+--- -----+------------+-------------+----------+------------+-----------+
|avg_views| avg_orders | max_views   |max_orders| min_views  |min_orders |
+---------+------------+-------------+----------+------------+-----------+
| 23       | 123       |   135       | 500      |    3       |    1      |
+---------+------------+-------------+----------+------------+-----------+

plt.figure(figsize=(13,7), dpi=300)

groups = [[23,135,3],
      [123,500,1]]
group_labels = ["views", "orders"]
num_items = len(group_labels)
ind = np.arange(num_items)
margin = 0.05
width = (1.-2.*margin)/num_items

s = plt.subplot(1,1,1)
for num, vals in enumerate(groups):
    print "plotting: ", vals
    # The position of the xdata must be calculated for each of the two data series
    xdata = ind+margin+(num*width)
    # Removing the "align=center" feature will left align graphs, which is what
    # this method of calculating positions assumes
    gene_rects = plt.bar(xdata, vals, width)
s.set_xticks(ind+0.5)
s.set_xticklabels(group_labels)

import pandas as pd

groups = [[23,135,3], [123,500,1]]
group_labels = ['views', 'orders']

# Convert data to pandas DataFrame.
df = pd.DataFrame(groups, index=group_labels).T

# Plot.
pd.concat(
    [df.mean().rename('average'), df.min().rename('min'),
     df.max().rename('max')],
    axis=1).plot.bar()