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eda-vizkit

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eda-vizkit provides small, reusable visualization utilities for exploratory data analysis.

It is designed for analysts who want clear, consistent visual evidence without rewriting common plotting mechanics for every project.

Purpose

Exploratory data analysis repeatedly uses the same kinds of visualizations:

  • numeric distributions
  • categorical distributions
  • numeric-to-numeric relationships
  • numeric-by-category relationships
  • missing-value summaries

eda-vizkit provides concise functions for these common views so analysts can spend more time exploring and interpreting data.

Design

eda-vizkit follows a small set of design rules:

  • accept ordinary pandas DataFrames and explicit column names
  • keep analytical choices visible to the caller
  • return Matplotlib Axes objects
  • never call plt.show()
  • avoid dependencies on analytical workflow frameworks
  • keep the implementation readable and replaceable

The caller retains control over display, composition, annotation, export, and interactive use.

Example

```python from eda_vizkit import save_chart, show_numeric_relationship

ax = show_numeric_relationship( df, x="flipper_length_mm", y="body_mass_g", )

save_chart( ax, "docs/images/feature-target-scatter.png", ) ```

See Also