12.2.2 Map, filter, and reduce

• Functional programming treats computation as the evaluation of mathematical functions
• Functional programming relies on state modification during computation.

  False
• Match the key principle of functional programming with its description:

  Immutability ↔️ Data cannot be modified after creation

  Statelessness ↔️ Functions do not rely on external state

  Pure Functions ↔️ Return same output for same input
• The Map Function transforms a list by applying a function to each element
• The Map Function modifies the original list when transforming its elements.

  False
• The Filter Function selects elements from a list that meet criteria specified by a predicate
• The Filter Function modifies the original list when selecting elements.

  False
• The Reduce Function combines elements of a list into a single value
• The Reduce Function modifies the original list when combining elements.

  False
• The Map Function applies a given function to each element
• What does the Reduce Function combine elements into?

  A single value
• The Reduce Function uses an accumulator to combine list elements.
• The Reduce Function modifies the original list.

  False
• What does the example in Python calculate using the Reduce Function?

  The sum of numbers
• The Map Function returns a new list with transformed elements.
• The Map Function changes the original list.

  False
• What does the Python example in the Map Function calculate?

  The square of numbers
• The `map()` function in Python uses a lambda function for transformation.
• What is the primary emphasis of Functional Programming?

  Mathematical functions
• Functional Programming allows state modification.

  False
• Match the aspect with the correct programming paradigm:

  Paradigm ↔️ Functional Programming

  State ↔️ No state modification

  Mutability ↔️ Data is immutable

  Functions ↔️ Pure functions with no side effects
• What are the key principles of Functional Programming?

  Immutability, statelessness, pure functions
• The Map Function returns a new list with transformed results.
• Is the Map Function destructive?

  No
• The Filter Function modifies the original list.

  False
• The Filter Function uses a predicate function to select elements.
• What does the Python example in the Filter Function select?

  Even numbers
• The Reduce Function modifies the original list.

  False
• What type of value does the Reduce Function return?

  A single aggregated value
• The Map Function applies a function to each element of a list.
• Is the Map Function destructive?

  No
• The Map Function transforms each element of a list without modifying the original list.
• Match the functional programming concept with its description:

  Reduce Function ↔️ Combines elements into a single value

  Map Function ↔️ Transforms each element of a list

  Filter Function ↔️ Selects elements based on a predicate
• What does the Map Function apply to each element of a list?

  A given function
• The Map Function is non-destructive, meaning it leaves the original list unchanged
• The original list is modified by the Map Function.

  False
• What is the purpose of the Filter Function?

  Selecting elements
• The Filter Function creates a new list based on a specified predicate function.
• The Filter Function alters the original list.

  False
• What does the Reduce Function use to combine list elements?

  An accumulator