我正在尝试从pandas数据框构建图，但是当我将该数据框的一部分作为yerr传递时，出现Key错误：0。
我已经检查过，并且在pandas page上报告了类似的问题，但是应该可以解决它，所以我不确定它来自哪里。
有人对为什么有想法，或者我如何绘制这两个数据框？
编辑：这就是为什么https://github.com/pydata/pandas/issues/11858的原因，无论如何我都可以解决该问题？
这是means.plot(kind='bar')现在我需要yerr：
我切片的数据帧看起来像这样：
#means
condition scenario_1 scenario_2 scenario_3
date
1950 7857.495 4418.180 4418.180
1960 1361.255 769.095 769.095
1970 947.855 649.875 649.875
1980 743.565 542.350 542.350
1990 4157.495 3780.185 3780.185
2000 4473.730 5953.955 5940.020
2010 962.565 736.735 486.140
2020 663.065 464.065 358.580
2030 609.285 375.195 264.415
2040 1706.620 1167.375 1051.090
2050 882.075 518.810 393.240
2060 1483.740 863.260 778.115
2070 2540.660 2417.420 2392.325
2080 3329.965 2484.215 2332.140
2090 1981.605 1326.115 1363.695
#errors
scenario_1 scneario_2 scenario_3
date
1950 6882.473594 3977.169284 3977.169284
1960 2063.900035 1209.355869 1209.355869
1970 1641.563211 1132.895230 1132.895230
1980 1304.848179 893.150490 893.150490
1990 4833.384691 4071.813927 4071.813927
2000 3071.053838 3300.206511 3262.672983
2010 1519.563511 1099.878070 703.131441
2020 1085.763048 694.784212 456.909226
2030 1012.836592 647.889589 342.873572
2040 2242.979678 1573.683502 1298.028517
2050 1462.245123 891.855864 517.363621
2060 2225.214719 1213.065737 975.519051
2070 2927.880585 2423.424810 2076.170121
2080 3572.416062 2436.318656 2316.993311
2090 2510.864263 1487.605484 1499.623779
#which I try to plot that way:
means.plot(kind='bar',yerr=errors)
我可以毫无问题地绘制平均值，但是每次我尝试添加yerr时，它都会给我：
KeyError Traceback (most recent call last)
<ipython-input-68-2e629f7a18f3> in <module>()
----> 1 means.plot(kind='bar', yerr=errors)
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/tools/plotting.pyc in __call__(self, x, y, kind, ax, subplots, sharex, sharey, layout, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, secondary_y, sort_columns, **kwds)
3669 fontsize=fontsize, colormap=colormap, table=table,
3670 yerr=yerr, xerr=xerr, secondary_y=secondary_y,
-> 3671 sort_columns=sort_columns, **kwds)
3672 __call__.__doc__ = plot_frame.__doc__
3673
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/tools/plotting.pyc in plot_frame(data, x, y, kind, ax, subplots, sharex, sharey, layout, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, secondary_y, sort_columns, **kwds)
2554 yerr=yerr, xerr=xerr,
2555 secondary_y=secondary_y, sort_columns=sort_columns,
-> 2556 **kwds)
2557
2558
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/tools/plotting.pyc in _plot(data, x, y, subplots, ax, kind, **kwds)
2382 plot_obj = klass(data, subplots=subplots, ax=ax, kind=kind, **kwds)
2383
-> 2384 plot_obj.generate()
2385 plot_obj.draw()
2386 return plot_obj.result
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/tools/plotting.pyc in generate(self)
985 self._compute_plot_data()
986 self._setup_subplots()
--> 987 self._make_plot()
988 self._add_table()
989 self._make_legend()
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/tools/plotting.pyc in _make_plot(self)
1920 w = self.bar_width / K
1921 rect = self._plot(ax, self.ax_pos + (i + 0.5) * w, y, w,
-> 1922 start=start, label=label, log=self.log, **kwds)
1923 self._add_legend_handle(rect, label, index=i)
1924
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/tools/plotting.pyc in _plot(cls, ax, x, y, w, start, log, **kwds)
1870 @classmethod
1871 def _plot(cls, ax, x, y, w, start=0, log=False, **kwds):
-> 1872 return ax.bar(x, y, w, bottom=start, log=log, **kwds)
1873
1874 @property
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/__init__.pyc in inner(ax, *args, **kwargs)
1810 warnings.warn(msg % (label_namer, func.__name__),
1811 RuntimeWarning, stacklevel=2)
-> 1812 return func(ax, *args, **kwargs)
1813 pre_doc = inner.__doc__
1814 if pre_doc is None:
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/axes/_axes.pyc in bar(self, left, height, width, bottom, **kwargs)
2154 errorbar = self.errorbar(x, y,
2155 yerr=yerr, xerr=xerr,
-> 2156 fmt='none', **error_kw)
2157 else:
2158 errorbar = None
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/__init__.pyc in inner(ax, *args, **kwargs)
1810 warnings.warn(msg % (label_namer, func.__name__),
1811 RuntimeWarning, stacklevel=2)
-> 1812 return func(ax, *args, **kwargs)
1813 pre_doc = inner.__doc__
1814 if pre_doc is None:
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/axes/_axes.pyc in errorbar(self, x, y, yerr, xerr, fmt, ecolor, elinewidth, capsize, barsabove, lolims, uplims, xlolims, xuplims, errorevery, capthick, **kwargs)
2961 # Check for scalar or symmetric, as in xerr.
