使用Pandas从数据透视表绘图

Question

Let's say that I have the following pivot table (this is the one created in the documentation ):

In [8]: tuples = list(zip(*[['bar', 'bar', 'baz', 'baz',
...:                 'foo', 'foo', 'qux', 'qux'],
...:                ['one', 'two', 'one', 'two',
...:                 'one', 'two', 'one', 'two']]))
...: 

In [9]: index = MultiIndex.from_tuples(tuples, names=['first', 'second'])

In [10]: df = DataFrame(randn(8, 2), index=index, columns=['A', 'B'])

In [11]: df2 = df[:4]

In [12]: df2
Out[12]: 
                     A         B
first second                    
bar   one     0.721555 -0.706771
      two    -1.039575  0.271860
baz   one    -0.424972  0.567020
      two     0.276232 -1.087401

How can I use this table to plot both 'bar' and 'baz' on the same plot with axes (second, A) (ie I want to create a plot with the points (one, 0.72), (two, -1.039), (one, -0.42), (two, 0.276), where the first two points are plotted in a different color than the latter two).

I tried using

df2[[0]].plot() 

but this plots the points sequentially on the x-axis so that they are ordered ((bar,one), .721), ((bar,two), -1.039), etc, rather than having the two 'one' points and the two 'two' points share a vertical axis.

Answer 1

Ok, I figured it out. The key was unstacking the data first:

import matplotlib.pyplot as plt

t=df2.unstack(level=0)
plt.plot(t[[0]], color='red')
plt.plot(t[[1]], color='blue')
plt.xticks(range(2), ['one','two'], size='small')

plt.show()