How to create broken vertical bar graphs in matplo

I'd like to create a broken vertical bar graph in matplotlib.

To give a better idea of the result I'm after, I put an example together with Balsamiq:

I've had a look at the matpltolib docs and examples but I can't seem to find the appropriate chart type to use. The only thing that looks remotely similar is the boxplot but this isn't what I need.

I'd rather not have to draw the graph manually with graphics primitive.
I can massage the data into shape as needed.

PS: If you know of a good library that does this in another language (javascript, for example), I'd be grateful for the pointer too.

It sounds like you have a few series of start datetimes and stop datetimes.

In that case, just use bar to plot things, and tell matplotlib that the axes are dates.

To get the times, you can exploit the fact that matplotlib's internal date format is a float where each integer corresponds to 0:00 of that day. Therefore, to get the times, we can just do times = dates % 1.

As an example (90% of this is generating and manipulating dates. The plotting is just a single call to bar.):

import datetime as dt
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl

def main():
    start, stop = dt.datetime(2012,3,1), dt.datetime(2012,4,1)

    fig, ax = plt.subplots()
    for color in ['blue', 'red', 'green']:
        starts, stops = generate_data(start, stop)
        plot_durations(starts, stops, ax, facecolor=color, alpha=0.5)
    plt.show()

def plot_durations(starts, stops, ax=None, **kwargs):
    if ax is None:
        ax = plt.gca()
    # Make the default alignment center, unless specified otherwise
    kwargs['align'] = kwargs.get('align', 'center')

    # Convert things to matplotlib's internal date format...
    starts, stops = mpl.dates.date2num(starts), mpl.dates.date2num(stops)

    # Break things into start days and start times 
    start_times = starts % 1
    start_days = starts - start_times
    durations = stops - starts
    start_times += int(starts[0]) # So that we have a valid date...

    # Plot the bars
    artist = ax.bar(start_days, durations, bottom=start_times, **kwargs)

    # Tell matplotlib to treat the axes as dates...
    ax.xaxis_date()
    ax.yaxis_date()
    ax.figure.autofmt_xdate()
    return artist

def generate_data(start, stop):
    """Generate some random data..."""
    # Make a series of events 1 day apart
    starts = mpl.dates.drange(start, stop, dt.timedelta(days=1))

    # Vary the datetimes so that they occur at random times
    # Remember, 1.0 is equivalent to 1 day in this case...
    starts += np.random.random(starts.size)

    # Make some random stopping times...
    stops = starts + 0.2 * np.random.random(starts.size)

    # Convert back to datetime objects...
    return mpl.dates.num2date(starts), mpl.dates.num2date(stops)

if __name__ == '__main__':
    main()

On a side note, for events that start on one day and end on the next, this will extend the y-axis into the next day. You can handle it in other ways if you prefer, but I think this is the simplest option.