How to do a range bar graph in matplotlib?

Appetizer

Commented Code

As far as I know, the most direct way to do what you want requires that you directly draw your rectangles on the matplotlib canvas using the patches module of matplotlib

A simple implementation follows

import matplotlib.pyplot as plt
import matplotlib.patches as patches

def plot_rect(data, delta=0.4):
    """data is a dictionary, {"Label":(low,hi), ... }
    return a drawing that you can manipulate, show, save etc"""

    yspan = len(data)
    yplaces = [.5+i for i in range(yspan)]
    ylabels = sorted(data.keys())

    fig = plt.figure()
    ax = fig.add_subplot(111)
    ax.set_yticks(yplaces)
    ax.set_yticklabels(ylabels)
    ax.set_ylim((0,yspan))

    # later we'll need the min and max in the union of intervals
    low, hi =  data[ylabels[0]]
    for pos, label in zip(yplaces,ylabels):
        start, end = data[label]
        ax.add_patch(patches.Rectangle((start,pos-delta/2.0),end-start,delta))
        if start<low : low=start
        if end>hi : hi=end

    # little small trick, draw an invisible line so that the x axis
    # limits are automatically adjusted...
    ax.plot((low,hi),(0,0))

    # now get the limits as automatically computed
    xmin, xmax = ax.get_xlim()
    # and use them to draw the hlines in your example
    ax.hlines(range(1,yspan),xmin,xmax)
    # the vlines are simply the x grid lines
    ax.grid(axis='x')
    # eventually return what we have done
    return ax

# this is the main script, note that we have imported pyplot as plt

# the data, inspired by your example, 
data = {'A':(1901,1921),
        'B':(1917,1935),
        'C':(1929,1948),
        'D':(1943,1963),
        'E':(1957,1983),
        'F':(1975,1991),
        'G':(1989,2007)}

# call the function and give its result a name
ax = plot_rect(data)
# so that we can further manipulate it using the `axes` methods, e.g.
ax.set_xlabel('Whatever')
# finally save or show what we have
plt.show()

The result of our sufferings has been shown in the first paragraph of this post...

Addendum

Let's say that you feel that blue is a very dull color...

The patches you've placed in your drawing are accessible as a property (aptly named patches...) of the drawing and modifiable too, e.g.,

ax = plot_rect(data)
ax.set_xlabel('Whatever')
for rect in ax.patches:
    rect.set(facecolor=(0.9,0.9,0.2,1.0), # a tuple, RGBA
          edgecolor=(0.6,0.2,0.3,1.0),
          linewidth=3.0)
plt.show()

In my VH opinion, a custom plotting function should do the least indispensable to characterize the plot, as this kind of post-production is usually very easy in matplotlib.