Review · Find the surprises · Data Playground

Task 1 · Pet adoption

Return df sorted first by species alphabetically, then by age from oldest to youngest within each species.

The editable setup on the right creates df. Run executes the setup and your work from top to bottom.

Your inputs

Pet adoption · 6 synthetic rows
name	species	age	weight	room
Milo	Cat	3	4.2	A
Pepper	Dog	7	18.5	B
Luna	Cat	2	3.6	A
Bean	Rabbit	4	2.4	B
Rex	Dog	5	22	A
Nori	Rabbit	1	1.8	B

Revisit the concept lesson →

Remember the idea

Sorting moves whole rows together. With multiple sort keys, the first sets the main order and the next resolves ties.

A small example

Sorting group ascending, score descending puts group A before B, then higher scores first within each group.

What each choice does
Code or choice	Meaning
`sort_values("score")`	Smallest to largest by default (ascending=True).
`ascending=False`	Largest to smallest.
`sort_values(["group", "score"], ascending=[True, False])`	Pair each column with its own direction.

Hint

Pass a list of columns and a matching list of ascending flags.

Reveal solution

One way to do it. Keep any supplied setup in the editor and use this in the Your work section.

df.sort_values(["species", "age"], ascending=[True, False])

# Supplied setup — editable import pandas as pd data = { "name": ["Milo", "Pepper", "Luna", "Bean", "Rex", "Nori"], "species": ["Cat", "Dog", "Cat", "Rabbit", "Dog", "Rabbit"], "age": [3, 7, 2, 4, 5, 1], "weight": [4.2, 18.5, 3.6, 2.4, 22, 1.8], "room": ["A", "B", "A", "B", "A", "B"], } df = pd.DataFrame(data) # Your work # Retrieve the earlier skill

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