根据pandas/matplotlib中的类绘制直方图 [英] Plotting histograms against classes in pandas / matplotlib

问题描述

是否有惯用的方式绘制两个类的要素直方图? 在大熊猫中，我基本上想要

Is there a idiomatic way to plot the histogram of a feature for two classes? In pandas, I basically want

df.feature[df.class == 0].hist()
df.feature[df.class == 1].hist()

要在同一个情节中.我能做

To be in the same plot. I could do

df.feature.hist(by=df.class)

但这给了我两个独立的情节.

but that gives me two separate plots.

这似乎是一项常见的任务，所以我想应该有一种惯用的方式来做到这一点.当然，我可以手动操作直方图以使其彼此相邻，但是通常熊猫都做得很好.

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.

我基本上希望在一行熊猫中使用这个matplotlib示例: http://matplotlib.org/examples/pylab_examples/barchart_demo .html

Basically I want this matplotlib example in one line of pandas: http://matplotlib.org/examples/pylab_examples/barchart_demo.html

我以为我错过了一些东西，但也许还没有(可能).

I thought I was missing something, but maybe it is not possible (yet).

推荐答案

df.groupby("class").feature.hist()怎么样?要查看重叠的分布，您可能需要将alpha=0.4传递给hist().另外，我很想使用内核密度估计值代替df.groupby("class").feature.plot(kind='kde')的直方图.

How about df.groupby("class").feature.hist()? To see overlapping distributions you'll probably need to pass alpha=0.4 to hist(). Alternatively, I'd be tempted to use a kernel density estimate instead of a histogram with df.groupby("class").feature.plot(kind='kde').

作为示例，我使用以下命令绘制了虹膜数据集的类:

As an example, I plotted the iris dataset's classes using:

iris.groupby("Name").PetalWidth.plot(kind='kde', ax=axs[1])
iris.groupby("Name").PetalWidth.hist(alpha=0.4, ax=axs[0])

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