lambda

What is a Lambda function?

In Excel, and other spreadsheet functions, there are many builtin functions. What if you want to define your own whether to convert a temperature from Fahrenheit to Celsius, or to solve a mathematical equation? In the image above, you see the syntax of a lambda expression in Excel. Microsoft advise us that we may:

Use a LAMBDA function to create custom, reusable functions and call them by a friendly name. The new function is available throughout the workbook and called like native Excel functions.

You can create a function for a commonly used formula, eliminate the need to copy and paste this formula (which can be error-prone), and effectively add your own functions to the native Excel function library. Furthermore, a LAMBDA function doesn't require VBA, macros or JavaScript, so non-programmers can also benefit from its use.

In using the lambda in Excel, the following terms are used:

parameter: A value that you want to pass to the function, such as a cell reference, string or number. You can enter up to 253 parameters. This argument is optional.

calculation: The formula you want to execute and return as the result of the function. It must be the last argument and it must return a result. This argument is required.

lambda functions In Python

It is much the same in Python and other programming languages! A lambda function in Python is a small, anonymous function defined using the lambda keyword. Unlike regular functions defined with def, lambda functions are typically used for simple operations and are written in a single line.

Key Characteristics

Anonymous: No name is assigned to the function.

Single Expression: Can only contain one expression, which is evaluated and returned.

Short and Concise: Ideal for simple tasks or when passing functions as arguments.

The terminology is different but means the same thing as depicted in the graphic below:

arguments: Inputs to the function (like parameters in a regular function).

expression: A single expression (formula) that is evaluated and returned.

Creating lambda functions in Python

Lets look at some simple examples, comparing using a user defined function, and the equivalent with a lambda function.

regular function

def square(num):

return num * num

print(square(5)) # Output: 25

def adder(num1, num2):

return num1 + num2

print(adder(3, 5)) # Output: 8

def arr_adder(arr):

return sum(arr)

print(arr_adder([1, 2, 3, 4])) # Output: 10

lambda equivalent

square = lambda x: x * x

print(square(5)) # Output: 25

adder = lambda x, y: x + y

print(adder(3, 5)) # Output: 8

# using a list comprehension

arr_adder = lambda arr: sum(i for i in arr)

print(arr_adder([1, 2, 3, 4])) # Output: 10

Common use-cases

1) Using with map()

The map() function applies a function to every item in an iterable:

numbers = [1, 2, 3, 4]

squares = list(map(lambda x: x * x, numbers))

print(squares) # Output: [1, 4, 9, 16] # each is the square of the input list

2) Using with filter()

The filter() function selects elements from an iterable based on a condition.

numbers = [1, 2, 3, 4, 5, 6]

evens = list(filter(lambda x: x % 2 == 0, numbers)) # only even numbers

print(evens) # Output: [2, 4, 6]

3) Using with sorted()

Lambda functions can define custom sorting keys.

pairs = [(1, 'one'), (3, 'three'), (2, 'two')]

sorted_pairs = sorted(pairs, key=lambda x: x[1])

# here the output is sorted alphabetically by the string at index 1

print(sorted_pairs) # Output: [(1, 'one'), (3, 'three'), (2, 'two')]

When to use lambda functions

When you need a simple function for a short task.
When passing a function as an argument to higher-order functions like map(), filter(), or sorted().
When you want concise code for one-off operations.

Limitations

Lambda functions can only contain a single expression.
They are less readable for complex logic compared to named functions.
Not suitable for functions requiring multiple statements or documentation.

For a Deep Dive, check out the realpython tutorial!

Exercises

Try these exercises to practice lambda functions.

Exercise 1: Basic Lambda

Create a lambda function that takes two arguments and returns their product. Test it with inputs 4 and 5.

Exercise 2: Using with map()

Given a list [10, 20, 30, 40], use a lambda function with map() to create a new list where each element is divided by 10.

Exercise 3: Using with filter()

Given a list [1, 2, 3, 4, 5, 6, 7, 8], use a lambda function with filter() to create a new list containing only numbers greater than 5.

Exercise 4: Using with sorted()

Given a list of tuples [('apple', 3), ('banana', 1), ('cherry', 2)], sort the list by the second element of each tuple using a lambda function.

Exercise Solutions

Here are the solutions- Try solving them yourself before checking!

Solution 1

product = lambda x, y: x * y

print(product(4, 5)) # Output: 20

Solution 2

numbers = [10, 20, 30, 40]

result = list(map(lambda x: x / 10, numbers))

print(result) # Output: [1.0, 2.0, 3.0, 4.0]

Solution 3

numbers = [1, 2, 3, 4, 5, 6, 7, 8]

result = list(filter(lambda x: x > 5, numbers))

print(result) # Output: [6, 7, 8]

Solution 4

fruits = [('apple', 3), ('banana', 1), ('cherry', 2)]

sorted_fruits = sorted(fruits, key=lambda x: x[1])

print(sorted_fruits) # Output: [('banana', 1), ('cherry', 2), ('apple', 3)]

Summary

Lambda functions are concise, anonymous functions for simple tasks.
They are powerful when used with functions like map(), filter(), and sorted().
Use them sparingly for clarity, and prefer named functions for complex logic.

Additional Resources

Python Documentation: Lambda Expressions

Practice more with online platforms like LeetCode or HackerRank.

Page updated

Google Sites

Report abuse