pandas 如何在同一图上显示条形图和折线图
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How to show a bar and line graph on the same plot
提问by user2546580
I am unable to show a bar and line graph on the same plot. Example code:
我无法在同一个图上显示条形图和折线图。示例代码：
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
Df = pd.DataFrame(data=np.random.randn(10,4), index=pd.DatetimeIndex(start='2005', freq='M', periods=10), columns=['A','B','C','D'])
fig = plt.figure()
ax = fig.add_subplot(111)
Df[['A','B']].plot(kind='bar', ax=ax)
Df[['C','D']].plot(ax=ax, color=['r', 'c'])
回答by Michal
You can also try this:
你也可以试试这个：
fig = plt.figure()
ax = DF['A','B'].plot(kind="bar");plt.xticks(rotation=0)
ax2 = ax.twinx()
ax2.plot(ax.get_xticks(),DF['C','D'],marker='o')
回答by xpt
I wanted to know as well, however all existing answers are not for showing bar and line graph on the sameplot, but on different axis instead.
我也想知道，但是所有现有的答案都不是为了在同一个图上显示条形图和折线图，而是在不同的轴上。
so I looked for the answer myself and have found an example that is working -- Plot Pandas DataFrame as Bar and Line on the same one chart. I can confirm that it works.
所以我自己寻找答案并找到了一个有效的例子 -在同一个图表上将 Pandas DataFrame 绘制为条形图和线形图。我可以确认它有效。
What baffled me was that, the almost same code works therebut does not work here. I.e., I copied the OP's code and can verify that it is not working as expected.
让我感到困惑的是，几乎相同的代码在那里工作，但在这里不起作用。即，我复制了 OP 的代码并且可以验证它没有按预期工作。
The only thing I could think of is to add the index column to Df[['A','B']]and Df[['C','D']], but I don't know how since the index column doesn't have a name for me to add.
我唯一能想到的就是将索引列添加到Df[['A','B']]and Df[['C','D']]，但我不知道如何，因为索引列没有名称供我添加。
Today, I realize that even I can make it works, the real problem is that Df[['A','B']]gives a grouped (clustered) bar chart, but grouped (clustered) linechart is not supported.
今天，我意识到即使我可以让它工作，真正的问题是Df[['A','B']]给出了一个分组（集群）条形图，但不支持分组（集群）折线图。
回答by moenad
You can do something like that, both on the same figure:
你可以在同一张图上做类似的事情：
In [4]: Df = pd.DataFrame(data=np.random.randn(10,4), index=pd.DatetimeIndex(start='2005', freq='M', periods=10), columns=['A','B','C','D'])
In [5]: fig, ax = plt.subplots(2, 1) # you can pass sharex=True, sharey=True if you want to share axes.
In [6]: Df[['A','B']].plot(kind='bar', ax=ax[0])
Out[6]: <matplotlib.axes.AxesSubplot at 0x10cf011d0>
In [7]: Df[['C','D']].plot(color=['r', 'c'], ax=ax[1])
Out[7]: <matplotlib.axes.AxesSubplot at 0x10a656ed0>
