Pareto chart for python (similar to Matlab's, but much more flexible)
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README.rst updated README.rst Sep 5, 2013
pareto_plot_test_figure.png added example figure Sep 2, 2013 added Sep 5, 2013



Pareto chart for python (similar to Matlab, but much more flexible).


  • Data labels for the chart x-axis.
  • Fully customizable with unique arg and kwarg inputs:
  • Put the chart on arbitrary axes.


First, a simple import:

from paretochart import pareto

Now, let's create the numeric data (no pre-sorting necessary):

data = [21, 2, 10, 4, 16]

We can even assign x-axis labels (in the same order as the data):

labels = ['tom', 'betty', 'alyson', 'john', 'bob']

For this example, we'll create 4 plots that show the customization capabilities:

import matplotlib.pyplot as plt

# create a grid of subplots
fig, axes = plt.subplots(2, 2)

The first plot will be the simplest usage, with just the data:

pareto(data, axes=axes[0, 0])
plt.title('Basic chart without labels', fontsize=10)

In the second plot, we'll add labels, put a cumulative limit at 0.75 (or 75%) and turn the cumulative line green:

pareto(data, labels, axes=axes[0, 1], limit=0.75, line_args=('g',))
plt.title('Data with labels, green cum. line, limit=0.75', fontsize=10)

In the third plot, we'll remove the cumulative line and limit line, make the bars green and resize them to a width of 0.5:

pareto(data, labels, cumplot=False, axes=axes[1, 0], data_kw={'width': 0.5,
    'color': 'g'})
plt.title('Data without cum. line, green bar width=0.5', fontsize=10)

In the fourth plot, let's put the cumulative limit at 95% and make that line yellow:

pareto(data, labels, limit=0.95, axes=axes[1, 1], limit_kw={'color': 'y'})
plt.title('Data trimmed at 95%, yellow limit line', fontsize=10)

And last, but not least, let's show the image:

fig.canvas.set_window_title('Pareto Plot Test Figure')

This should result in the following image (click here if the image doesn't show up):


Since this is really a single python file, you can simply go to the GitHub page, simply download and put it in a directory that python can find it.

Alternatively, the file can be installed using:

$ pip install --upgrade paretochart


$ easy_install --upgrade paretochart

If you are using Python3, download the compressed file from here, unzip and run:

$ 2to3 -w *.py

while in the unzipped directory, then run:

$ python3 install

NOTE: Administrative privileges may be required to perform any of the above install methods.


Please send feature requests, bug reports, or feedback to Abraham Lee.