# Lambda map, reduce, and filter functions

In this article, we are going to discuss the Lambda map, reduce, and filter built-in functions’ usage.

In Python, the `map()`, `reduce()`, and `filter()` functions are higher-order functions that can be used with lambda functions to perform various operations on lists and other iterable objects.

1. `map()` function:

The `map()` the function applies a given function to each item of an iterable and returns a new iterable with the transformed values. The syntax for the `map()` function is:

`map(function, iterable)`

Here, `function` is the function to be applied to each item of the iterable, and `iterable` is the iterable object to be transformed.

You can use lambda functions with the `map()` function to apply a simple operation to each item of an iterable. For example, to square each item in a list, you can use the following code:

```numbers = [1, 2, 3, 4, 5]
squared = list(map(lambda x: x**2, numbers))
print(squared)   # Output: [1, 4, 9, 16, 25]```
1. `reduce()` function:

The `reduce()` the function applies a given function to the first two items of an iterable, then applies the function to the result and the next item, and so on, until all items have been processed. The syntax for the `reduce()` function is:

`reduce(function, iterable)`

Here, `function` is the function to be applied to the first two items of the iterable and their result, and `iterable` is the iterable object to be processed.

You can use lambda functions with the `reduce()` function to apply a simple operation to an iterable. For example, to find the product of all items in a list, you can use the following code:

```from functools import reduce
numbers = [1, 2, 3, 4, 5]
product = reduce(lambda x, y: x*y, numbers)
print(product)   # Output: 120```
1. `filter()` function:

The `filter()` the function applies a given function to each item of an iterable and returns a new iterable with only the items for which the function returns `True`. The syntax for the `filter()` function is:

`filter(function, iterable)`

Here, `function` is the function to be applied to each item of the iterable, and `iterable` is the iterable object to be filtered.

You can use lambda functions with the `filter()` function to filter an iterable based on a simple condition. For example, to filter out all even numbers from a list, you can use the following code:

```numbers = [1, 2, 3, 4, 5]
odd_numbers = list(filter(lambda x: x % 2 != 0, numbers))
print(odd_numbers)   # Output: [1, 3, 5]``` 