Find an extreme row by its label

Understand the idea

idxmax() returns the largest known value’s row label, rather than its value or numbered position.

Illustrative data

Click the highlighted code to change the result.

df[].idxmax()

Source `df`
row	`reading`	`temperature`
101	12	22
106	15	25
103	19	24
109	13	20

→

Result103

Largest reading: 19. Its row label is 103; its position is 2.

Follow the code

label = df["reading"].idxmax()
row = df.loc[label]
row[["hours", "reading"]]

What the syntax does

label = df["reading"].idxmax(): Find the label of the largest reading, not its value or position.

Labelled sensor readings
row	`sample`	`hours`	`reading`
101	R1	1	12
109	R2	4	4
103	R3	6	19
150	R4	3	8
106	R5	2	7
118	R6	5	15

Your task · Follow

Which label identifies the largest `reading`?

Use all rows of df.
Display the index label of the largest reading.
Use idxmax()
Return the label rather than its reading or position.

Setup is included in the editor.

Hint

The result is a label suitable for loc, not the largest measurement.

Reveal solution

Keep the supplied setup and replace the Your work section with this example.

df["reading"].idxmax()

# Supplied setup — editable import pandas as pd data = { "sample": ["R1", "R2", "R3", "R4", "R5", "R6"], "hours": [1, 4, 6, 3, 2, 5], "reading": [12, 4, 19, 8, 7, 15], } df = pd.DataFrame(data) df.index = [101, 109, 103, 150, 106, 118] # Your work df["reading"].____()

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