Map Filter Reduce

Map, Filter, and Reduce are three fundamental higher-order functions in functional programming used for processing collections of data. Map transforms each element in a collection by applying a function, Filter selects elements that satisfy a condition, and Reduce aggregates all elements into a single value using an accumulator. These functions are widely implemented in programming languages and libraries to enable declarative, concise data manipulation without explicit loops.

Also known as: map-filter-reduce, map reduce filter, functional programming trio, MFR, array methods

Why learn Map Filter Reduce?

Developers should learn and use Map, Filter, and Reduce to write cleaner, more readable, and maintainable code when working with arrays, lists, or other iterable data structures. They are essential for tasks like data transformation (e.g., converting formats), filtering datasets (e.g., removing invalid entries), and performing aggregations (e.g., summing values), commonly seen in data processing, analytics, and functional programming paradigms.

Learning Resources

• docs: MDN Web Docs: Array.prototype.map(), filter(), reduce()
• docs: Python Documentation: map(), filter(), and functools.reduce()
• tutorial: FreeCodeCamp: Learn JavaScript Functional Programming
• video: YouTube: Map, Filter, Reduce Explained
• book: Eloquent JavaScript: Higher-Order Functions