Barplot with log y-axis program syntax with matplotlib pyplot

Are you sure that is all your code does? Where does the code throw the error? During plotting? Because this works for me:

In [16]: import numpy as np
In [17]: x = np.arange(1,8, 1)
In [18]: y = np.exp(x)

In [20]: import matplotlib.pyplot as plt
In [21]: fig = plt.figure()
In [22]: ax = fig.add_subplot(111)
In [24]: ax.bar(x, y, log=1)
Out[24]: 
[<matplotlib.patches.Rectangle object at 0x3cb1550>,
 <matplotlib.patches.Rectangle object at 0x40598d0>,
 <matplotlib.patches.Rectangle object at 0x4059d10>,
 <matplotlib.patches.Rectangle object at 0x40681d0>,
 <matplotlib.patches.Rectangle object at 0x4068650>,
 <matplotlib.patches.Rectangle object at 0x4068ad0>,
 <matplotlib.patches.Rectangle object at 0x4068f50>]
In [25]: plt.show()

Here's the plot

As already suggested in the comments to Greg's answer, you're indeed seeing an issue that was fixed in matplotlib 1.3 by setting the default behavior to 'clip'. Upgrading to 1.3 fixes the issue for me.

Note that it doesn't seem to matter how you apply the log scale, whether as a keyword argument to bar or via set_yscale on the axis.

See also this answer to "Logarithmic y-axis bins in python" that suggests this workaround:

plt.yscale('log', nonposy='clip')

The error is raised due to the log = True statement in ax.bar(.... I'm unsure if this a matplotlib bug or it is being used in an unintended way. It can easily be fixed by removing the offending argument log=True.

This can be simply remedied by simply logging the y values yourself.

x_values = np.arange(1,8, 1)
y_values = np.exp(x_values)

log_y_values = np.log(y_values)

fig = plt.figure()
ax = fig.add_subplot(111)
ax.bar(x_values,log_y_values) #Insert log=True argument to reproduce error

Appropriate labels log(y) need to be adding to be clear it is the log values.