Vectorise before apply

A responsible finish · W30 · 8 MIN

Choose a simple column operation before a row function.

Exercises within this concept

FollowFollow the techniqueCurrent exercise
ChangeAdapt a requirement
TransferChoose and combine

Understand the idea

Express a calculation directly on a Series when possible. Vectorized arithmetic applies the operation to every value.

Illustration · not the exercise output

A small example

Prices [10, 20] × 1.1 become [11, 22]. Subtracting their original mean (15) gives [−5, 5].

Follow the code

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

df["adjusted"] = (df["price"] * 1.1).round(2)
df

What each part does

df["price"] * 1.1: direct vectorised arithmetic

Other choices for later exercises

map(dictionary): a value lookup
apply(lambda x: ...): call a function on each value

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

A price revision raises all unit prices in df by 10%.
Add adjusted as the revised price rounded to two decimals, preserving the original price.
Display df.
Use vectorised arithmetic; do not use apply().

Hint

Keep raw and revised prices side by side.

Reveal solution

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

df["adjusted"] = (df["price"] * 1.1).round(2)
df

Optional stretch

Compare with df["{a}"].apply(lambda x: round(x * 1.1, 2)). Which expresses the intent more directly?

Your task · Follow

A price revision raises all unit prices in df by 10%.
Add adjusted as the revised price rounded to two decimals, preserving the original price.
Display df.
Use vectorised arithmetic; do not use apply().

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
df["adjusted"] = (df["price"] * ____).round(2)
df

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.