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May 2, 2014
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ENH: Scatter plot now supports errorbar #6834

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2 changes: 1 addition & 1 deletion doc/source/release.rst
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Expand Up @@ -63,7 +63,7 @@ New features
Date is used primarily in astronomy and represents the number of days from
noon, January 1, 4713 BC. Because nanoseconds are used to define the time
in pandas the actual range of dates that you can use is 1678 AD to 2262 AD. (:issue:`4041`)
- Added error bar support to the ``.plot`` method of ``DataFrame`` and ``Series`` (:issue:`3796`)
- Added error bar support to the ``.plot`` method of ``DataFrame`` and ``Series`` (:issue:`3796`, :issue:`6834`)
- Implemented ``Panel.pct_change`` (:issue:`6904`)

API Changes
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2 changes: 1 addition & 1 deletion doc/source/v0.14.0.txt
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Expand Up @@ -365,7 +365,7 @@ Plotting

- Hexagonal bin plots from ``DataFrame.plot`` with ``kind='hexbin'`` (:issue:`5478`), See :ref:`the docs<visualization.hexbin>`.
- ``DataFrame.plot`` and ``Series.plot`` now supports area plot with specifying ``kind='area'`` (:issue:`6656`)
- Plotting with Error Bars is now supported in the ``.plot`` method of ``DataFrame`` and ``Series`` objects (:issue:`3796`), See :ref:`the docs<visualization.errorbars>`.
- Plotting with Error Bars is now supported in the ``.plot`` method of ``DataFrame`` and ``Series`` objects (:issue:`3796`, :issue:`6834`), See :ref:`the docs<visualization.errorbars>`.
- ``DataFrame.plot`` and ``Series.plot`` now support a ``table`` keyword for plotting ``matplotlib.Table``, See :ref:`the docs<visualization.table>`.
- ``plot(legend='reverse')`` will now reverse the order of legend labels for
most plot kinds. (:issue:`6014`)
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5 changes: 4 additions & 1 deletion doc/source/visualization.rst
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Expand Up @@ -394,10 +394,13 @@ x and y errorbars are supported and be supplied using the ``xerr`` and ``yerr``

- As a ``DataFrame`` or ``dict`` of errors with column names matching the ``columns`` attribute of the plotting ``DataFrame`` or matching the ``name`` attribute of the ``Series``
- As a ``str`` indicating which of the columns of plotting ``DataFrame`` contain the error values
- As raw values (``list``, ``tuple``, or ``np.ndarray``). Must be the same length as the plotting ``DataFrame``/``Series``
- As list-like raw values (``list``, ``tuple``, or ``np.ndarray``). Must be the same length as the plotting ``DataFrame``/``Series``
- As float. The error value will be applied to all data.

Asymmetrical error bars are also supported, however raw error values must be provided in this case. For a ``M`` length ``Series``, a ``Mx2`` array should be provided indicating lower and upper (or left and right) errors. For a ``MxN`` ``DataFrame``, asymmetrical errors should be in a ``Mx2xN`` array.

**Note**: Plotting ``xerr`` is not supported in time series.

Here is an example of one way to easily plot group means with standard deviations from the raw data.

.. ipython:: python
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155 changes: 121 additions & 34 deletions pandas/tests/test_graphics.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,6 @@
#!/usr/bin/env python
# coding: utf-8

import nose
import os
import string
Expand Down Expand Up @@ -27,7 +30,6 @@ def _skip_if_no_scipy():
except ImportError:
raise nose.SkipTest("no scipy")


@tm.mplskip
class TestSeriesPlots(tm.TestCase):
def setUp(self):
Expand Down Expand Up @@ -315,24 +317,36 @@ def test_dup_datetime_index_plot(self):
@slow
def test_errorbar_plot(self):

s = Series(np.arange(10))
s = Series(np.arange(10), name='x')
s_err = np.random.randn(10)

d_err = DataFrame(randn(10, 2), index=s.index, columns=['x', 'y'])
# test line and bar plots
kinds = ['line', 'bar']
for kind in kinds:
_check_plot_works(s.plot, yerr=Series(s_err), kind=kind)
_check_plot_works(s.plot, yerr=s_err, kind=kind)
_check_plot_works(s.plot, yerr=s_err.tolist(), kind=kind)

