Python 使用多索引绘制熊猫图
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Pandas Plotting with Multi-Index
提问by Reustonium
After performing a groupby.sum()on a DataFrameI'm having some trouble trying to create my intended plot.
在 agroupby.sum()上执行 a 后，DataFrame我在尝试创建我想要的情节时遇到了一些麻烦。
How can I create a subplot (kind='bar') for each Code, where the x-axis is the Monthand the bars are ColAand ColB?
如何kind='bar'为每个创建子图 ( ) Code，其中 x 轴是 the Month，条形图是ColAand ColB？
采纳答案by Reustonium
I found the unstack(level) method to work perfectly, which has the added benefit of not needing a priori knowledge about how many Codes there are.
我发现 unstack(level) 方法可以完美地工作，它的另一个好处是不需要关于有多少代码的先验知识。
df.unstack(level=0).plot(kind='bar', subplots=True)
回答by segmentationfault
Using the following DataFrame ...
使用以下数据帧...
# using pandas version 0.14.1
from pandas import DataFrame
import pandas as pd
import matplotlib.pyplot as plt
data = {'ColB': {('A', 4): 3.0,
('C', 2): 0.0,
('B', 4): 51.0,
('B', 1): 0.0,
('C', 3): 0.0,
('B', 2): 7.0,
('Code', 'Month'): '',
('A', 3): 5.0,
('C', 1): 0.0,
('C', 4): 0.0,
('B', 3): 12.0},
'ColA': {('A', 4): 66.0,
('C', 2): 5.0,
('B', 4): 125.0,
('B', 1): 5.0,
('C', 3): 41.0,
('B', 2): 52.0,
('Code', 'Month'): '',
('A', 3): 22.0,
('C', 1): 14.0,
('C', 4): 51.0,
('B', 3): 122.0}}
df = DataFrame(data)
... you can plot the following (using cross-section):
...您可以绘制以下内容（使用横截面）：
f, a = plt.subplots(3,1)
df.xs('A').plot(kind='bar',ax=a[0])
df.xs('B').plot(kind='bar',ax=a[1])
df.xs('C').plot(kind='bar',ax=a[2])
One for A, one for B and one for C, x-axis: 'Month', the bars are ColA and ColB. Maybe this is what you are looking for.
一个用于 A，一个用于 B，一个用于 C，x 轴：“月”，条形是 ColA 和 ColB。也许这就是你正在寻找的。
