Rename columns

A safe working copy · W02 · 8 MIN

Give a column a clear name.

Exercises within this concept

FollowFollow the techniqueCurrent exercise
ChangeAdapt the workflow
TransferCombine earlier skills

Understand the idea

rename changes labels without changing cell values. A dictionary states each old name and its replacement.

Illustration · not the exercise output

A small example

{"cost": "cost_dollars"} changes only the cost heading; the numbers stay the same.

Follow the code

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

df = df.rename(columns={"price": "amount"})
df

What each part does

df.rename(columns={"price": "amount"}): Return a table with the price heading changed to amount; the values stay put.
columns={"price": "amount"}: In the dictionary, the old heading comes first and the new heading second.
df =: Store the returned table so the new heading is kept.

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

Rename price to amount in df; keep every other column and row.
Keep the changes in df and display it.
Use: rename().

Hint

rename returns a table; assign it back to df to retain the new labels.

Reveal solution

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

df = df.rename(columns={"price": "amount"})
df

Your task · Follow

Rename price to amount in df; keep every other column and row.
Keep the changes in df and display it.
Use: rename().

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 = ____
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.