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Sorting

In Pandas, we can sort by a column or by the index:

# Sort by the price column
df = df.sort_values("price")

# Sort by index
df = df.sort_index()

In Polars, with no index available, the sort() method sorts by columns or expressions:

# Sort by the price column
df = df.sort("price")

Sort by Expression

Say we had a DataFrame of RPG character stats, and we wanted to sort by the sum of attack_rating and luck_bonus. In Pandas, you'd often create a temporary calculated column. In Polars, you can sort by an expression directly:

df = df.sort(pl.col("attack_rating") + pl.col("luck_bonus"))

Assignment

SnackStack's support team needs a queue of devices where those with the lowest combined battery_pct and signal_pct should be reviewed first.

Complete the build_service_queue function. It accepts a Polars DataFrame of device status rows and returns a new DataFrame.

Filter to only rows where needs_service is True.
Sort the filtered rows by the sum of battery_pct and signal_pct.
Select and return only the device_id, battery_pct, and signal_pct columns.