BUG: Let new MPL automatically determine xlims (#15495)
nmartensen Jun 5, 2017
e68580a
TST: plotting: update expected results for matplotlib 2
nmartensen Jun 10, 2017
c440bc9
TST: plotting: Relax some tests to work with matplotlib 2.0
nmartensen Jun 10, 2017
a468598
DOC: lineplot/xlims whatsnew entry for v0.21.0
nmartensen Jul 19, 2017
15eae82
Merge branch 'master' into master
TomAugspurger Sep 18, 2017
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2 changes: 2 additions & 0 deletions doc/source/whatsnew/v0.21.0.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -525,6 +525,8 @@ Plotting
^^^^^^^^
- Bug in plotting methods using ``secondary_y`` and ``fontsize`` not setting secondary axis font size (:issue:`12565`)
- Bug when plotting ``timedelta`` and ``datetime`` dtypes on y-axis (:issue:`16953`)
- Line plots no longer assume monotonic x data when calculating xlims, they show the entire lines now even for unsorted x data. (:issue:`11310`)(:issue:`11471`)
- With matplotlib 2.0.0 and above, calculation of x limits for line plots is left to matplotlib, so that its new default settings are applied. (:issue:`15495`)
- Bug in ``Series.plot.bar`` or ``DataFramee.plot.bar`` with ``y`` not respecting user-passed ``color`` (:issue:`16822`)


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10 changes: 6 additions & 4 deletions pandas/plotting/_core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,8 @@
from pandas.util._decorators import Appender

from pandas.plotting._compat import (_mpl_ge_1_3_1,
_mpl_ge_1_5_0)
_mpl_ge_1_5_0,
_mpl_ge_2_0_0)
from pandas.plotting._style import (mpl_stylesheet, plot_params,
_get_standard_colors)
from pandas.plotting._tools import (_subplots, _flatten, table,
Expand Down Expand Up @@ -969,9 +970,10 @@ def _make_plot(self):
**kwds)
self._add_legend_handle(newlines[0], label, index=i)

lines = _get_all_lines(ax)
left, right = _get_xlim(lines)
ax.set_xlim(left, right)
if not _mpl_ge_2_0_0():
lines = _get_all_lines(ax)
left, right = _get_xlim(lines)
ax.set_xlim(left, right)

@classmethod
def _plot(cls, ax, x, y, style=None, column_num=None,
Expand Down
4 changes: 2 additions & 2 deletions pandas/plotting/_tools.py
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Original file line number Diff line number Diff line change
Expand Up @@ -361,8 +361,8 @@ def _get_xlim(lines):
left, right = np.inf, -np.inf
for l in lines:
x = l.get_xdata(orig=False)
left = min(x[0], left)
right = max(x[-1], right)
left = min(np.nanmin(x), left)
right = max(np.nanmax(x), right)
return left, right


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120 changes: 87 additions & 33 deletions pandas/tests/plotting/test_datetimelike.py
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Expand Up @@ -386,16 +386,24 @@ def test_get_finder(self):

@pytest.mark.slow
def test_finder_daily(self):
xp = Period('1999-1-1', freq='B').ordinal
day_lst = [10, 40, 252, 400, 950, 2750, 10000]
for n in day_lst:

if self.mpl_ge_2_0_0:
xpl1 = [7565, 7564, 7553, 7546, 7518, 7428, 7066]
xpl2 = [7566, 7564, 7554, 7546, 7519, 7429, 7066]
else:
xpl1 = xpl2 = [Period('1999-1-1', freq='B').ordinal] * len(day_lst)

for i, n in enumerate(day_lst):
xp = xpl1[i]
rng = bdate_range('1999-1-1', periods=n)
ser = Series(np.random.randn(len(rng)), rng)
_, ax = self.plt.subplots()
ser.plot(ax=ax)
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
assert xp == rs
xp = xpl2[i]
vmin, vmax = ax.get_xlim()
ax.set_xlim(vmin + 0.9, vmax)
rs = xaxis.get_majorticklocs()[0]
Expand All @@ -404,16 +412,24 @@ def test_finder_daily(self):

@pytest.mark.slow
def test_finder_quarterly(self):
xp = Period('1988Q1').ordinal
yrs = [3.5, 11]
for n in yrs:

if self.mpl_ge_2_0_0:
xpl1 = [68, 68]
xpl2 = [72, 68]
else:
xpl1 = xpl2 = [Period('1988Q1').ordinal] * len(yrs)

for i, n in enumerate(yrs):
xp = xpl1[i]
rng = period_range('1987Q2', periods=int(n * 4), freq='Q')
ser = Series(np.random.randn(len(rng)), rng)
_, ax = self.plt.subplots()
ser.plot(ax=ax)
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
assert rs == xp
xp = xpl2[i]
(vmin, vmax) = ax.get_xlim()
ax.set_xlim(vmin + 0.9, vmax)
rs = xaxis.get_majorticklocs()[0]
Expand All @@ -422,16 +438,24 @@ def test_finder_quarterly(self):

