Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[2.3.0] - 2026-04-18

DataFrame.setIndex(columnName, { drop }) — promote a column to be the index
DataFrame.resetIndex({ drop, name }) — demote the current index back to a column or discard it
Series.at / DataFrame.at — fast scalar label-based cell accessors with .get / .set
Series.iat / DataFrame.iat — fast scalar position-based cell accessors with .get / .set
DataFrame.apply(fn, { axis }) — apply a function column-wise (axis 0) or row-wise (axis 1), passing real Series instances to the callback
camelCase aliases for the existing snake_case methods (sortValues, sortIndex, valueCounts, dropDuplicates)

Established camelCase as the canonical naming convention; snake_case names retained as aliases. Documented in README under “Naming convention”.

Zero breaking changes. All existing snake_case method calls continue to work via the new aliases.

Series sorting methods: sort_values() and sort_index() with ascending/descending support
Series missing data handling: fillna(), dropna(), isna(), notna()
Series value operations: unique(), value_counts(), duplicated(), drop_duplicates()
Series comparison operations: eq(), ne(), gt(), lt(), ge(), le(), between()
Series cumulative operations: cumsum(), cumprod(), cummax(), cummin()
Series string accessor (str) with 9 methods: upper(), lower(), contains(), replace(), split(), strip(), startswith(), endswith(), len()
Series indexing accessors: loc (label-based) and iloc (position-based) with get() and set() methods
Series window operations: rolling(window) and expanding() with mean(), sum(), min(), max(), std()
Comprehensive documentation for all new Series methods in README

DataFrame.merge() method supporting inner, left, right, and outer joins with single/multiple join keys
DataFrame.concat() static method for vertical (axis=0) and horizontal (axis=1) concatenation
Comprehensive merge and concat examples in README (Examples 8 and 9)
35 new unit tests for merge and concat operations

Comprehensive DataFrame class with full JSDoc documentation and best practices
Comprehensive Series class with statistical methods (mean, median, mode, std, var, min, max)
DataFrame.select() method for column selection with validation
DataFrame.filter() method with support for complex conditions and chaining
DataFrame.groupBy() method with aggregation support (mean, sum, count, min, max, std)
GroupBy aggregation for single and multiple columns with hierarchical grouping
Full testing infrastructure with Jest configuration
Type detection and validation utilities
Comprehensive error handling system with custom error types
CSV export functionality via toCsv() method
Series transformation methods (map, apply, replace)
Series statistical methods with null value handling
223 comprehensive unit tests covering all functionality

Major refactoring of core Series and DataFrame classes
Enhanced error handling with custom ValidationError, ColumnError, and IndexError
Improved type detection system for better data type inference
Updated Jest configuration to exclude unimplemented modules from coverage