在Seaborn中，您可以使用FacetGrid设置要绘制的数据感知网格。然后，您可以使用map或map_dataframe方法绘制这些网格。
我无法正确指定适用于map或map_dataframe的用户定义的绘图功能。在这个例子中，我使用errorbar函数，我希望将错误值作为2xN数组传递。在我的例子中（取自@ mwaskom的回答here），错误是对称的 - 但想象一下我的情况并非如此。
In [255]:
from scipy import stats
tips_all = sns.load_dataset("tips")
tips_grouped = tips_all.groupby(["smoker", "size"])
tips = tips_grouped.mean()
tips["error_min"] = tips_grouped.total_bill.apply(stats.sem) * 1.96
tips["error_max"] = tips_grouped.total_bill.apply(stats.sem) * 1.96
tips.reset_index(inplace=True)
tips
Out[255]:
smoker size total_bill tip error_min error_max
0 No 1 8.660000 1.415000 2.763600 2.763600
1 No 2 15.342333 2.489000 0.919042 0.919042
2 No 3 21.009615 3.069231 2.680447 2.680447
3 No 4 27.769231 4.195769 3.303131 3.303131
4 No 5 30.576667 5.046667 11.620808 11.620808
5 No 6 34.830000 5.225000 9.194360 9.194360
6 Yes 1 5.825000 1.460000 5.399800 5.399800
7 Yes 2 17.955758 2.709545 1.805528 1.805528
8 Yes 3 28.191667 4.095000 6.898186 6.898186
9 Yes 4 30.609091 3.992727 5.150063 5.150063
10 Yes 5 29.305000 2.500000 2.263800 2.263800
定义我的错误栏功能，它接收数据并索引错误列以生成2xN数组：
In [256]:
def my_errorbar(*args, **kwargs):
data = kwargs['data']
errors = np.vstack([data['error_min'],
data['error_max']])
print(errors)
plt.errorbar(data[args[0]],
data[args[1]],
yerr=errors,
**kwargs);
使用map_dataframe进行呼叫（因为我的函数将数据作为kwarg获取）：
In [257]:
g = sns.FacetGrid(tips, col="smoker", size=5)
g.map_dataframe(my_errorbar, "size", "total_bill", marker="o")
[[ 2.7636 0.9190424 2.68044722 3.30313068 11.62080751
9.19436049]
[ 2.7636 0.9190424 2.68044722 3.30313068 11.62080751
9.19436049]]
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-257-dc8b35ec70ec> in <module>()
1 g = sns.FacetGrid(tips, col="smoker", size=5)
----> 2 g.map_dataframe(my_errorbar, "size", "total_bill", marker="o")
/Users/x/miniconda3/envs/default/lib/python3.4/site-packages/seaborn/axisgrid.py in map_dataframe(self, func, *args, **kwargs)
509
510 # Draw the plot
--> 511 self._facet_plot(func, ax, args, kwargs)
512
513 # Finalize the annotations and layout
/Users/x/miniconda3/envs/default/lib/python3.4/site-packages/seaborn/axisgrid.py in _facet_plot(self, func, ax, plot_args, plot_kwargs)
527
528 # Draw the plot
--> 529 func(*plot_args, **plot_kwargs)
530
531 # Sort out the supporting information
<ipython-input-256-62202c841233> in my_errorbar(*args, **kwargs)
9 data[args[1]],
10 yerr=errors,
---> 11 **kwargs);
12
13
/Users/x/miniconda3/envs/default/lib/python3.4/site-packages/matplotlib/pyplot.py in errorbar(x, y, yerr, xerr, fmt, ecolor, elinewidth, capsize, barsabove, lolims, uplims, xlolims, xuplims, errorevery, capthick, hold, **kwargs)
2764 barsabove=barsabove, lolims=lolims, uplims=uplims,
2765 xlolims=xlolims, xuplims=xuplims,
-> 2766 errorevery=errorevery, capthick=capthick, **kwargs)
2767 draw_if_interactive()
2768 finally:
/Users/x/miniconda3/envs/default/lib/python3.4/site-packages/matplotlib/axes/_axes.py in errorbar(self, x, y, yerr, xerr, fmt, ecolor, elinewidth, capsize, barsabove, lolims, uplims, xlolims, xuplims, errorevery, capthick, **kwargs)
2859
2860 if not barsabove and plot_line:
-> 2861 l0, = self.plot(x, y, fmt, **kwargs)
2862
2863 if ecolor is None:
/Users/x/miniconda3/envs/default/lib/python3.4/site-packages/matplotlib/axes/_axes.py in plot(self, *args, **kwargs)
1371 lines = []
1372
-> 1373 for line in self._get_lines(*args, **kwargs):
1374 self.add_line(line)
1375 lines.append(line)
/Users/x/miniconda3/envs/default/lib/python3.4/site-packages/matplotlib/axes/_base.py in _grab_next_args(self, *args, **kwargs)
302 return
303 if len(remaining) <= 3:
--> 304 for seg in self._plot_args(remaining, kwargs):
305 yield seg
306 return
/Users/x/miniconda3/envs/default/lib/python3.4/site-packages/matplotlib/axes/_base.py in _plot_args(self, tup, kwargs)
290 ncx, ncy = x.shape[1], y.shape[1]
291 for j in xrange(max(ncx, ncy)):
--> 292 seg = func(x[:, j % ncx], y[:, j % ncy], kw, kwargs)
293 ret.append(seg)
294 return ret
/Users/x/miniconda3/envs/default/lib/python3.4/site-packages/matplotlib/axes/_base.py in _makeline(self, x, y, kw, kwargs)
242 **kw
243 )
--> 244 self.set_lineprops(seg, **kwargs)
245 return seg
246
/Users/x/miniconda3/envs/default/lib/python3.4/site-packages/matplotlib/axes/_base.py in set_lineprops(self, line, **kwargs)
184 raise TypeError('There is no line property "%s"' % key)
185 func = getattr(line, funcName)
--> 186 func(val)
187
188 def set_patchprops(self, fill_poly, **kwargs):
/Users/x/miniconda3/envs/default/lib/python3.4/site-packages/matplotlib/lines.py in set_data(self, *args)
557 """
558 if len(args) == 1:
--> 559 x, y = args[0]
560 else:
561 x, y = args
ValueError: too many values to unpack (expected 2)
我不明白这里失败的原因。请注意，绘图函数获取某些内容，因为会生成第一个错误栏网格图。我假设我没有正确传递**kwargs字典。
一般情况下，如果tutorial for Seaborn包含一个或两个用户定义的绘图函数示例传递给map或map_dataframe，我会发现它真的很有用。
答案 0 :(得分：4)
这是@ mwaskom的答案，并且是一种享受（见评论）：
只需更改my_errorbar功能，即可弹出关键字dict中的data：
def my_errorbar(*args, **kwargs):
data = kwargs.pop('data')
errors = np.vstack([data['error_min'],
data['error_max']])
print(errors)
plt.errorbar(data[args[0]],
data[args[1]],
yerr=errors,
**kwargs);