Review · First contact · Data Playground

Task 1 · Pet adoption

A spot check should include rows from anywhere in df.

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

Your requirements

Display a reproducible sample of three rows using random_state=1.

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

A preview returns selected rows with all their columns. It leaves the original table unchanged.

A small example

For rows A, B, C, D: head(2) shows A, B; tail(2) shows C, D.

What each choice does
Code or choice	Meaning
`head(n) / tail(n)`	Take n rows from the start / end. With no number, each defaults to five.
`sample(n, random_state=1)`	Choose n rows from across the table. The fixed seed repeats the selection on the same data.

Hint

A reproducible sample needs both a sample size and a random seed.

Reveal solution

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

df.sample(3, random_state=1)

# 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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