根据 Pandas / matplotlib 中的类绘制直方图
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Plotting histograms against classes in pandas / matplotlib
提问by Andreas Mueller
Is there a idiomatic way to plot the histogram of a feature for two classes? In pandas, I basically want
有没有一种惯用的方法来绘制两个类的特征的直方图？在Pandas中，我基本上想要
df.feature[df.class == 0].hist()
df.feature[df.class == 1].hist()
To be in the same plot. I could do
要在同一个情节。我可以
df.feature.hist(by=df.class)
but that gives me two separate plots.
但这给了我两个不同的情节。
This seems to be a common task so I would imagine there to be an idiomatic way to do this. Of course I could manipulate the histograms manually to fit next to each other but usually pandas does that quite nicely.
这似乎是一项常见的任务，所以我想有一种惯用的方法来做到这一点。当然，我可以手动操作直方图以使其彼此相邻，但通常Pandas可以很好地做到这一点。
Basically I want this matplotlib example in one line of pandas: http://matplotlib.org/examples/pylab_examples/barchart_demo.html
基本上我想在一行Pandas中使用这个 matplotlib 示例：http: //matplotlib.org/examples/pylab_examples/barchart_demo.html
I thought I was missing something, but maybe it is not possible (yet).
我以为我错过了一些东西，但也许这是不可能的（目前）。
采纳答案by jmz
How about df.groupby("class").feature.hist()? To see overlapping distributions you'll probably need to pass alpha=0.4to hist(). Alternatively, I'd be tempted to use a kernel density estimate instead of a histogram with df.groupby("class").feature.plot(kind='kde').
怎么样df.groupby("class").feature.hist()？要查看重叠你可能需要通过发行alpha=0.4来hist()。或者，我很想使用核密度估计而不是带有df.groupby("class").feature.plot(kind='kde').
As an example, I plotted the iris dataset's classes using:
例如，我使用以下方法绘制了 iris 数据集的类：
iris.groupby("Name").PetalWidth.plot(kind='kde', ax=axs[1])
iris.groupby("Name").PetalWidth.hist(alpha=0.4, ax=axs[0])
