Read a Series: labels and values

Understand the idea

A Series pairs each value with an index label. Labels and numbered positions are different.

Illustrative data

list(readings.index)

Series
Position	Index label	Reading
0	101	12
1	109	4
2	103	19

Result[101, 109, 103]

Follow the code

readings = df["reading"]
list(readings.index)

What the syntax does

readings = df["reading"]: Select one labelled Series.
readings.index: Read the row labels, not the measurements.
list(...): Display the labels or values as a Python list.

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 labels belong to the measurements?

Select reading from all rows of df.
Display its row labels as a list in their current order.
Use the Series index attribute.

Setup is included in the editor.

Hint

The labels are beside the readings. Read .index, without parentheses.

Reveal solution

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

readings = df["reading"]
list(readings.index)

# 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 readings = df["reading"] list(readings.____)

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