pandas 在所有子图中绘制带有列的 DataFrame
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Plotting DataFrame with column in all subplots
提问by TomCho
Consider that I have a pandas DataFrame with 3 columns. I would to plot two of these columns as separate subplots and the other one should appear on both the other subplots.
考虑到我有一个包含 3 列的 Pandas DataFrame。我会将这些列中的两列绘制为单独的子图，而另一列应该出现在其他两个子图中。
To explain better, consider the example
为了更好地解释，考虑这个例子
x = np.linspace(0,10,5)
y1 = 2*x
y2 = 3*x
y3 = 4*x
df = pd.DataFrame(index=x, data=zip(*[y1,y2,y3]))
df.plot(subplots=True, layout=(1,3), ylim=[0,40])
This code displays
此代码显示
Which is close to what I want. But not exactly. I would like that plot to have only two subplots. One with columns 0 and 1, and the other with columns 0 and 2. As is comparing each column to another column. The closest I got was
这接近我想要的。但不完全是。我希望那个情节只有两个子情节。一个包含第 0 列和第 1 列，另一个包含第 0 列和第 2 列。将每一列与另一列进行比较。我得到的最接近的是
df[[1,2]].plot(subplots=True, layout=(1,2), ylim=[0,40])
plt.plot(df.index, df[0], label=0)
which gives me this picture, where column 0 only appears in the second subplot, and not on all of them:
这给了我这张图片，其中第 0 列仅出现在第二个子图中，而不是所有子图中：
Is there any way to do this? Preferably not going completely outside of pandas. I know I could just iterate through columns 1 and 2 and manually plot them with pyplot alongside column 0, but that's just too much code and I'd like to avoid that, if possible.
有没有办法做到这一点？最好不要完全离开Pandas。我知道我可以遍历第 1 列和第 2 列，并在第 0 列旁边使用 pyplot 手动绘制它们，但这只是代码太多，如果可能，我想避免这种情况。
采纳答案by Romain
Like this
像这样
ax = df[[1,2]].plot(subplots=True, layout=(1,2), ylim=[0,40])
for axe in ax[0]:
axe.plot(df.index, df[0])
