Create a numeric column

New columns & clean text · W07 · 8 MIN

Calculate a whole column at once.

Exercises within this concept

FollowFollow the techniqueCurrent exercise
ChangeAdapt a requirement
TransferChoose and combine

Understand the idea

Arithmetic on columns works row by row. Assigning to a new column name stores a derived measurement alongside the originals.

Illustration · not the exercise output

A small example

Prices [3, 5] plus tips [1, 2] give totals [4, 7]. Ages [2, 3] years become [24, 36] months.

Follow the code

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

df["pair_price"] = df["price"] * 2
df

What each part does

df["pair_price"] =: Create a new column called pair_price on the left.
df["price"] * 2: Multiply each existing price by two on the right, row by row.

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

The shop offers a two-item pack of each candy.
Using df unit prices, add pair_price equal to twice price.
Keep the original columns and display df.

Hint

A two-item pack costs two unit prices under this offer.

Reveal solution

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

df["pair_price"] = df["price"] * 2
df

Your task · Follow

The shop offers a two-item pack of each candy.
Using df unit prices, add pair_price equal to twice price.
Keep the original columns and display df.

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["pair_price"] = df["price"] * ____
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.