pandas seaborn:选择的 KDE 带宽为 0。无法估计密度
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seaborn: Selected KDE bandwidth is 0. Cannot estimate density
提问by SaadH
import pandas as pd
import seaborn as sns
ser_test = pd.Series([1,0,1,4,6,0,6,5,1,3,2,5,1])
sns.kdeplot(ser_test, cumulative=True)
The above code generates the following CDF graph:
上面的代码生成以下 CDF 图:
But when the elements of the series are modified to:
但是当系列的元素被修改为:
ser_test = pd.Series([1,0,1,1,6,0,6,1,1,0,2,1,1])
sns.kdeplot(ser_test, cumulative=True)
I get the following error:
我收到以下错误:
ValueError: could not convert string to float: 'scott'
RuntimeError: Selected KDE bandwidth is 0. Cannot estimate density.
ValueError: 无法将字符串转换为浮点数:'scott'
运行时错误:选定的 KDE 带宽为 0。无法估计密度。
What does this error mean and how can I resolve it to generate a CDF (even if it is very skewed).
这个错误是什么意思,我如何解决它以生成 CDF(即使它非常倾斜)。
Edit:I am using seaborn version 0.9.0
编辑:我使用的是 seaborn 0.9.0 版
The complete trace is below:
完整的跟踪如下:
ValueError: could not convert string to float: 'scott'
During handling of the above exception, another exception occurred:
RuntimeError Traceback (most recent call last)
<ipython-input-93-7cee594b4526> in <module>
1 ser_test = pd.Series([1,0,1,1,6,0,6,1,1,0,2,1,1])
----> 2 sns.kdeplot(ser_test, cumulative=True)
~/.local/lib/python3.5/site-packages/seaborn/distributions.py in kdeplot(data, data2, shade, vertical, kernel, bw, gridsize, cut, clip, legend, cumulative, shade_lowest, cbar, cbar_ax, cbar_kws, ax, **kwargs)
689 ax = _univariate_kdeplot(data, shade, vertical, kernel, bw,
690 gridsize, cut, clip, legend, ax,
--> 691 cumulative=cumulative, **kwargs)
692
693 return ax
~/.local/lib/python3.5/site-packages/seaborn/distributions.py in _univariate_kdeplot(data, shade, vertical, kernel, bw, gridsize, cut, clip, legend, ax, cumulative, **kwargs)
281 x, y = _statsmodels_univariate_kde(data, kernel, bw,
282 gridsize, cut, clip,
--> 283 cumulative=cumulative)
284 else:
285 # Fall back to scipy if missing statsmodels
~/.local/lib/python3.5/site-packages/seaborn/distributions.py in _statsmodels_univariate_kde(data, kernel, bw, gridsize, cut, clip, cumulative)
353 fft = kernel == "gau"
354 kde = smnp.KDEUnivariate(data)
--> 355 kde.fit(kernel, bw, fft, gridsize=gridsize, cut=cut, clip=clip)
356 if cumulative:
357 grid, y = kde.support, kde.cdf
~/.local/lib/python3.5/site-packages/statsmodels/nonparametric/kde.py in fit(self, kernel, bw, fft, weights, gridsize, adjust, cut, clip)
138 density, grid, bw = kdensityfft(endog, kernel=kernel, bw=bw,
139 adjust=adjust, weights=weights, gridsize=gridsize,
--> 140 clip=clip, cut=cut)
141 else:
142 density, grid, bw = kdensity(endog, kernel=kernel, bw=bw,
~/.local/lib/python3.5/site-packages/statsmodels/nonparametric/kde.py in kdensityfft(X, kernel, bw, weights, gridsize, adjust, clip, cut, retgrid)
451 bw = float(bw)
452 except:
--> 453 bw = bandwidths.select_bandwidth(X, bw, kern) # will cross-val fit this pattern?
454 bw *= adjust
455
~/.local/lib/python3.5/site-packages/statsmodels/nonparametric/bandwidths.py in select_bandwidth(x, bw, kernel)
172 # eventually this can fall back on another selection criterion.
173 err = "Selected KDE bandwidth is 0. Cannot estimate density."
--> 174 raise RuntimeError(err)
175 else:
176 return bandwidth
RuntimeError: Selected KDE bandwidth is 0. Cannot estimate density.
回答by Josh Friedlander
What's going on here is that Seaborn (or rather, the library it relies on to calculate the KDE - scipy or statsmodels) isn't managing to figure out the "bandwidth", a scaling parameter used in the calculation. You can pass it manually. I played with a few values and found 1.5 gave a graph at the same scale as your previous:
这里发生的事情是 Seaborn(或者更确切地说,它依赖于计算 KDE-scipy 或 statsmodels 的库)没有设法找出“带宽”,这是计算中使用的缩放参数。您可以手动传递它。我玩了几个值,发现 1.5 给出了一个与你之前相同比例的图表:
sns.kdeplot(ser_test, cumulative=True, bw=1.5)
See also here. Worth installing statsmodels
if you don't have it.
另请参见此处。statsmodels
如果你没有它,值得安装。
回答by Jakub Maly
pip uninstall statsmodels
solved a similar problem with the same error.
pip uninstall statsmodels
用同样的错误解决了类似的问题。
回答by user108569
if you don't want to wait for the seaborn git update to get released in a stable version, you can try one of the solutions in the issue page. specifically henrymartin1's suggestion to try manually passing in a small bandwidth inside a try/catch block (suggested by ahartikainen) which grabs the text of this specific error (so other errors still get raised):
如果您不想等待 seaborn git 更新以稳定版本发布,您可以尝试问题页面中的解决方案之一。特别是 henrymartin1 的建议,即尝试在 try/catch 块(由 ahartikainen 建议)中手动传入一个小带宽,该块获取此特定错误的文本(因此仍会引发其他错误):
try:
sns.distplot(df)
except RuntimeError as re:
if str(re).startswith("Selected KDE bandwidth is 0. Cannot estimate density."):
sns.distplot(df, kde_kws={'bw': 0.1})
else:
raise re
This worked for me.
这对我有用。