_check_plot_works(s.plot, xerr=s_err)
ax = _check_plot_works(s.plot, yerr=Series(s_err), kind=kind)
_check_has_errorbars(self, ax, xerr=0, yerr=1)
ax = _check_plot_works(s.plot, yerr=s_err, kind=kind)
_check_has_errorbars(self, ax, xerr=0, yerr=1)
ax = _check_plot_works(s.plot, yerr=s_err.tolist(), kind=kind)
_check_has_errorbars(self, ax, xerr=0, yerr=1)
ax = _check_plot_works(s.plot, yerr=d_err, kind=kind)
_check_has_errorbars(self, ax, xerr=0, yerr=1)
ax = _check_plot_works(s.plot, xerr=0.2, yerr=0.2, kind=kind)
_check_has_errorbars(self, ax, xerr=1, yerr=1)

ax = _check_plot_works(s.plot, xerr=s_err)
_check_has_errorbars(self, ax, xerr=1, yerr=0)

# test time series plotting
ix = date_range('1/1/2000', '1/1/2001', freq='M')
ts = Series(np.arange(12), index=ix)
ts = Series(np.arange(12), index=ix, name='x')
ts_err = Series(np.random.randn(12), index=ix)
td_err = DataFrame(randn(12, 2), index=ix, columns=['x', 'y'])

_check_plot_works(ts.plot, yerr=ts_err)
ax = _check_plot_works(ts.plot, yerr=ts_err)
_check_has_errorbars(self, ax, xerr=0, yerr=1)
ax = _check_plot_works(ts.plot, yerr=td_err)
_check_has_errorbars(self, ax, xerr=0, yerr=1)

# check incorrect lengths and types
with tm.assertRaises(ValueError):
Expand Down Expand Up @@ -1505,27 +1519,51 @@ def test_errorbar_plot(self):
df_err = DataFrame(d_err)

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

kinds = ['line', 'bar', 'barh']
for kind in kinds:
_check_plot_works(df.plot, yerr=df_err['x'], kind=kind)
_check_plot_works(df.plot, yerr=d_err, kind=kind)
_check_plot_works(df.plot, yerr=df_err, xerr=df_err, kind=kind)
_check_plot_works(df.plot, yerr=df_err['x'], xerr=df_err['x'], kind=kind)
_check_plot_works(df.plot, yerr=df_err, xerr=df_err, subplots=True, kind=kind)
ax = _check_plot_works(df.plot, yerr=df_err['x'], kind=kind)
_check_has_errorbars(self, ax, xerr=0, yerr=2)
ax = _check_plot_works(df.plot, yerr=d_err, kind=kind)
_check_has_errorbars(self, ax, xerr=0, yerr=2)
ax = _check_plot_works(df.plot, yerr=df_err, xerr=df_err, kind=kind)
_check_has_errorbars(self, ax, xerr=2, yerr=2)
ax = _check_plot_works(df.plot, yerr=df_err['x'], xerr=df_err['x'], kind=kind)
_check_has_errorbars(self, ax, xerr=2, yerr=2)
ax = _check_plot_works(df.plot, xerr=0.2, yerr=0.2, kind=kind)
_check_has_errorbars(self, ax, xerr=2, yerr=2)
axes = _check_plot_works(df.plot, yerr=df_err, xerr=df_err, subplots=True, kind=kind)
for ax in axes:
_check_has_errorbars(self, ax, xerr=1, yerr=1)

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

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

# yerr is iterator
import itertools
ax = _check_plot_works(df.plot, yerr=itertools.repeat(0.1, len(df)))
_check_has_errorbars(self, ax, xerr=0, yerr=2)

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

with tm.assertRaises(ValueError):
df.plot(yerr=np.random.randn(11))
Expand All @@ -1539,21 +1577,33 @@ def test_errorbar_with_integer_column_names(self):
# test with integer column names
df = DataFrame(np.random.randn(10, 2))
df_err = DataFrame(np.random.randn(10, 2))
_check_plot_works(df.plot, yerr=df_err)
_check_plot_works(df.plot, y=0, yerr=1)
ax = _check_plot_works(df.plot, yerr=df_err)
_check_has_errorbars(self, ax, xerr=0, yerr=2)
ax = _check_plot_works(df.plot, y=0, yerr=1)
_check_has_errorbars(self, ax, xerr=0, yerr=1)

