Changelog

Changelog#

SheetBuddy follows Semantic Versioning. Below are the details for each release.

Version 3.1.1 (Latest) 🚀#

📊 Outlier Detection & Visualization

  • Feature: Detect outliers in numerical columns using Z-score or IQR method.

  • Implementation: New methods detect_outliers() and add_outliers_plot() to identify and visualize outliers using boxplots.

📈 Enhanced EDA Visualizations

  • Feature: Comprehensive visualizations in the EDA sheet: - Histograms for numerical columns. - Boxplots for outliers. - Correlation heatmaps for understanding relationships.

  • Implementation: Integrated methods for automatic visualization in Excel reports.

📝 Custom Text Headings

  • Feature: Descriptive section titles for each visualization.

  • Implementation: add_text_heading() method for adding custom headings.

📂 Structured Dataset Summary

  • Feature: New Dataset Info sheet providing dataset metadata (format, number of rows, description, and data link).

  • Implementation: add_dataset_info() method.

📦 Requirements

  • pandas==1.3.3

  • requests==2.26.0

  • openpyxl==3.0.9

  • tqdm==4.62.3

  • matplotlib==3.4.3

  • seaborn==0.11.2

  • scipy==1.7.1

💾 Installation

  • Requires Python 3.7+

pip install sheetbuddy==3.1.1

📢 Note: This library is optimized for numerical datasets.

Version 2.0.0 🎯#

🔗 Correlation Matrix Analysis

  • Feature: Computes the correlation matrix for numerical columns.

  • Benefit: Helps understand variable relationships.

  • Output: Saved as ‘Correlation Matrix’ in the generated Excel report.

📊 Basic Mathematical Statistics

  • Feature: Computes mean, median, mode, and range.

  • Benefit: Provides an overview of central tendency and dispersion.

  • Output: Saved as ‘Basic Mathematics’ sheet.

🚀 Improvements

  • Progress Bars: Enhanced user experience with loading indicators.

  • Better Data Handling: Optimized for CSV, JSON, and Excel files.

🛠️ Bug Fixes

  • Fixed Read-Only File System Errors: Improved output file handling.

  • Enhanced Error Logging: More detailed logs for troubleshooting.

📖 Documentation

  • Expanded Docstrings for all methods.

  • New Usage Examples in the README.

Version 1.0.0 (Initial Release) 🎉#

📅 Release Date: June 23, 2024

🚀 Major New Features

  • Excel Sheet Styling: Advanced formatting for reports.

  • Additional Functionalities: Extended data analysis capabilities.

📈 Improvements

  • Performance Optimization: Faster execution and larger dataset handling.

  • Better Data Processing: Optimized file parsing and encoding.

🛠️ Bug Fixes

  • General Fixes: Resolved multiple minor issues.

  • Compatibility Fixes: Ensured support for different Python & Excel versions.

❌ Breaking Changes

  • API Changes: Some functions have been renamed.

  • Deprecated Methods: Older methods replaced with more efficient alternatives.

📖 Documentation Updates

  • New Tutorials for styling and EDA features.

  • Example Use Cases:

import sheetbuddy as sb

data = sb.read_csv('data.csv')
styled_excel = sb.style_excel(data)
sb.save_excel(styled_excel, 'styled_output.xlsx')

✅ View Full Changelog on GitHub: 🔗 [GitHub Compare View](AshishRogannagari/SheetBuddy)

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