Can't get un-stacked bar plot in python pandas
Question: This is weird. I just can't seem to get unstacked bar plot in python pandas
(unlike pandas official guide). The bars just seem to be overlapped, instead
of placed sideways. Any clue why it would be?

    
    
    df.plot(kind='bar',stacked=False, figsize=(20,15), alpha=0.4)
    

Here is the link to the image: ![enter image description
here](http://i.stack.imgur.com/2UAb1.png)

and here is a sample df

    
    
                    OLS     Ridge     Lasso        EN
    BN         0.008935  0.013937  0.000000  0.000000
    BO         0.037947  0.034341  0.021778  0.021771
    BP         0.205764  0.190278  0.184766  0.179000
    CB         0.302772  0.106399  0.161487  0.076948
    CD         0.464572  0.378660  0.424983  0.401792
    CF         0.062425  0.006078  0.000000 -0.000000
    CL        -0.005794  0.002631  0.000000  0.001082
    CN         0.012761  0.011331  0.010272  0.010476
    


Answer: Ok. So now I have to ask what version of pandas you're on. When I run:

    
    
    from matplotlib import pyplot as plt
    import pandas
    try:
        from io import StringIO
    except:
        from StringIO import StringIO
    
    data = StringIO("""\
                    OLS     Ridge     Lasso        EN
    BN         0.008935  0.013937  0.000000  0.000000
    BO         0.037947  0.034341  0.021778  0.021771
    BP         0.205764  0.190278  0.184766  0.179000
    CB         0.302772  0.106399  0.161487  0.076948
    CD         0.464572  0.378660  0.424983  0.401792
    CF         0.062425  0.006078  0.000000 -0.000000
    CL        -0.005794  0.002631  0.000000  0.001082
    CN         0.012761  0.011331  0.010272  0.010476
    """)
    
    df = pandas.read_csv(data, sep='\s+')
    fig, axes = plt.subplots(nrows=2, figsize=(6, 10))
    df.plot(kind='bar', stacked=False, alpha=0.4, ax=axes[0])
    df.plot(kind='bar', stacked=True, alpha=0.4, ax=axes[1])
    for ax in axes:
        ax.set_ylim(bottom=0)
    

I get: ![enter image description here](http://i.stack.imgur.com/iilW9.png)

I'm on pandas 0.13 via (ana)conda

