In [1]:

    

import math
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator
%matplotlib inline


    

In [2]:

    

ts2017 = pd.Series([1,2,3], index=['A', 'B', 'C'])
ts2016 = pd.Series([4,5,6], index=['C', 'B', 'A'])
ts2015 = pd.Series([5,4,3], index=['C', 'B', 'A'])


    

In [3]:

    

df2017 = ts2017.to_frame()
df2017 = df2017.rename(columns={0:2017})


    

In [4]:

    

df2016 = ts2016.to_frame()
df2016 = df2016.rename(columns={0:2016})


    

In [5]:

    

df2015 = ts2015.to_frame()
df2015 = df2015.rename(columns={0:2015})


    

In [6]:

    

df = pd.concat([df2017, df2016, df2015], axis=1, join_axes=[df2017.index])
df =df.transpose()
df


    

    
Out[6]:







  

    

      

      
A
      
B
      
C
    
  
  

    

      
2017
      
1
      
2
      
3
    
    

      
2016
      
6
      
5
      
4
    
    

      
2015
      
3
      
4
      
5
    
  

In [7]:

    

ax = df.plot(linestyle='--', marker='o')

# scale to the maximum tick value thanks to MaxNLocator 
ax.xaxis.set_major_locator(MaxNLocator(integer=True))