Metadata-Version: 2.1
Name: sunburst
Version: 1.0.0a2
Summary: Use matplotlib to plot sunburst charts/hierarchical pie charts/ring charts/multilevel pie charts (as e.g. in disk usage diagrams).
Home-page: https://github.com/klieret/sunburst
Author: Kilian Lieret
Author-email: kilian.lieret@posteo.de
Maintainer: Kilian Lieret
Maintainer-email: kilian.lieret@posteo.de
License: BSD
Project-URL: Bug Tracker, https://github.com/klieret/sunburst/issues
Project-URL: Documentation, https://sunburst.readthedocs.io/
Project-URL: Source Code, https://github.com/klieret/sunburst/
Keywords: plot,matplotlib,pyplot,sunburst,pie chart,multilevel pie chart,disk usage diagram,ring chart,hierarchical pie chart
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE.txt

# Sunburst Charts

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🔖 **Check out the [full documentation](https://sunburst.readthedocs.io/en/latest/)!**

## Introduction

`sunburst` is a module to create "Ring charts" or "Hierarchical Pie
Charts" (also called "Multilevel Pie Charts" or "Sunburst Charts") together with the `matplotlib` package. Quoting
[Wikipedia](https://en.wikipedia.org/wiki/Pie_chart#Ring_chart_.2F_Sunburst_chart_.2F_Multilevel_pie_chart):

> A ring chart, also known as a sunburst chart or a multilevel pie
> chart, is used to visualize hierarchical data, depicted by concentric circles. The circle in the centre represents the root node, with the
> hierarchy moving outward from the center. A segment of the inner
> circle bears a hierarchical relationship to those segments of the
> outer circle which lie within the angular sweep of the parent segment.

A prominent example are disk usage charts (see
`examples/disk_usage_plot.py` for this example):

![](https://cloud.githubusercontent.com/assets/13602468/20408444/c8cb6a56-ad15-11e6-8f5c-1abef69dc551.png)

## ✨ Features

`sunburst` tries to be

-   Intuitive & Easy to use: After setting up your data and
    `matplotlib`, not more than two lines are necessary to generate
    first plots ([minimal
    example](https://github.com/klieret/sunburst/blob/master/examples/minimal_example_sunburst.py)).
-   Flexible & Robust: Wherever it makes sense, the methods of the
    `SunburstPlot` class are intended to be overwritten. Methods that
    are responsible for spacing, coloring, styling etc. of the `wedges`
    take the corresponding data point (`path`) as an argument, allowing to set most properties independently for each `wedge`.

More specifically:

-   Clever positioning of labels, which - depending on space constraints are positioned in a tangentially or radially.
-   An easy way to "explode" the plot by redefining
    `sunburst.wedge_spacing`
    ([example](https://github.com/klieret/sunburst/blob/master/examples/minimal_example_exploded.py),
    [example](https://github.com/klieret/sunburst/blob/master/examples/disk_usage_exploded.py)).

## 📦 Installation

To install, run

```bash
pip3 install sunburst
```

## 🚧 Migration notice

For the first release to pypi, this package has been rebranded as
`sunburst`. This includes non-backwards compatible changes to the API: Most importantly, the `HPie` class is now `SunburstPlot` and many other
changes.

To get the old version back, check out the `old-hpie` branch.

## 🔥 Minimal example

You can find several examples at `examples/`. The most basic example is
`minimal_example_sunburst.py`:

```python
import matplotlib.pyplot as plt
from sunburst import SunburstPlot, stringvalues_to_pv

# set up some data
data = stringvalues_to_pv({
    'ipsum':                      40.45,
    'ipsum/eirmod':               29.34,
    'ipsum/eirmod/dolor':         94.4,
    'lorem':                      36.12,
    'lorem/sadipscing/dolor':     44.32,
    'lorem/sadipscing/lorem':     37.15,
    'lorem/sadipscing/nonumy':    23.98,
    'lorem/eirmod':               11.12,
    'lorem/eirmod/lorem':         45.65,
    'lorem/sadipscing':           79.67,
})


fig, ax = plt.subplots()
sbp = SunburstPlot(data, ax)
sbp.plot(setup_axes=True)
ax.set_title('Example SunburstPlot')

plt.show()
```

Running this script with `python3 minimal_example_sunburst.py` will
produce the following plot:

![](https://cloud.githubusercontent.com/assets/13602468/20408443/c8c8c1d4-ad15-11e6-86a6-868dc98e91d0.png)

## The Data

Note that the value corresponding to path is always the value
*excluding* the values of the children of the path. Therefore plotting
the `SunburstPlot` object computes a "completed" version of the
"pathvalue dictionary". You can check this with the
`SunburstPlot._completed_pv` instance variable which gets initialized
after calling `SunburstPlot.plot(*args)`. Running our minimal example
prints the following:

```python
sbp._completed_pv.items() = {
    Path((, )): 442.2,  # = the total sum of all items =
                        # = 36.12 + 44.32 + 37.15 + 23.98 + ...
    Path(('ipsum', )): 164.19000000000003,  # = sum of "ipsum" and all of its children =
                                            # = 40.45 + 29.34 + 94.4
    Path(('ipsum', 'eirmod', )): 123.74000000000001, # = sum of ipsum/eirmod and all of its children =
                                                     # = 29.34 + 94.4
    Path(('ipsum', 'eirmod', 'dolor', )): 94.4,
    Path(('lorem', )): 278.01,
    Path(('lorem', 'eirmod', )): 56.769999999999996,
    Path(('lorem', 'eirmod', 'lorem', )): 45.65,
    Path(('lorem', 'sadipscing', )): 185.12,
    Path(('lorem', 'sadipscing', 'dolor', )): 44.32,
    Path(('lorem', 'sadipscing', 'lorem', )): 37.15,
    Path(('lorem', 'sadipscing', 'nonumy', )): 23.98,
}
```

`sunburst/tests/test_calc.py` contains an explicit test of this
calculation based on a similar example.

## Ring Charts

Thus you get ring charts, if and only if all of the non-zero values
correspond to paths with the same length. E.g. if we change the above data as follows (by lengthening the paths with question marks and
removing the entry for the empty path):

```python
data = stringvalues_to_pv({
    'ipsum/?/?':                 40.45,
    'ipsum/eirmod/?':            29.34,
    'ipsum/eirmod/dolor':        94.4,
    'lorem/?/?':                 36.12,
    'lorem/sadipscing/dolor':    44.32,
    'lorem/sadipscing/lorem':    37.15,
    'lorem/sadipscing/nonumy':   23.98,
    'lorem/eirmod/?':            11.12,
    'lorem/eirmod/lorem':        45.65,
    'lorem/sadipscing/?':        79.67,
})
```

we should get a classical ring chart. This is
`minimal_example_rings.py`. Running it via
`python3 minimal_example_rings.py` yields the following plot, which
indeed just fills up the white space of the above plot with wedges
labeled `?`.

![](https://cloud.githubusercontent.com/assets/13602468/20408445/c8cdf4ec-ad15-11e6-9a10-2758c3469f9d.png)

## License

This project is licensed under the *BSD 3-Clause License*, see
`LICENSE.txt`.


