kvbiii-plots 0.4.2

A collection of plotting functions for data visualization in Python.

kvbiii-plots

Overview

kvbiii-plots is a modular Python package for advanced data visualization, focusing on exploratory data analysis (EDA), machine learning (ML), and model evaluation.

Folder Structure

┣━ 📁 .github
┃  ┗━ 📁 workflows
┃     ┗━ 📜 python-publish.yml
┣━ 📁 kvbiii_plots
┃  ┣━ 📁 eda
┃  ┃  ┣━ 📁 examples
┃  ┃  ┃  ┣━ 📓 categorical_plots_examples.ipynb
┃  ┃  ┃  ┣━ 📓 continuous_plots_examples.ipynb
┃  ┃  ┃  ┣━ 📓 multivariate_plots_examples.ipynb
┃  ┃  ┃  ┗━ 📓 time_series_plots_examples.ipynb
┃  ┃  ┣━ 🐍 __init__.py
┃  ┃  ┣━ 🐍 categorical_plots.py
┃  ┃  ┣━ 🐍 continuous_plots.py
┃  ┃  ┣━ 🐍 multivariate_plots.py
┃  ┃  ┗━ 🐍 time_series_plots.py
┃  ┣━ 📁 evaluation
┃  ┃  ┣━ 📁 examples
┃  ┃  ┃  ┣━ 📓 classification_plots_examples.ipynb
┃  ┃  ┃  ┣━ 📓 regression_plots_examples.ipynb
┃  ┃  ┃  ┗━ 📓 shap_plots_examples.ipynb
┃  ┃  ┣━ 🐍 __init__.py
┃  ┃  ┣━ 🐍 classification_plots.py
┃  ┃  ┣━ 🐍 regression_plots.py
┃  ┃  ┗━ 🐍 shap_plots.py
┃  ┣━ 📁 ml
┃  ┃  ┣━ 📁 examples
┃  ┃  ┃  ┣━ 📓 optuna_plots_examples.ipynb
┃  ┃  ┃  ┗━ 📓 other_plots_examples.ipynb
┃  ┃  ┣━ 🐍 __init__.py
┃  ┃  ┣━ 🐍 optuna_plots.py
┃  ┃  ┗━ 🐍 other_plots.py
┃  ┣━ 🐍 __init__.py
┃  ┗━ 🐍 base_plots.py
┣━ 📁 tests
┃  ┣━ 📁 eda
┃  ┃  ┣━ 🐍 test_categorical_plots.py
┃  ┃  ┣━ 🐍 test_continuous_plots.py
┃  ┃  ┣━ 🐍 test_eda_init.py
┃  ┃  ┣━ 🐍 test_multivariate_plots.py
┃  ┃  ┗━ 🐍 test_time_series_plots.py
┃  ┣━ 📁 evaluation
┃  ┃  ┣━ 🐍 test_classification_plots.py
┃  ┃  ┣━ 🐍 test_evaluation_init.py
┃  ┃  ┣━ 🐍 test_regression_plots.py
┃  ┃  ┗━ 🐍 test_shap_plots.py
┃  ┣━ 📁 ml
┃  ┃  ┣━ 🐍 test_ml_init.py
┃  ┃  ┣━ 🐍 test_optuna_plots.py
┃  ┃  ┗━ 🐍 test_other_plots.py
┃  ┣━ 🐍 conftest.py
┃  ┣━ 🐍 test_base_plots.py
┃  ┗━ 🐍 test_main_init.py
┣━ 📄 .env
┣━ 👻 .gitignore
┣━ 🐚 install_package.sh
┣━ ⚙️ pyproject.toml
┣━ 📖 README.md
┗━ 📃 requirements.txt

