In this lab, you'll get some hands on practice creating and using lambda functions.
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
import pandas as pd
df = pd.read_csv('Yelp_Reviews.csv')
df.head(2)
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Unnamed: 0 | business_id | cool | date | funny | review_id | stars | text | useful | user_id | |
---|---|---|---|---|---|---|---|---|---|---|
0 | 1 | pomGBqfbxcqPv14c3XH-ZQ | 0 | 2012-11-13 | 0 | dDl8zu1vWPdKGihJrwQbpw | 5 | I love this place! My fiance And I go here atl... | 0 | msQe1u7Z_XuqjGoqhB0J5g |
1 | 2 | jtQARsP6P-LbkyjbO1qNGg | 1 | 2014-10-23 | 1 | LZp4UX5zK3e-c5ZGSeo3kA | 1 | Terrible. Dry corn bread. Rib tips were all fa... | 3 | msQe1u7Z_XuqjGoqhB0J5g |
Use a lambda function to create a new column called 'stars_squared' by squarring the stars column.
#Your code here
Select the month from the date string using a lambda function.
# Your code here
Do this with a single line of code!
# Your code here
#Your code here
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
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
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.