API Reference

This section provides comprehensive documentation for all BoxFrame classes, methods, and utilities. The API is organized into logical sections for easy navigation.

Core Classes

DataFrame API

The main class for working with two-dimensional data. Includes methods for data inspection, selection, manipulation, grouping, and cleaning.

Series API

One-dimensional labeled arrays. Provides methods for data access, statistical operations, and data manipulation.

GroupBy API

Grouping and aggregation operations for both Series and DataFrame.

WasmEngine API

High-performance WASM engine for memory management and accelerated operations.

Utilities & Factory Methods

Static Methods

BoxFrame static factory methods for creating DataFrames and Series, plus data I/O operations and utility functions.

CSV Parser API

CSV parsing functions for reading data from files, URLs, and strings.

GoogleSheets API

Integration for reading public Google Sheets data.

Utility Functions

Helper functions for data type handling, conversions, and validation.

Data Types

Complete type definitions, interfaces, and type aliases used throughout the BoxFrame API.

Error Handling

Comprehensive error handling with specific error classes for different scenarios.

Quick Reference

Most Common Operations

// Create DataFrame
const df = new DataFrame({
    name: ["Alice", "Bob", "Charlie"],
    age: [25, 30, 35],
    city: ["New York", "London", "Tokyo"]
});

// Basic operations
df.head()                    // First 5 rows
df.shape                     // [rows, columns]
df.get("age")                // Get column as Series
df.query("age > 30")         // Filter rows with query

// Data manipulation
df.assign({ salary: [50000, 60000, 70000] })  // Add column
df.sortValues("age", false)                   // Sort descending
df.groupBy("city").agg({ age: "mean" })       // Group and aggregate

Performance Features

• WASM Acceleration: Automatic fallback to JavaScript if WASM unavailable
• Memory Management: Efficient memory usage with automatic cleanup
• Performance Monitoring: Query memory usage and active series count

Error Handling

BoxFrame uses descriptive error messages for better debugging:

• Column Errors: "Column 'name' not found" when accessing missing columns
• Index Errors: "Index length mismatch" when data lengths don't align
• Query Errors: "Invalid condition" when query syntax is wrong
• Validation Errors: Specific messages for invalid parameters