Plot logarithmic axes with matplotlib in python Plot logarithmic axes with matplotlib in python python python

# 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()`` 