How to plot a superimposed bar chart using matplotlib in python?

Question

I want to plot a bar chart or a histogram using matplotlib. I don\'t want a stacked bar plot, but a superimposed barplot of two lists of data, for instance I have the follow

Answer 1

Building on @Ffisegydd's answer, if your data is in a Pandas DataFrame, this should work nicely:

def overlapped_bar(df, show=False, width=0.9, alpha=.5,
                   title='', xlabel='', ylabel='', **plot_kwargs):
    """Like a stacked bar chart except bars on top of each other with transparency"""
    xlabel = xlabel or df.index.name
    N = len(df)
    M = len(df.columns)
    indices = np.arange(N)
    colors = ['steelblue', 'firebrick', 'darksage', 'goldenrod', 'gray'] * int(M / 5. + 1)
    for i, label, color in zip(range(M), df.columns, colors):
        kwargs = plot_kwargs
        kwargs.update({'color': color, 'label': label})
        plt.bar(indices, df[label], width=width, alpha=alpha if i else 1, **kwargs)
        plt.xticks(indices + .5 * width,
                   ['{}'.format(idx) for idx in df.index.values])
    plt.legend()
    plt.title(title)
    plt.xlabel(xlabel)
    plt.ylabel(ylabel)
    if show:
        plt.show()
    return plt.gcf()

And then in a python command line:

low = [1000.95, 1233.37, 1198.97, 1198.01, 1214.29, 1130.86, 1138.70, 1104.12, 1012.95, 1000.36]
high = [1184.53, 1523.48, 1521.05, 1517.88, 1519.88, 1414.98, 1419.34, 1415.13, 1182.70, 1165.17]
df = pd.DataFrame(np.matrix([high, low]).T, columns=['High', 'Low'],
                  index=pd.Index(['T%s' %i for i in range(len(high))],
                  name='Index'))
overlapped_bar(df, show=False)