Bar charts are often used to present experimental data in scientific papers. Let's make a chart with bars that represent the average value of some experimental data and add error bars to represent the standard deviation:
import numpy
import matplotlib.pyplot as plt
# Define experimental data
cluster1_data = numpy.array([9.7, 3.2])
cluster1_x = numpy.array([2,4])
cluster1_error = numpy.array([1.3, 0.52])
cluster2_data = numpy.array([6.8, 7.3])
cluster2_x = numpy.array([8,10])
cluster2_error = numpy.array([0.72, 0.97])
# Join data arrays for plotting
data = numpy.concatenate([cluster1_data, cluster2_data])
bar_centers = numpy.concatenate([cluster1_x, cluster2_x])
errors = numpy.concatenate([cluster1_error, cluster2_error])
# Plot
fig = plt.figure(figsize=(5,4)) # size in inches
plt.bar(bar_centers, data, yerr=errors,
width=2.0, align='center', color='white', ecolor='black')
plt.ylabel('outcome')
plt.text(4, 4, '*', fontsize=14)
# Label ticks...