apply() on columns in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the apply() function do when used on DataFrame columns in pandas?

It applies a given function to each column (Series) of the DataFrame, allowing you to transform or analyze each column separately.

beginner

How do you apply a function to each column of a DataFrame using apply()?

Use df.apply(your_function). By default, apply() works column-wise, passing each column as a Series to the function.

intermediate

What is the difference between apply() and applymap() in pandas?

apply() works on rows or columns (Series), while applymap() works element-wise on every single value in the DataFrame.

beginner

Example: How to calculate the range (max - min) of each column using apply()?

Use df.apply(lambda col: col.max() - col.min()). This applies the lambda function to each column and returns a Series of ranges.

intermediate

Can apply() on columns handle functions that return multiple values?

Yes, if the function returns a Series or list, apply() will combine these into a DataFrame with new columns.

What is the default axis when using apply() on a pandas DataFrame?

A Columns (axis=0)

B Rows (axis=1)

C Elements (each cell)

D No default axis

By default, apply() works on columns, which is axis=0 in pandas.

Which pandas function applies a function element-wise to every cell in a DataFrame?

A apply()

B applymap()

C map()

D transform()

applymap() applies a function to each element in the DataFrame.

What will df.apply(lambda col: col.mean()) return?

A Mean of each row

B Sum of each row

C Mean of each column

D Sum of each column

The lambda function calculates the mean of each column because apply() works column-wise by default.

If a function passed to apply() returns a Series, what is the output?

A A Series

B A scalar value

C An error

D A DataFrame

When the function returns a Series for each column, apply() combines these into a DataFrame.

How can you apply a function to each row instead of each column using apply()?

A Set <code>axis=1</code>

B Set <code>axis=0</code>

C Use <code>applymap()</code>

D Use <code>map()</code>

Setting axis=1 makes apply() work row-wise.

Explain how the apply() function works on DataFrame columns in pandas and give a simple example.

Think about how you can transform or summarize each column separately.

Describe the difference between apply() and applymap() in pandas.

Consider the level at which the function is applied: whole columns vs individual cells.