@pytest.mark.slow
def test_finder_monthly(self):
xp = Period('Jan 1988').ordinal
yrs = [1.15, 2.5, 4, 11]
for n in yrs:

if self.mpl_ge_2_0_0:
xpl1 = [216, 216, 204, 204]
xpl2 = [216, 216, 216, 204]
else:
xpl1 = xpl2 = [Period('Jan 1988').ordinal] * len(yrs)

for i, n in enumerate(yrs):
xp = xpl1[i]
rng = period_range('1987Q2', periods=int(n * 12), freq='M')
ser = Series(np.random.randn(len(rng)), rng)
_, ax = self.plt.subplots()
ser.plot(ax=ax)
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
assert rs == xp
xp = xpl2[i]
vmin, vmax = ax.get_xlim()
ax.set_xlim(vmin + 0.9, vmax)
rs = xaxis.get_majorticklocs()[0]
Expand All @@ -450,7 +474,11 @@ def test_finder_monthly_long(self):

@pytest.mark.slow
def test_finder_annual(self):
xp = [1987, 1988, 1990, 1990, 1995, 2020, 2070, 2170]
if self.mpl_ge_2_0_0:
xp = [1986, 1986, 1990, 1990, 1995, 2020, 1970, 1970]
else:
xp = [1987, 1988, 1990, 1990, 1995, 2020, 2070, 2170]

for i, nyears in enumerate([5, 10, 19, 49, 99, 199, 599, 1001]):
rng = period_range('1987', periods=nyears, freq='A')
ser = Series(np.random.randn(len(rng)), rng)
Expand All @@ -470,7 +498,10 @@ def test_finder_minutely(self):
ser.plot(ax=ax)
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
xp = Period('1/1/1999', freq='Min').ordinal
if self.mpl_ge_2_0_0:
xp = Period('1998-12-29 12:00', freq='Min').ordinal
else:
xp = Period('1/1/1999', freq='Min').ordinal
assert rs == xp

def test_finder_hourly(self):
Expand All @@ -481,7 +512,10 @@ def test_finder_hourly(self):
ser.plot(ax=ax)
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
xp = Period('1/1/1999', freq='H').ordinal
if self.mpl_ge_2_0_0:
xp = Period('1998-12-31 22:00', freq='H').ordinal
else:
xp = Period('1/1/1999', freq='H').ordinal
assert rs == xp

@pytest.mark.slow
Expand Down Expand Up @@ -665,8 +699,8 @@ def test_mixed_freq_regular_first(self):
assert idx2.equals(s2.index.to_period('B'))
left, right = ax2.get_xlim()
pidx = s1.index.to_period()
assert left == pidx[0].ordinal
assert right == pidx[-1].ordinal
assert left <= pidx[0].ordinal
assert right >= pidx[-1].ordinal

@pytest.mark.slow
def test_mixed_freq_irregular_first(self):
Expand Down Expand Up @@ -696,8 +730,8 @@ def test_mixed_freq_regular_first_df(self):
assert idx2.equals(s2.index.to_period('B'))
left, right = ax2.get_xlim()
pidx = s1.index.to_period()
assert left == pidx[0].ordinal
assert right == pidx[-1].ordinal
assert left <= pidx[0].ordinal
assert right >= pidx[-1].ordinal

@pytest.mark.slow
def test_mixed_freq_irregular_first_df(self):
Expand Down Expand Up @@ -1211,8 +1245,8 @@ def test_irregular_ts_shared_ax_xlim(self):

# check that axis limits are correct
left, right = ax.get_xlim()
assert left == ts_irregular.index.min().toordinal()
assert right == ts_irregular.index.max().toordinal()
assert left <= ts_irregular.index.min().toordinal()
assert right >= ts_irregular.index.max().toordinal()

@pytest.mark.slow
def test_secondary_y_non_ts_xlim(self):
Expand All @@ -1228,7 +1262,7 @@ def test_secondary_y_non_ts_xlim(self):
s2.plot(secondary_y=True, ax=ax)
left_after, right_after = ax.get_xlim()

assert left_before == left_after
assert left_before >= left_after
assert right_before < right_after

@pytest.mark.slow
Expand All @@ -1245,7 +1279,7 @@ def test_secondary_y_regular_ts_xlim(self):
s2.plot(secondary_y=True, ax=ax)
left_after, right_after = ax.get_xlim()

assert left_before == left_after
assert left_before >= left_after
assert right_before < right_after

@pytest.mark.slow
Expand Down Expand Up @@ -1278,8 +1312,8 @@ def test_secondary_y_irregular_ts_xlim(self):
ts_irregular[:5].plot(ax=ax)

left, right = ax.get_xlim()
assert left == ts_irregular.index.min().toordinal()
assert right == ts_irregular.index.max().toordinal()
assert left <= ts_irregular.index.min().toordinal()
assert right >= ts_irregular.index.max().toordinal()

def test_plot_outofbounds_datetime(self):
# 2579 - checking this does not raise
Expand All @@ -1294,9 +1328,14 @@ def test_format_timedelta_ticks_narrow(self):
if is_platform_mac():
pytest.skip("skip on mac for precision display issue on older mpl")

