# Plot logarithmic axes with matplotlib in python

You can use the `Axes.set_yscale`

method. That allows you to change the scale after the `Axes`

object is created. That would also allow you to build a control to let the user pick the scale if you needed to.

The relevant line to add is:

`ax.set_yscale('log')`

You can use `'linear'`

to switch back to a linear scale. Here's what your code would look like:

`import pylabimport matplotlib.pyplot as plta = [pow(10, i) for i in range(10)]fig = plt.figure()ax = fig.add_subplot(2, 1, 1)line, = ax.plot(a, color='blue', lw=2)ax.set_yscale('log')pylab.show()`

First of all, it's not very tidy to mix `pylab`

and `pyplot`

code. What's more, pyplot style is preferred over using pylab.

Here is a slightly cleaned up code, using only `pyplot`

functions:

`from matplotlib import pyplota = [ pow(10,i) for i in range(10) ]pyplot.subplot(2,1,1)pyplot.plot(a, color='blue', lw=2)pyplot.yscale('log')pyplot.show()`

The relevant function is `pyplot.yscale()`

. If you use the object-oriented version, replace it by the method `Axes.set_yscale()`

. Remember that you can also change the scale of X axis, using `pyplot.xscale()`

(or `Axes.set_xscale()`

).

Check my question What is the difference between ‘log’ and ‘symlog’? to see a few examples of the graph scales that matplotlib offers.

You simply need to use semilogy instead of plot:

`from pylab import *import matplotlib.pyplot as pyplota = [ pow(10,i) for i in range(10) ]fig = pyplot.figure()ax = fig.add_subplot(2,1,1)line, = ax.semilogy(a, color='blue', lw=2)show()`