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BUG/CLN: LinePlot uses incorrect xlim when secondary_y=True #7459

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merged 1 commit into from Jul 7, 2014
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5 doc/source/v0.14.1.txt
@@ -148,6 +148,11 @@ Performance
+
+- Bug in line plot doesn't set correct ``xlim`` if ``secondary_y=True`` (:issue:`7459`)
+
+
+
Experimental
~~~~~~~~~~~~
View
35 pandas/tests/test_graphics.py
@@ -457,6 +457,20 @@ def test_plot_figsize_and_title(self):
self._check_text_labels(ax.title, 'Test')
self._check_axes_shape(ax, axes_num=1, layout=(1, 1), figsize=(16, 8))
+ def test_ts_line_lim(self):
+ ax = self.ts.plot()
+ xmin, xmax = ax.get_xlim()
+ lines = ax.get_lines()
+ self.assertEqual(xmin, lines[0].get_data(orig=False)[0][0])
+ self.assertEqual(xmax, lines[0].get_data(orig=False)[0][-1])
+ tm.close()
+
+ ax = self.ts.plot(secondary_y=True)
+ xmin, xmax = ax.get_xlim()
+ lines = ax.get_lines()
+ self.assertEqual(xmin, lines[0].get_data(orig=False)[0][0])
+ self.assertEqual(xmax, lines[0].get_data(orig=False)[0][-1])
+
def test_ts_area_lim(self):
ax = self.ts.plot(kind='area', stacked=False)
xmin, xmax = ax.get_xlim()
@@ -1091,6 +1105,27 @@ def test_line_area_nan_df(self):
self.assert_numpy_array_equal(ax.lines[0].get_ydata(), expected1)
self.assert_numpy_array_equal(ax.lines[1].get_ydata(), expected2)
+ def test_line_lim(self):
+ df = DataFrame(rand(6, 3), columns=['x', 'y', 'z'])
+ ax = df.plot()
+ xmin, xmax = ax.get_xlim()
+ lines = ax.get_lines()
+ self.assertEqual(xmin, lines[0].get_data()[0][0])
+ self.assertEqual(xmax, lines[0].get_data()[0][-1])
+
+ ax = df.plot(secondary_y=True)
+ xmin, xmax = ax.get_xlim()
+ lines = ax.get_lines()
+ self.assertEqual(xmin, lines[0].get_data()[0][0])
+ self.assertEqual(xmax, lines[0].get_data()[0][-1])
+
+ axes = df.plot(secondary_y=True, subplots=True)
+ for ax in axes:
+ xmin, xmax = ax.get_xlim()
+ lines = ax.get_lines()
+ self.assertEqual(xmin, lines[0].get_data()[0][0])
+ self.assertEqual(xmax, lines[0].get_data()[0][-1])
+
def test_area_lim(self):
df = DataFrame(rand(6, 4),
columns=['x', 'y', 'z', 'four'])
View
92 pandas/tools/plotting.py
@@ -909,13 +909,9 @@ def _args_adjust(self):
pass
def _maybe_right_yaxis(self, ax):
- _types = (list, tuple, np.ndarray)
- sec_true = isinstance(self.secondary_y, bool) and self.secondary_y
- list_sec = isinstance(self.secondary_y, _types)
- has_sec = list_sec and len(self.secondary_y) > 0
- all_sec = list_sec and len(self.secondary_y) == self.nseries
-
- if (sec_true or has_sec) and not hasattr(ax, 'right_ax'):
+ if hasattr(ax, 'right_ax'):
+ return ax.right_ax
+ else:
orig_ax, new_ax = ax, ax.twinx()
new_ax._get_lines.color_cycle = orig_ax._get_lines.color_cycle
@@ -924,38 +920,25 @@ def _maybe_right_yaxis(self, ax):
if len(orig_ax.get_lines()) == 0: # no data on left y
orig_ax.get_yaxis().set_visible(False)
-
- if len(new_ax.get_lines()) == 0:
- new_ax.get_yaxis().set_visible(False)
-
- if sec_true or all_sec:
- ax = new_ax
- else:
- ax.get_yaxis().set_visible(True)
-
- return ax
+ return new_ax
def _setup_subplots(self):
if self.subplots:
nrows, ncols = self._get_layout()
fig, axes = _subplots(nrows=nrows, ncols=ncols,
sharex=self.sharex, sharey=self.sharey,
- figsize=self.figsize, ax=self.ax,
- secondary_y=self.secondary_y,
- data=self.data)
+ figsize=self.figsize, ax=self.ax)
if not com.is_list_like(axes):
axes = np.array([axes])
else:
if self.ax is None:
fig = self.plt.figure(figsize=self.figsize)
ax = fig.add_subplot(111)
- ax = self._maybe_right_yaxis(ax)
else:
fig = self.ax.get_figure()
if self.figsize is not None:
fig.set_size_inches(self.figsize)
- ax = self._maybe_right_yaxis(self.ax)
-
+ ax = self.ax
axes = [ax]
if self.logx or self.loglog:
@@ -1182,14 +1165,21 @@ def _get_ax(self, i):
# get the twinx ax if appropriate
if self.subplots:
ax = self.axes[i]
+
+ if self.on_right(i):
+ ax = self._maybe_right_yaxis(ax)
+ self.axes[i] = ax
else:
ax = self.axes[0]
- if self.on_right(i):
- if hasattr(ax, 'right_ax'):
- ax = ax.right_ax
- elif hasattr(ax, 'left_ax'):
- ax = ax.left_ax
+ if self.on_right(i):
+ ax = self._maybe_right_yaxis(ax)
+
+ sec_true = isinstance(self.secondary_y, bool) and self.secondary_y
+ all_sec = (com.is_list_like(self.secondary_y) and
+ len(self.secondary_y) == self.nseries)
