Adjust axis scaling with pandas parallel_coordinates

Question

I'm working on plotting some data with pandas in the form of parallel coordinates, and I'm not too sure how to go about setting the the y-axis scaling.

Here's my code:

import matplotlib
import matplotlib.pyplot as plt
import pandas as panda
from pandas.tools.plotting import parallel_coordinates

def parallel_coords(filename):

    matplotlib.style.use('ggplot')

    data = panda.read_csv(filename)
    parallel_coordinates(data[['postcode','2005','2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013', '2014', '2015']], 'postcode')
    plt.show()

parallel_coords('crime_data_updated.csv')

The output looks like this: You can see that there's heaps of data. How can I change the y axis scale? For example making it logarithmically scaled or choosing to only display between 0 - 5000. I've had a look at the pandas documentation but it has not helped thus far.

Answer 1

It is indeed possible to scale axes and the kind of data you have seems like very suitable to try to scale.

Seems like all you need to do is define that y axis is to be scaled - without needing to do any scaling yourself - and matplolib.pyplot does all graft for you.

Try with this:

parallel_coordinates(data[['postcode','2005','2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013', '2014', '2015']], 'postcode')
plt.yscale('log') ## <- should be enough to define log scaling on your y-axis here
plt.show()

You can see documentation here

I hope that helps!