如何在 1 个图中组合 2 个数据框直方图? [英] How to combine 2 dataframe histograms in 1 plot?

问题描述

我想使用显示数据框中所有直方图的代码.那将是 df.hist(bins=10).但是，我想添加另一个显示CDF的直方图 df_hist = df.hist(cumulative = True，bins = 100，density = 1，histt​​ype ="step")

I would like to use a code that shows all histograms in a dataframe. That will be df.hist(bins=10). However, I would like to add another histograms which shows CDF df_hist=df.hist(cumulative=True,bins=100,density=1,histtype="step")

我尝试使用 fig = plt.figure()和 plt.subplot(211).但是，此df.hist实际上是pandas函数的一部分，而不是matplotlib函数的一部分.我还尝试设置轴，并向每个直方图添加ax = ax1和ax2选项，但这没有用.

I tried separating their matplotlib axes by using fig=plt.figure() and plt.subplot(211). But this df.hist is actually part of pandas function, not matplotlib function. I also tried setting axes and adding ax=ax1 and ax2 options to each histogram but it didn't work.

如何将这些直方图组合在一起?有什么帮助吗?

How can I combine these histograms together? Any help?

我想要组合的直方图是这样的.我想并排展示它们，或将第二个放在第一个的顶端.对不起，我不在乎让它们看起来不错.

Histograms that I want to combine are like these. I want to show them side by side or put the second one on tip of the first one. Sorry that I didn't care to make them look good.

推荐答案

可以将它们绘制在一起:

It is possible to draw them together:

# toy data frame
df = pd.DataFrame(np.random.normal(0,1,(100,20)))

# draw hist
fig, axes = plt.subplots(5,4, figsize=(16,10))
df.plot(kind='hist', subplots=True, ax=axes, alpha=0.5)

# clone axes so they have different scales
ax_new = [ax.twinx() for ax in axes.flatten()]
df.plot(kind='kde', ax=ax_new, subplots=True)
plt.show()

输出:

还可以并排绘制它们.例如

It's also possible to draw them side-by-side. For example

fig, axes = plt.subplots(10,4, figsize=(16,10))
hist_axes = axes.flatten()[:20]
df.plot(kind='hist', subplots=True, ax=hist_axes, alpha=0.5)

kde_axes = axes.flatten()[20:]
df.plot(kind='kde', subplots=True, ax=kde_axes, alpha=0.5)

将在kde上绘制历史记录.

will plot hist on top of kde.

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