生成单元素序列的直方图时，Seaborn distplot错误

Question

当我使用seaborn的distplot（在0.7.1中）可视化直方图时，如果输入系列只包含一个元素，则会出错。换句话说，像是

import numpy as np
import seaborn as sns

num_elements = 1000
sns.distplot(np.random.normal(10, 1, num_elements))

效果很好但是如果我将num_elements设置为1，我会收到以下错误：

In [8]: num_elements = 1

In [9]: sns.distplot(np.random.normal(10, 1, num_elements))
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-9-35e3f8293582> in <module>()
----> 1 sns.distplot(np.random.normal(10, 1, num_elements))

/usr/local/lib/python2.7/site-packages/seaborn/distributions.pyc in distplot(a, bins, hist, kde, rug, fit, hist_kws, kde_kws, rug_kws, fit_kws, color, vertical, norm_hist, axlabel, label, ax)
    207     if hist:
    208         if bins is None:
--> 209             bins = min(_freedman_diaconis_bins(a), 50)
    210         hist_kws.setdefault("alpha", 0.4)
    211         hist_kws.setdefault("normed", norm_hist)

/usr/local/lib/python2.7/site-packages/seaborn/distributions.pyc in _freedman_diaconis_bins(a)
     28     # From http://stats.stackexchange.com/questions/798/
     29     a = np.asarray(a)
---> 30     h = 2 * iqr(a) / (len(a) ** (1 / 3))
     31     # fall back to sqrt(a) bins if iqr is 0
     32     if h == 0:

TypeError: len() of unsized object

稍微戳了一下源后，我发现我可以通过指定bin的数量来避免这个错误。但这让我又接触到了另一个：

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-10-6e6569de737a> in <module>()
----> 1 sns.distplot(np.random.normal(10, 1, num_elements), bins=10)

/usr/local/lib/python2.7/site-packages/seaborn/distributions.pyc in distplot(a, bins, hist, kde, rug, fit, hist_kws, kde_kws, rug_kws, fit_kws, c\olor, vertical, norm_hist, axlabel, label, ax)
    213         hist_color = hist_kws.pop("color", color)
    214         ax.hist(a, bins, orientation=orientation,
--> 215                 color=hist_color, **hist_kws)
    216         if hist_color != color:
    217             hist_kws["color"] = hist_color

/usr/local/lib/python2.7/site-packages/matplotlib/__init__.pyc in inner(ax, *args, **kwargs)
   1817                     warnings.warn(msg % (label_namer, func.__name__),
   1818                                   RuntimeWarning, stacklevel=2)
-> 1819             return func(ax, *args, **kwargs)
   1820         pre_doc = inner.__doc__
   1821         if pre_doc is None:

/usr/local/lib/python2.7/site-packages/matplotlib/axes/_axes.pyc in hist(self, x, bins, range, normed, weights, cumulative, bottom, histtype, align, orientation, rwidth, log, color, label, stacked, **kwargs)
   5933             x = np.array([[]])
   5934         else:
-> 5935             x = _normalize_input(x, 'x')
   5936         nx = len(x)  # number of datasets
   5937

/usr/local/lib/python2.7/site-packages/matplotlib/axes/_axes.pyc in _normalize_input(inp, ename)
   5875                 else:
   5876                     raise ValueError(
-> 5877                         "{ename} must be 1D or 2D".format(ename=ename))
   5878                 if inp.shape[1] < inp.shape[0]:
   5879                     warnings.warn(

ValueError: x must be 1D or 2D

这里发生了什么？是否有一些解决方法可以用来强制seaborn为这个单个元素系列绘制直方图？对于上下文，我需要这个，因为我在共享轴上绘制多个直方图，描述不同的条件。在某些情况下，在这种情况下可能只有一个元素，但我应该只能绘制一个条形图！

Answer 1

当数组长度为1时，您可以通过复制值来欺骗seaborn：

rs = np.random.RandomState(0)
num_elements = 1
x = rs.normal(10, 1, num_elements)
sns.distplot(np.r_[x, x], kde=False, norm_hist=True)

或者如果你不需要seaborn提供的好吃的东西（大多数对单个元素没有意义），只需使用matplotlib或pandas：

plt.hist(x, bins=1)

pd.Series(x).hist(bins=1);