Files Description

• 📁 .github: GitHub configuration files.
  • 📁 workflows: CI/CD workflow definitions.
    • 📜 python-publish.yml: Python package publishing workflow.
• 📁 kvbiii_plots: Main package source code.
  • 📁 eda: Exploratory Data Analysis plotting modules.
    • 📁 examples: Example Jupyter notebooks for EDA plots.
      • 📓 categorical_plots_examples.ipynb: Categorical plot examples.
      • 📓 continuous_plots_examples.ipynb: Continuous plot examples.
      • 📓 multivariate_plots_examples.ipynb: Multivariate plot examples.
      • 📓 time_series_plots_examples.ipynb: Time series plot examples.
    • 🐍 __init__.py: EDA module initializer.
    • 🐍 categorical_plots.py: Functions for categorical plots.
    • 🐍 continuous_plots.py: Functions for continuous plots.
    • 🐍 multivariate_plots.py: Functions for multivariate plots.
    • 🐍 time_series_plots.py: Functions for time series plots.
  • 📁 evaluation: Model evaluation plotting modules.
    • 📁 examples: Example notebooks for evaluation plots.
      • 📓 classification_plots_examples.ipynb: Classification plot examples.
      • 📓 regression_plots_examples.ipynb: Regression plot examples.
      • 📓 shap_plots_examples.ipynb: SHAP plot examples.
    • 🐍 __init__.py: Evaluation module initializer.
    • 🐍 classification_plots.py: Functions for classification plots.
    • 🐍 regression_plots.py: Functions for regression plots.
    • 🐍 shap_plots.py: Functions for SHAP plots.
  • 📁 ml: Machine learning plotting modules.
    • 📁 examples: Example notebooks for ML plots.
      • 📓 optuna_plots_examples.ipynb: Optuna optimization plot examples.
      • 📓 other_plots_examples.ipynb: Miscellaneous ML plot examples.
    • 🐍 __init__.py: ML module initializer.
    • 🐍 optuna_plots.py: Functions for Optuna plots.
    • 🐍 other_plots.py: Other ML-related plots.
  • 🐍 __init__.py: Main package initializer.
  • 🐍 base_plots.py: Base plotting utilities.
• 📁 tests: Unit tests for all modules.
  • 📁 eda: Tests for EDA plotting functions.
    • 🐍 test_categorical_plots.py: Tests for categorical plots.
    • 🐍 test_continuous_plots.py: Tests for continuous plots.
    • 🐍 test_eda_init.py: Tests for EDA module initialization.
    • 🐍 test_multivariate_plots.py: Tests for multivariate plots.
    • 🐍 test_time_series_plots.py: Tests for time series plots.
  • 📁 evaluation: Tests for evaluation plotting functions.
    • 🐍 test_classification_plots.py: Tests for classification plots.
    • 🐍 test_evaluation_init.py: Tests for evaluation module initialization.
    • 🐍 test_regression_plots.py: Tests for regression plots.
    • 🐍 test_shap_plots.py: Tests for SHAP plots.
  • 📁 ml: Tests for ML plotting functions.
    • 🐍 test_ml_init.py: Tests for ML module initialization.
    • 🐍 test_optuna_plots.py: Tests for Optuna plots.
    • 🐍 test_other_plots.py: Tests for other ML plots.
  • 🐍 conftest.py: Pytest configuration.
  • 🐍 test_base_plots.py: Tests for base plotting utilities.
  • 🐍 test_main_init.py: Tests for main package initialization.
• 📄 .env: Environment variable definitions.
• 👻 .gitignore: Git ignored files specification.
• 🐚 install_package.sh: Shell script for package installation.
• ⚙️ pyproject.toml: Project metadata and build configuration.
• 📖 README.md: Main project documentation.
• 📃 requirements.txt: Python dependencies list.

Installation

To install the repository, follow these steps:

1. Clone the repository:

git clone <repo_url>

2. Navigate to the repository directory:

cd kvbiii-plots

3. Create a virtual environment (optional but recommended):

python -m venv <venv_name>

4. Activate the virtual environment:

source <venv_name>/bin/activate

Usage

You can check the example Jupyter notebooks in the examples folders within each module for usage examples.

For instance, see categorical_plots_examples.ipynb.

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Last updated on 2025-09-03 18:05:55