Fancy indexing with integer arrays in NumPy - Step-by-Step Execution

Concept Flow - Fancy indexing with integer arrays

Start with base array

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Provide integer index array

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Use index array to select elements

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Create new array with selected elements

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Output

Fancy indexing uses an array of integers to pick elements from another array, creating a new array with those elements.

Execution Sample

NumPy

import numpy as np
arr = np.array([10, 20, 30, 40, 50])
indices = np.array([1, 3, 4])
result = arr[indices]
print(result)

Select elements at positions 1, 3, and 4 from the array using fancy indexing.

Execution Table

Step	Action	Array State	Index Array	Result	Explanation
1	Create base array	[10, 20, 30, 40, 50]	-	-	Base array with 5 elements created
2	Create index array	-	[1, 3, 4]	-	Index array with positions to select
3	Select elements using indices	[10, 20, 30, 40, 50]	[1, 3, 4]	[20, 40, 50]	Elements at positions 1,3,4 selected
4	Print result	-	-	[20, 40, 50]	Output the selected elements

💡 All indices processed, fancy indexing completed

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	Final
arr	undefined	[10, 20, 30, 40, 50]	[10, 20, 30, 40, 50]	[10, 20, 30, 40, 50]	[10, 20, 30, 40, 50]
indices	undefined	undefined	[1, 3, 4]	[1, 3, 4]	[1, 3, 4]
result	undefined	undefined	undefined	[20, 40, 50]	[20, 40, 50]

Key Moments - 3 Insights

Why does the result array have length 3, not the same length as the base array?

Because fancy indexing selects elements only at the positions given by the index array, which has length 3 (see execution_table step 3). The result length matches the index array length.

What happens if an index is repeated in the index array?

The element at that repeated index appears multiple times in the result. Fancy indexing picks elements in order, so repeats cause repeats in output (not shown here but follows same logic).

Can the index array contain indices out of range?

No, if an index is out of range, numpy raises an IndexError. All indices must be valid positions in the base array.

Visual Quiz - 3 Questions

Look at the execution_table step 3, what is the value of result?

A [20, 40, 50]

B [1, 3, 4]

C [10, 30, 50]

D [10, 20, 30, 40, 50]

💡 Hint

Check the 'Result' column in step 3 of execution_table

At which step is the index array created?

A Step 1

B Step 3

C Step 2

D Step 4

💡 Hint

Look at the 'Action' column and when 'Create index array' happens

If the index array was [0, 0, 2], what would be the length of the result array?

A 2

B 3

C 5

D 1

💡 Hint

Result length matches index array length, see variable_tracker for indices length

Concept Snapshot

Fancy indexing with integer arrays:
- Use an integer array to pick elements from another array.
- Syntax: result = arr[indices]
- Result length equals index array length.
- Repeated indices repeat elements in result.
- Indices must be valid positions in base array.

Full Transcript

Fancy indexing with integer arrays means using an array of integers as positions to select elements from another array. We start with a base array, then create an index array with positions we want. Using arr[indices], numpy picks elements at those positions and creates a new array. The result length matches the index array length. If indices repeat, elements repeat in the result. Indices must be valid or an error occurs. This method is useful to select multiple elements at once in any order.