@slow
def test_errorbar_with_partial_columns(self):
df = DataFrame(np.random.randn(10, 3))
df_err = DataFrame(np.random.randn(10, 2), columns=[0, 2])
kinds = ['line', 'bar']
for kind in kinds:
_check_plot_works(df.plot, yerr=df_err, kind=kind)
ax = _check_plot_works(df.plot, yerr=df_err, kind=kind)
_check_has_errorbars(self, ax, xerr=0, yerr=2)

ix = date_range('1/1/2000', periods=10, freq='M')
df.set_index(ix, inplace=True)
df_err.set_index(ix, inplace=True)
_check_plot_works(df.plot, yerr=df_err, kind='line')
ax = _check_plot_works(df.plot, yerr=df_err, kind='line')
_check_has_errorbars(self, ax, xerr=0, yerr=2)

d = {'x': np.arange(12), 'y': np.arange(12, 0, -1)}
df = DataFrame(d)
d_err = {'x': np.ones(12)*0.2, 'z': np.ones(12)*0.4}
df_err = DataFrame(d_err)
for err in [d_err, df_err]:
ax = _check_plot_works(df.plot, yerr=err)
_check_has_errorbars(self, ax, xerr=0, yerr=1)

@slow
def test_errorbar_timeseries(self):
Expand All @@ -1568,13 +1618,19 @@ def test_errorbar_timeseries(self):

kinds = ['line', 'bar', 'barh']
for kind in kinds:
_check_plot_works(tdf.plot, yerr=tdf_err, kind=kind)
_check_plot_works(tdf.plot, yerr=d_err, kind=kind)
_check_plot_works(tdf.plot, y='y', kind=kind)
_check_plot_works(tdf.plot, y='y', yerr='x', kind=kind)
_check_plot_works(tdf.plot, yerr=tdf_err, kind=kind)
_check_plot_works(tdf.plot, kind=kind, subplots=True)

ax = _check_plot_works(tdf.plot, yerr=tdf_err, kind=kind)
_check_has_errorbars(self, ax, xerr=0, yerr=2)
ax = _check_plot_works(tdf.plot, yerr=d_err, kind=kind)
_check_has_errorbars(self, ax, xerr=0, yerr=2)
ax = _check_plot_works(tdf.plot, y='y', yerr=tdf_err['x'], kind=kind)
_check_has_errorbars(self, ax, xerr=0, yerr=1)
ax = _check_plot_works(tdf.plot, y='y', yerr='x', kind=kind)
_check_has_errorbars(self, ax, xerr=0, yerr=1)
ax = _check_plot_works(tdf.plot, yerr=tdf_err, kind=kind)
_check_has_errorbars(self, ax, xerr=0, yerr=2)
axes = _check_plot_works(tdf.plot, kind=kind, yerr=tdf_err, subplots=True)
for ax in axes:
_check_has_errorbars(self, ax, xerr=0, yerr=1)

def test_errorbar_asymmetrical(self):

Expand Down Expand Up @@ -1608,6 +1664,21 @@ def test_table(self):
plotting.table(ax, df.T)
self.assert_(len(ax.tables) == 1)

def test_errorbar_scatter(self):
df = DataFrame(np.random.randn(5, 2), index=range(5), columns=['x', 'y'])
df_err = DataFrame(np.random.randn(5, 2) / 5,
index=range(5), columns=['x', 'y'])

ax = _check_plot_works(df.plot, kind='scatter', x='x', y='y')
_check_has_errorbars(self, ax, xerr=0, yerr=0)
ax = _check_plot_works(df.plot, kind='scatter', x='x', y='y', xerr=df_err)
_check_has_errorbars(self, ax, xerr=1, yerr=0)
ax = _check_plot_works(df.plot, kind='scatter', x='x', y='y', yerr=df_err)
_check_has_errorbars(self, ax, xerr=0, yerr=1)
ax = _check_plot_works(df.plot, kind='scatter', x='x', y='y',
xerr=df_err, yerr=df_err)
_check_has_errorbars(self, ax, xerr=1, yerr=1)


@tm.mplskip
class TestDataFrameGroupByPlots(tm.TestCase):
Expand Down Expand Up @@ -1803,8 +1874,24 @@ def assert_is_valid_plot_return_object(objs):
''.format(objs.__class__.__name__))


def _check_has_errorbars(t, ax, xerr=0, yerr=0):
containers = ax.containers
xerr_count = 0
yerr_count = 0
for c in containers:
has_xerr = getattr(c, 'has_xerr', False)
has_yerr = getattr(c, 'has_yerr', False)
if has_xerr:
xerr_count += 1
if has_yerr:
yerr_count += 1
t.assertEqual(xerr, xerr_count)
t.assertEqual(yerr, yerr_count)


def _check_plot_works(f, *args, **kwargs):
import matplotlib.pyplot as plt
ret = None

try:
try:
Expand Down
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