Lambda Functions - Lab

Introduction|

In this lab, you'll get some hands on practice creating and using lambda functions.

Objectives

You will be able to:

• Understand what lambda functions are and why they are useful
• Use lambda functions to transform data within lists and DataFrames

Lambda Functions

import pandas as pd
df = pd.read_csv('Yelp_Reviews.csv')
df.head(2)

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Simple Arithmetic

Use a lambda function to create a new column called 'stars_squared' by squarring the stars column.

#Your code here

Dates

Select the month from the date string using a lambda function.

# Your code here

What is the average number of words for a yelp review?

Do this with a single line of code!

# Your code here

Create a new column for the number of words in the review.

#Your code here

Rewrite the following as a lamda function. Create a new column 'Review_Length'

def rewrite_as_lambda(value):
    if len(value) < 50:
        return 'Short'
    elif len(value) < 80:
        return 'Medium'
    else:
        return 'Long'
#Hint: nest your if, else conditionals

#Your code here

Level Up: Dates Adavanced!

Overwrite the date column by reordering the month and day from YYYY-MM-DD to DD-MM-YYYY. Try to do this using a lambda function.

#Your code here

Summary

Great! Hopefully you're getting the hang of lambda functions now! It's important not to overuse them - it will often make more sense to define a function so that it's reusable elsewhere. But whenever you need to quickly apply some simple processing to a collection of data you have a new technique that will help you to do just that. It'll also be useful if you're reading someone elses code that happens to use lambdas.