Squarify

Common errors

• AttributeError: module 'squarify' has no attribute 'plot'

  cause This typically occurs if a local file named `squarify.py` exists in your working directory, shadowing the installed `squarify` library. Another cause can be not importing `matplotlib.pyplot` if `squarify.plot` is being used.
  fix Rename any local file named `squarify.py` or ensure `import matplotlib.pyplot as plt` is present if you intend to use `squarify.plot`.

• ModuleNotFoundError: No module named 'squarify'

  cause The `squarify` package is not installed in the Python environment you are currently using, or there's a mismatch between where it's installed and where your interpreter is looking.
  fix Install the package using `pip install squarify`. If using a virtual environment or Jupyter/IDE, ensure the correct Python interpreter path is selected.

• Labels for small treemap squares overlap or go out of bounds, making them unreadable.

  cause By default, `squarify.plot` may not automatically adjust label font sizes or positions for very small rectangles, leading to visual clutter.
  fix Manually adjust font size using `text_kwargs={'fontsize': N}` or consider adding custom logic for label placement/wrapping for smaller squares. For highly dynamic or dense treemaps, some labels may need to be omitted.

Warnings

• gotcha Input `sizes` list must be positive values and sorted in descending order before passing to `squarify.squarify` or `squarify.plot`.
  Fix: Always sort your `sizes` list: `sizes.sort(reverse=True)`.
• gotcha For `squarify.squarify` (the layout function), the sum of `sizes` should equal the total area (`dx * dy`). Use `squarify.normalize_sizes(values, dx, dy)` to prepare your values if they don't already match the target area.
  Fix: Use `normalized_sizes = squarify.normalize_sizes(original_sizes, width, height)` before calling `squarify.squarify(normalized_sizes, ...)`.
• gotcha The `squarify` algorithm prioritizes aspect ratios close to 1. This can sometimes lead to less clarity in hierarchical structures or instability in layout with small data changes compared to other treemap algorithms.
  Fix: Be aware of this characteristic; for applications requiring strict hierarchy visibility or layout stability for animations, consider alternative treemap implementations.

Install

• pip install squarify Install with pip

Imports

• squarify
  wrong:

  from squarify import squarify

  correct:

  import squarify

  The common pattern is to import the entire module as 'squarify', then call functions like `squarify.plot()` or `squarify.squarify()`.
• pyplot

  import matplotlib.pyplot as plt

  Required when using the `squarify.plot` function for visualization.

Quickstart

This quickstart demonstrates how to create a basic treemap using `squarify.plot()`. It shows how to define sizes and labels, sort the sizes (a requirement for squarify), and render the treemap using Matplotlib.

import squarify
import matplotlib.pyplot as plt

sizes = [500, 433, 78, 25, 25, 7]
labels = ['Category A', 'Category B', 'Category C', 'Category D', 'Category E', 'Category F']
colors = ['#4C72B0', '#55A868', '#C44E52', '#8172B2', '#CCB974', '#64B5CD']

# Sort sizes in descending order as required by squarify
sizes.sort(reverse=True)

plt.figure(figsize=(10, 6))
squarify.plot(sizes=sizes, label=labels, color=colors, alpha=0.8)
plt.title('Treemap Visualization with Squarify')
plt.axis('off') # Removes axes to show only the treemap
plt.show()