2962 if len(yerr) > 1 and not ((len(yerr) == len(y) and not (
-> 2963 iterable(yerr[0]) and len(yerr[0]) > 1))):
2964 raise ValueError("yerr must be a scalar, the same "
2965 "dimensions as y, or 2xN.")
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/core/series.pyc in __getitem__(self, key)
555 def __getitem__(self, key):
556 try:
--> 557 result = self.index.get_value(self, key)
558
559 if not np.isscalar(result):
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/core/index.pyc in get_value(self, series, key)
1788
1789 try:
-> 1790 return self._engine.get_value(s, k)
1791 except KeyError as e1:
1792 if len(self) > 0 and self.inferred_type in ['integer','boolean']:
pandas/index.pyx in pandas.index.IndexEngine.get_value (pandas/index.c:3204)()
pandas/index.pyx in pandas.index.IndexEngine.get_value (pandas/index.c:2903)()
pandas/index.pyx in pandas.index.IndexEngine.get_loc (pandas/index.c:3843)()
pandas/hashtable.pyx in pandas.hashtable.Int64HashTable.get_item (pandas/hashtable.c:6525)()
pandas/hashtable.pyx in pandas.hashtable.Int64HashTable.get_item (pandas/hashtable.c:6463)()
KeyError: 0
我读到yerr的索引必须包含0，所以我也尝试这样做，但是得到了相同的错误。足够令人沮丧的是，如果我仅绘制具有scneario_1错误的scenario_1的平均值，它将起作用...
我刚刚升级了熊猫和matplotlib。
这是用于准备数据帧的丑陋代码：
frames = []
# Cleaning and adding some fields for each individual scenario's dataframe for concat
for scenario in scenarios :
i = glob.glob( os.path.join( input_path,graph_variable, '*'.join([ 'ALF',graph_variable.replace('_',''), model, scenario,'.csv' ]) ) )[0]
tab = pd.read_csv( i, index_col=0 ).ix[begin:end]
tab['std'] = tab.std(axis=1)
tab['date'] = tab.index
tab['scenario']= scenario
tab = pd.melt(tab, id_vars=["date", "scenario",'std'], var_name="condition")
frames.append(tab)
#Complete dataframe creation with both scenario in long data form
df = pd.concat(frames, ignore_index= True)
df = df.drop('condition', 1)
df = df.rename(columns = {'scenario':'condition'})
df = df.sort_values(by=['condition','date'])
df = df.reset_index(drop=True)
df = df.groupby(["condition", "date"]).mean().unstack("condition")
errors = df['std'].groupby(df.index // 10 * 10).sum()
means = df.value.groupby(df.index // 10 * 10).sum()
最佳答案
这是一个快速而肮脏的解决方案，但是您可以添加一个索引值为零的蒙版条目，并调整图边界以将其隐藏。
# log the plot bounds we'll actually want at the end
xlim = means.index.min(), means.index.max()
# add data points that will not be plotted anyways
means = means.append(DataFrame(np.empty((1, len(means.columns)))+np.nan,
columns=means.columns, index=[0.0,]))
errors = errors.append(DataFrame(np.empty((1, len(df.columns)))+np.nan,
columns=means.columns, index=[0.0,]))
ax = means.plot(kind='bar', yerr=errors)
ax.set_xlim(*xlim)
关于python - 用yerr绘制的 Pandas 给出关键错误:0，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/35137961/