Sort the table

Understanding values · I12 · 8 MIN

Order filtered rows to answer a question.

Exercises within this concept

FollowFollow the techniqueCurrent exercise
ChangeChange sort direction
TransferSort with two keys

Understand the idea

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

Illustration · not the exercise output

A small example

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

Follow the code

Apply the idea to the supplied table. Read from top to bottom; the final line displays the result.

filtered = df[df["price"] > 2.1]
filtered.sort_values("rating", ascending=False)

What each part does

sort_values("rating"): sort by that column
ascending=False: largest first
filtered =: give an intermediate table a useful name

Your inputs

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

Candy shop · 6 synthetic rows
candy	flavour	price	rating	shelf
Gummy Bear	fruity	1.2	4.1	A
Choco Pop	chocolate	2.1	4.6	B
Mint Bite	mint	1.5	3.8	A
Berry Loop	fruity	2.8	4.4	B
Cocoa Cube	chocolate	3.4	4.9	A
Lemon Drop	fruity	1.8	4	B

Your task · Follow

Using df, keep rows with price greater than 2.1; then sort them from highest to lowest rating.
Use: sort_values().

Hint

Filter first, then sort the remaining whole rows; ascending=False puts the highest first.

Reveal solution

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

filtered = df[df["price"] > 2.1]
filtered.sort_values("rating", ascending=False)

Your task · Follow

Using df, keep rows with price greater than 2.1; then sort them from highest to lowest rating.
Use: sort_values().

YOUR PYTHON

Tab: indent · Shift+Tab: outdent · Esc, then Tab: leave editor

# Supplied setup — editable
import pandas as pd

data = {
    "candy": [
        "Gummy Bear",
        "Choco Pop",
        "Mint Bite",
        "Berry Loop",
        "Cocoa Cube",
        "Lemon Drop",
    ],
    "flavour": ["fruity", "chocolate", "mint", "fruity", "chocolate", "fruity"],
    "price": [1.2, 2.1, 1.5, 2.8, 3.4, 1.8],
    "rating": [4.1, 4.6, 3.8, 4.4, 4.9, 4],
    "shelf": ["A", "B", "A", "B", "A", "B"],
}

df = pd.DataFrame(data)

# Your work
filtered = df[df["price"] > ____]
filtered.sort_values(____, ascending=____)

Each run executes all editor code in a fresh Python session. Display a value by leaving it on the final line.

Python starts when you open a lesson.

Output

Run your code to see what Python returns.