pandas 使用子图的熊猫条形图
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Pandas Bar Plot using Subplots
提问by Charanjit Pabla
I am using pandas to create bar plot. Here is an example:
我正在使用Pandas来创建条形图。下面是一个例子：
df=pd.DataFrame(np.random.rand(10, 4), columns=['a', 'b', 'c', 'd'])
df.plot(kind='bar')
I want to plot two subplots within a figure and have a and b on one bar plot and c and d on another. How do I go about this?
我想在一个图中绘制两个子图，并在一个条形图中有 a 和 b，在另一个条形图中有 c 和 d。我该怎么做？
Further, if I wanted to include the two subplots with another subplot but not created by pandas, how to do that? So a 3x1 figure where two of the subplots are from the data frame using pandas and one without using pandas.
此外，如果我想将两个子图与另一个子图一起包含但不是由Pandas创建的，该怎么做？所以一个 3x1 的图，其中两个子图来自使用Pandas的数据框，一个不使用Pandas。
Taking a second attempt at this but with some modifications.
对此进行第二次尝试，但进行了一些修改。
df=pd.DataFrame(np.random.rand(10, 4), columns=['a', 'b', 'c', 'd'])
x=[1,2,3,4,5]
y=[1,4,9,16,25]
fig, axes = plt.subplots(figsize=(8,8),nrows=2, ncols=2)
ax1=plt.subplot(2,2,1)
plt.plot(x,y)
#ax2=plt.subplot(2,2,2)
df["b"].plot(ax=axes[0,1], kind='bar', grid=True)
df["c"].plot(ax=axes[1,0], kind='bar', grid=True)
df["d"].plot(ax=axes[1,1], kind='bar', grid=True)
ax1.grid(True)
ax1.set_ylabel('Test')
ax1.set_xlabel('Test2')
#ax2.set_ylabel('Test')
How do I add axes labels for the bar plots in my subplots? Notice I have commented out ax2=plt.subplot(2,2,2) as I was testing this but this erases the bar plot completely and add the labels. Why does it do that and how can I get around this? Below is the output with the ax2... un-commented.
如何为子图中的条形图添加轴标签？请注意，我在测试时已注释掉 ax2=plt.subplot(2,2,2)，但这会完全擦除条形图并添加标签。为什么会这样，我该如何解决这个问题？下面是带有 ax2... 未注释的输出。
回答by rpanai
You can start to play from this:
你可以从这个开始玩：
%matplotlib inline
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
df=pd.DataFrame(np.random.rand(10, 4), columns=['a', 'b', 'c', 'd'])
fig, axes = plt.subplots(nrows=1, ncols=2)
df[["a","b"]].plot(ax=axes[0],kind='bar')
df[["c", "d"]].plot(ax=axes[1], kind='bar');
Then you can have a look at this
然后你可以看看这个
