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Pareto chart for python (similar to Matlab's, but much more flexible) - Fork from @tintrinh

Project description

@RogerioPradoJ paretochart - rogeriopradoj-paretochart - Fork from @tintrinh

Pareto chart for python 3 (similar to Matlab, but much more flexible) - Fork from @tintrinh.


  • 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.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 rogeriopradoj-paretochart

If you are using Python2, you can use original @tintrinh's project::

pip install --upgrade paretochart

Development and Publishing New Versions

Using knowledge from

  • define next version number (try to follow semver 2
  • make the changes in codebase
  • update
    • version
    • download_url
  • update
    • pareto_plot_test_figure url
  • commit, tag, and push to git central repo
  • create a source distribution, and validate it:
    • python sdist
    • twine check dist/*
  • upload the source to PyPi:
    • twine upload dist/*

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