Rows and columns by label

Selecting data · I09 · 8 MIN

Select named rows and columns with loc.

Exercises within this concept

FollowFollow the techniqueCurrent exercise
ChangeAdapt a requirement
TransferChoose and combine

Understand the idea

loc selects labels, not positions. Use a slice for a continuous range and a list for specific labels.

Illustration · not the exercise output

A small example

With labels A, B, C, D, E: loc["B":"D"] selects B, C, D; loc[["D", "B"]] selects D, then B.

Follow the code

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

df.loc["B":"D", ["price"]]

What each part does

df.loc["B":"D", ["price"]]: labels B through D, including D; one price column

Other choices for later exercises

df.iloc[1:4, [2]]: positions 1, 2 and 3; column at position 2

Your inputs

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

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

Your task · Follow

Using df, return labels B through D, including the end label, keeping only price as a one-column DataFrame.
Use: loc.

Hint

A label slice includes its ending label. Keep the column name in a list for a DataFrame.

Reveal solution

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

df.loc["B":"D", ["price"]]

Your task · Follow

Using df, return labels B through D, including the end label, keeping only price as a one-column DataFrame.
Use: loc.

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)

df.index = ["A", "B", "C", "D", "E", "F"]

# Your work
# Build the requested result from the given table
result = df.loc[____, ____]
result

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.