+ if sec_true or all_sec:
+ self.axes[0] = ax
ax.get_yaxis().set_visible(True)
return ax
@@ -1550,8 +1540,6 @@ def _make_plot(self):
data = self._maybe_convert_index(self.data)
self._make_ts_plot(data)
else:
- from pandas.core.frame import DataFrame
- lines = []
x = self._get_xticks(convert_period=True)
plotf = self._get_plot_function()
@@ -1563,8 +1551,6 @@ def _make_plot(self):
kwds = self.kwds.copy()
self._maybe_add_color(colors, kwds, style, i)
- lines += _get_all_lines(ax)
-
errors = self._get_errorbars(label=label, index=i)
kwds = dict(kwds, **errors)
@@ -1588,15 +1574,13 @@ def _make_plot(self):
newlines = plotf(*args, **kwds)
self._add_legend_handle(newlines[0], label, index=i)
- lines.append(newlines[0])
-
if self.stacked and not self.subplots:
if (y >= 0).all():
self._pos_prior += y
elif (y <= 0).all():
self._neg_prior += y
- if self._is_datetype():
+ lines = _get_all_lines(ax)
left, right = _get_xlim(lines)
ax.set_xlim(left, right)
@@ -2253,14 +2237,7 @@ def plot_series(series, label=None, kind='line', use_index=True, rot=None,
import matplotlib.pyplot as plt
if ax is None and len(plt.get_fignums()) > 0:
ax = _gca()
- if ax.get_yaxis().get_ticks_position().strip().lower() == 'right':
- fig = _gcf()
- axes = fig.get_axes()
- for i in reversed(range(len(axes))):
- ax = axes[i]
- ypos = ax.get_yaxis().get_ticks_position().strip().lower()
- if ypos == 'left':
- break
+ ax = getattr(ax, 'left_ax', ax)
# is there harm in this?
if label is None:
@@ -2890,8 +2867,7 @@ def _get_layout(nplots, layout=None):
def _subplots(nrows=1, ncols=1, naxes=None, sharex=False, sharey=False, squeeze=True,
- subplot_kw=None, ax=None, secondary_y=False, data=None,
- **fig_kw):
+ subplot_kw=None, ax=None, **fig_kw):
"""Create a figure with a set of subplots already made.
This utility wrapper makes it convenient to create common layouts of
@@ -2932,12 +2908,6 @@ def _subplots(nrows=1, ncols=1, naxes=None, sharex=False, sharey=False, squeeze=
ax : Matplotlib axis object, optional
- secondary_y : boolean or sequence of ints, default False
- If True then y-axis will be on the right
-
@jreback

jreback Jul 6, 2014

Contributor

what did these kw's do?
- data : DataFrame, optional
- If secondary_y is a sequence, data is used to select columns.
-
fig_kw : Other keyword arguments to be passed to the figure() call.
Note that all keywords not recognized above will be
automatically included here.
@@ -2993,22 +2963,8 @@ def _subplots(nrows=1, ncols=1, naxes=None, sharex=False, sharey=False, squeeze=
axarr = np.empty(nplots, dtype=object)
- def on_right(i):
- if isinstance(secondary_y, bool):
- return secondary_y
- if isinstance(data, DataFrame):
- return data.columns[i] in secondary_y
-
# Create first subplot separately, so we can share it if requested
ax0 = fig.add_subplot(nrows, ncols, 1, **subplot_kw)
- if on_right(0):
- orig_ax = ax0
- ax0 = ax0.twinx()
- ax0._get_lines.color_cycle = orig_ax._get_lines.color_cycle
-
- orig_ax.get_yaxis().set_visible(False)
- orig_ax.right_ax = ax0
- ax0.left_ax = orig_ax
if sharex:
subplot_kw['sharex'] = ax0
@@ -3020,12 +2976,6 @@ def on_right(i):
# convention.
for i in range(1, nplots):
ax = fig.add_subplot(nrows, ncols, i + 1, **subplot_kw)
- if on_right(i):
- orig_ax = ax
- ax = ax.twinx()
- ax._get_lines.color_cycle = orig_ax._get_lines.color_cycle
-
- orig_ax.get_yaxis().set_visible(False)
axarr[i] = ax
if nplots > 1:
View
14 pandas/tseries/plotting.py
@@ -4,11 +4,7 @@
"""
#!!! TODO: Use the fact that axis can have units to simplify the process
-import datetime as pydt
-from datetime import datetime
-
from matplotlib import pylab
-import matplotlib.units as units
import numpy as np
@@ -22,7 +18,7 @@
from pandas.tseries.converter import (PeriodConverter, TimeSeries_DateLocator,
TimeSeries_DateFormatter)
-from pandas.tools.plotting import _get_all_lines
+from pandas.tools.plotting import _get_all_lines, _get_xlim
#----------------------------------------------------------------------
# Plotting functions and monkey patches
@@ -222,14 +218,6 @@ def _get_freq(ax, series):
return freq
-def _get_xlim(lines):
- left, right = np.inf, -np.inf
- for l in lines:
- x = l.get_xdata()
- left = min(x[0].ordinal, left)
- right = max(x[-1].ordinal, right)
- return left, right
-
# Patch methods for subplot. Only format_dateaxis is currently used.
# Do we need the rest for convenience?