How big is it?

Getting oriented · I03 · 8 MIN

Read the row and column counts.

Exercises within this concept

FollowFollow the techniqueCurrent exercise
ChangeAdapt the workflow
TransferCombine earlier skills

Understand the idea

shape reports two counts in a fixed order: rows, then columns. Count the entire table unless the question explicitly asks about a preview.

Illustration · not the exercise output

A small example

A table with 6 records and 3 fields has shape (6, 3); its first two rows have shape (2, 3).

Follow the code

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

df.shape

What each part does

df.shape: a pair of counts: rows then columns

Other choices for later exercises

len(df): count the rows
[0]: take the first item; Python starts counting at zero

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, return the pair (number of rows, number of columns) for Candy shop.
Use: shape.

Hint

shape is an attribute, so do not add parentheses. Rows come before columns.

Reveal solution

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

df.shape

Optional stretch

Compare len(df) with df.shape[0]. They should agree.

Your task · Follow

Using df, return the pair (number of rows, number of columns) for Candy shop.
Use: shape.

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.____

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.