expected_labels = [
'00:00:00.00000000{:d}'.format(i)
for i in range(10)]
if self.mpl_ge_2_0_0:
expected_labels = [''] + [
'00:00:00.00000000{:d}'.format(2 * i)
for i in range(5)] + ['']
else:
expected_labels = [
'00:00:00.00000000{:d}'.format(i)
for i in range(10)]

rng = timedelta_range('0', periods=10, freq='ns')
df = DataFrame(np.random.randn(len(rng), 3), rng)
Expand All @@ -1312,17 +1351,32 @@ def test_format_timedelta_ticks_wide(self):
if is_platform_mac():
pytest.skip("skip on mac for precision display issue on older mpl")

expected_labels = [
'00:00:00',
'1 days 03:46:40',
'2 days 07:33:20',
'3 days 11:20:00',
'4 days 15:06:40',
'5 days 18:53:20',
'6 days 22:40:00',
'8 days 02:26:40',
''
]
if self.mpl_ge_2_0_0:
expected_labels = [
'',
'00:00:00',
'1 days 03:46:40',
'2 days 07:33:20',
'3 days 11:20:00',
'4 days 15:06:40',
'5 days 18:53:20',
'6 days 22:40:00',
'8 days 02:26:40',
'9 days 06:13:20',
''
]
else:
expected_labels = [
'00:00:00',
'1 days 03:46:40',
'2 days 07:33:20',
'3 days 11:20:00',
'4 days 15:06:40',
'5 days 18:53:20',
'6 days 22:40:00',
'8 days 02:26:40',
''
]

rng = timedelta_range('0', periods=10, freq='1 d')
df = DataFrame(np.random.randn(len(rng), 3), rng)
Expand Down
39 changes: 31 additions & 8 deletions pandas/tests/plotting/test_frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -304,6 +304,29 @@ def test_unsorted_index(self):
rs = Series(rs[:, 1], rs[:, 0], dtype=np.int64, name='y')
tm.assert_series_equal(rs, df.y)

def test_unsorted_index_lims(self):
df = DataFrame({'y': [0., 1., 2., 3.]}, index=[1., 0., 3., 2.])
ax = df.plot()
xmin, xmax = ax.get_xlim()
lines = ax.get_lines()
assert xmin <= np.nanmin(lines[0].get_data()[0])
assert xmax >= np.nanmax(lines[0].get_data()[0])

df = DataFrame({'y': [0., 1., np.nan, 3., 4., 5., 6.]},
index=[1., 0., 3., 2., np.nan, 3., 2.])
ax = df.plot()
xmin, xmax = ax.get_xlim()
lines = ax.get_lines()
assert xmin <= np.nanmin(lines[0].get_data()[0])
assert xmax >= np.nanmax(lines[0].get_data()[0])

df = DataFrame({'y': [0., 1., 2., 3.], 'z': [91., 90., 93., 92.]})
ax = df.plot(x='z', y='y')
xmin, xmax = ax.get_xlim()
lines = ax.get_lines()
assert xmin <= np.nanmin(lines[0].get_data()[0])
assert xmax >= np.nanmax(lines[0].get_data()[0])

@pytest.mark.slow
def test_subplots(self):
df = DataFrame(np.random.rand(10, 3),
Expand Down Expand Up @@ -735,14 +758,14 @@ def test_line_lim(self):
ax = df.plot()
xmin, xmax = ax.get_xlim()
lines = ax.get_lines()
assert xmin == lines[0].get_data()[0][0]
assert xmax == lines[0].get_data()[0][-1]
assert xmin <= lines[0].get_data()[0][0]
assert xmax >= lines[0].get_data()[0][-1]

ax = df.plot(secondary_y=True)
xmin, xmax = ax.get_xlim()
lines = ax.get_lines()
assert xmin == lines[0].get_data()[0][0]
assert xmax == lines[0].get_data()[0][-1]
assert xmin <= lines[0].get_data()[0][0]
assert xmax >= lines[0].get_data()[0][-1]

axes = df.plot(secondary_y=True, subplots=True)
self._check_axes_shape(axes, axes_num=3, layout=(3, 1))
Expand All @@ -751,8 +774,8 @@ def test_line_lim(self):
assert not hasattr(ax, 'right_ax')
xmin, xmax = ax.get_xlim()
lines = ax.get_lines()
assert xmin == lines[0].get_data()[0][0]
assert xmax == lines[0].get_data()[0][-1]
assert xmin <= lines[0].get_data()[0][0]
assert xmax >= lines[0].get_data()[0][-1]

def test_area_lim(self):
df = DataFrame(rand(6, 4), columns=['x', 'y', 'z', 'four'])
Expand All @@ -763,8 +786,8 @@ def test_area_lim(self):
xmin, xmax = ax.get_xlim()
ymin, ymax = ax.get_ylim()
lines = ax.get_lines()
assert xmin == lines[0].get_data()[0][0]
assert xmax == lines[0].get_data()[0][-1]
assert xmin <= lines[0].get_data()[0][0]
assert xmax >= lines[0].get_data()[0][-1]
assert ymin == 0

ax = _check_plot_works(neg_df.plot.area, stacked=stacked)
Expand Down
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