# Plot logarithmic axes with matplotlib in 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. Heres what your code would look like:

```
import pylab
import matplotlib.pyplot as plt
a = [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, its not very tidy to mix `pylab`

and `pyplot`

code. Whats more, pyplot style is preferred over using pylab.

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

functions:

```
from matplotlib import pyplot
a = [ 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.

#### Plot logarithmic axes with matplotlib in python

You simply need to use semilogy instead of plot:

```
from pylab import *
import matplotlib.pyplot as pyplot
a = [ 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()
```