Who meets both conditions? · Data Playground

The question

A product team needs the three largest available order lines from the East region.

df Ranked shortlist

Your inputs

`df`

One row is an order line. in_stock determines availability; quantity counts units, not distinct products.

Field meanings and units

order_id: Order or order-line identifier, as defined by this brief.
product: Recorded product label.
category: Product category.
region: Sales region.
quantity: Number of units.
unit_price: Dollars per unit.
discount: Discount in dollars for the whole order line.
in_stock: Whether the order line is marked available.

`df` · first 5 of 18 rows
`order_id`	`product`	`category`	`region`	`quantity`	`unit_price`	`discount`	`in_stock`
P001	" Notebook "	Paper	East	2	3.5	0	false
P002	PEN	Writing	West	5	1.2	None	true
P003	" pencil"	Writing	East	3	0.8	0.5	true
P004	Note-book	Paper	West	4	3.5	1	true
P005	" Notebook "	Paper	East	1	3.5	0	true

View all 18 rows

`df` · complete input
`order_id`	`product`	`category`	`region`	`quantity`	`unit_price`	`discount`	`in_stock`
P001	" Notebook "	Paper	East	2	3.5	0	false
P002	PEN	Writing	West	5	1.2	None	true
P003	" pencil"	Writing	East	3	0.8	0.5	true
P004	Note-book	Paper	West	4	3.5	1	true
P005	" Notebook "	Paper	East	1	3.5	0	true
P006	PEN	Writing	West	6	1.2	None	false
P007	" pencil"	Writing	East	2	0.8	0.5	true
P008	Note-book	Paper	West	8	3.5	1	true
P009	" Notebook "	Paper	East	2	3.5	0	true
P010	PEN	Writing	West	5	1.2	None	true
P011	" pencil"	Writing	East	3	0.8	0.5	false
P012	Note-book	Paper	West	4	3.5	1	true
P013	" Notebook "	Paper	East	1	3.5	0	true
P014	PEN	Writing	West	6	1.2	None	true
P015	" pencil"	Writing	East	2	0.8	0.5	true
P016	Note-book	Paper	West	8	3.5	1	false
P017	" Notebook "	Paper	East	2	3.5	0	true
P018	PEN	Writing	West	5	1.2	None	true

The editable setup in Your Python creates these inputs when you run it.

Your task · Who meets both conditions?

A product team needs the three largest available order lines from the East region.

shortlistDataFrameunitsnumber

Deliverables

Make the outputs listed below. Use each name exactly as shown. Then choose Check answer.

Python name key

Teal outlines name table columns. Violet left rules name Python objects. Dotted rules mark syntax, functions and parameters. Use each name exactly as shown.

Qualifying shortlistOutputshortlistDataFrame
1. Create shortlist from in_stock records in region East.
2. Take the top three by quantity descending, breaking ties by order_id ascending.
3. Keep order_id, product and quantity.
Units representedOutputunitsnumber
1. Store the total quantity in the shortlist as units.

Data policy Keep all supplied source tables unchanged. Work on separate outputs.

Help Hints & explained solution

Choose the amount of help you need. Opening one hint does not reveal the others.

Hint 1 — Think

Should ranking happen before or after eligibility is decided?

Hint 2 — Tools

Boolean selection, sort_values(), head() and sum()

Revisit: Combine conditions · Sort the table · Take the first look · Answer one numerical question

Hint 3 — Approach

Restrict to eligible records, rank with the stated tie-break, retain three, and total only their quantities.

Explained solution

Add these lines below # Your work in the editor. The supplied input setup is already there.

shortlist = (
    df.loc[df.in_stock & (df.region == 'East'), ['order_id', 'product', 'quantity']]
    .sort_values(['quantity', 'order_id'], ascending=[False, True])
    .head(3)
)
units = shortlist.quantity.sum()
shortlist

View supplied setup

This code is already at the top of the editor.

import pandas as pd

# Supplied input: df (18 rows)
df = pd.DataFrame(
    [
        ('P001', ' Notebook ', 'Paper', 'East', 2, 3.5, 0, False),
        ('P002', 'PEN', 'Writing', 'West', 5, 1.2, None, True),
        ('P003', ' pencil', 'Writing', 'East', 3, 0.8, 0.5, True),
        ('P004', 'Note-book', 'Paper', 'West', 4, 3.5, 1, True),
        ('P005', ' Notebook ', 'Paper', 'East', 1, 3.5, 0, True),
        ('P006', 'PEN', 'Writing', 'West', 6, 1.2, None, False),
        ('P007', ' pencil', 'Writing', 'East', 2, 0.8, 0.5, True),
        ('P008', 'Note-book', 'Paper', 'West', 8, 3.5, 1, True),
        ('P009', ' Notebook ', 'Paper', 'East', 2, 3.5, 0, True),
        ('P010', 'PEN', 'Writing', 'West', 5, 1.2, None, True),
        ('P011', ' pencil', 'Writing', 'East', 3, 0.8, 0.5, False),
        ('P012', 'Note-book', 'Paper', 'West', 4, 3.5, 1, True),
        ('P013', ' Notebook ', 'Paper', 'East', 1, 3.5, 0, True),
        ('P014', 'PEN', 'Writing', 'West', 6, 1.2, None, True),
        ('P015', ' pencil', 'Writing', 'East', 2, 0.8, 0.5, True),
        ('P016', 'Note-book', 'Paper', 'West', 8, 3.5, 1, False),
        ('P017', ' Notebook ', 'Paper', 'East', 2, 3.5, 0, True),
        ('P018', 'PEN', 'Writing', 'West', 5, 1.2, None, True),
    ],
    columns=['order_id', 'product', 'category', 'region', 'quantity', 'unit_price', 'discount', 'in_stock'],
)

Why these steps exist

Eligibility comes before ranking: unavailable products must not occupy a shortlist place.
The total uses just the three selected lines, and the ID tie-break makes the handoff deterministic.

Another valid approach

You may sort in stages or with multiple keys, provided ties are resolved before selecting three records.