我的数据集如下：
train['SalePrice'].head()
0 208500
1 181500
2 223500
3 140000
4 250000
Name: SalePrice, dtype: int64
我想使用seaborn.distplot（train [＆＃39; SalePrice＆＃39;]）绘制它，但会显示以下错误。
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-94-00861be8ee63> in <module>()
1 #SalePrice
----> 2 sns.distplot(train['SalePrice'])
3 #train['SalePrice'].head()
/usr/lib/python3/dist-packages/seaborn/distributions.py in distplot(a, bins, hist, kde, rug, fit, hist_kws, kde_kws, rug_kws, fit_kws, color, vertical, norm_hist, axlabel, label, ax)
210 hist_color = hist_kws.pop("color", color)
211 ax.hist(a, bins, orientation=orientation,
--> 212 color=hist_color, **hist_kws)
213 if hist_color != color:
214 hist_kws["color"] = hist_color
/usr/lib/python3/dist-packages/matplotlib/__init__.py in inner(ax, *args, **kwargs)
1812 warnings.warn(msg % (label_namer, func.__name__),
1813 RuntimeWarning, stacklevel=2)
-> 1814 return func(ax, *args, **kwargs)
1815 pre_doc = inner.__doc__
1816 if pre_doc is None:
/usr/lib/python3/dist-packages/matplotlib/axes/_axes.py in hist(self, x, bins, range, normed, weights, cumulative, bottom, histtype, align, orientation, rwidth, log, color, label, stacked, **kwargs)
6008 # this will automatically overwrite bins,
6009 # so that each histogram uses the same bins
-> 6010 m, bins = np.histogram(x[i], bins, weights=w[i], **hist_kwargs)
6011 m = m.astype(float) # causes problems later if it's an int
6012 if mlast is None:
/usr/local/lib/python3.5/dist-packages/numpy/lib/function_base.py in histogram(a, bins, range, normed, weights, density)
727
728 # Initialize empty histogram
--> 729 n = np.zeros(bins, ntype)
730 # Pre-compute histogram scaling factor
731 norm = bins / (mx - mn)
TypeError: 'numpy.float64' object cannot be interpreted as an integer
我不明白这里的类型错误是什么。 Python版本：3.5.2 Seaborn版本：0.6.0。