apply() with lambda functions in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the apply() function do in pandas?

It lets you run a function on each row or column of a DataFrame or on each element of a Series, making it easy to transform data.

beginner

How do lambda functions help when using apply()?

Lambda functions let you write small, quick functions directly inside <code>apply()</code> without needing to define a separate function first.

beginner

Example: What does this code do?<br>

df['new'] = df['old'].apply(lambda x: x * 2)

It creates a new column called 'new' where each value is double the corresponding value in the 'old' column.

intermediate

What argument do you use with apply() to apply a function across rows instead of columns?

Use axis=1 to apply the function across rows. The default is axis=0 for columns.

beginner

Can apply() with lambda functions be used on both Series and DataFrames?

Yes, apply() works on Series to apply a function to each element, and on DataFrames to apply a function to each column or row.

What does df['col'].apply(lambda x: x + 1) do?

A Adds 1 to the first value only

B Adds 1 to the entire column

C Removes 1 from each value in 'col'

D Adds 1 to each value in 'col'

The lambda function adds 1 to each element in the 'col' column.

Which apply() argument applies a function across rows in a DataFrame?

A axis=0

B axis=1

C row=True

D columns=True

axis=1 applies the function across rows.

What type of function is commonly used inside apply() for quick operations?

A Lambda function

B Recursive function

C Generator function

D Decorator function

Lambda functions are small, quick functions often used inside apply().

If you want to apply a function to each column in a DataFrame, which axis do you use?

A axis=0

B axis=1

C axis=2

D axis=-1

axis=0 applies the function to each column.

Can apply() change the data type of a column?

A Only for numeric columns

B No, data types are fixed

C Yes, if the function returns a different type

D Only for string columns

If the function returns a different type, the column's data type can change.

Explain how apply() works with lambda functions on a pandas DataFrame.

Think about how you can quickly change data in a table using small functions.

Describe a real-life example where you might use apply() with a lambda function in data analysis.

Imagine you have a list of prices and want to add tax to each price.