np.intersect1d() for intersection in NumPy - Step-by-Step Execution

Concept Flow - np.intersect1d() for intersection

Input: Array1, Array2

↓

Find common elements

↓

Sort and remove duplicates

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Return intersection array

The function takes two arrays, finds elements present in both, removes duplicates, sorts them, and returns the result.

Execution Sample

NumPy

import numpy as np
arr1 = np.array([1, 2, 3, 4])
arr2 = np.array([3, 4, 5, 6])
result = np.intersect1d(arr1, arr2)
print(result)

This code finds the common elements between arr1 and arr2 and prints the sorted intersection without duplicates.

Execution Table

Step	Action	Input Arrays	Intermediate Result	Output
1	Receive input arrays	[1, 2, 3, 4], [3, 4, 5, 6]	N/A	N/A
2	Find common elements	Same	[3 4]	N/A
3	Sort and remove duplicates	[3 4]	[3 4]	N/A
4	Return intersection array	N/A	N/A	[3 4]
5	Print result	N/A	N/A	[3 4]

💡 All common elements found, duplicates removed, sorted, and returned.

Variable Tracker

Variable	Start	After Step 2	After Step 3	Final
arr1	[1 2 3 4]	[1 2 3 4]	[1 2 3 4]	[1 2 3 4]
arr2	[3 4 5 6]	[3 4 5 6]	[3 4 5 6]	[3 4 5 6]
result	N/A	[3 4]	[3 4]	[3 4]

Key Moments - 2 Insights

Why does the output not include duplicates even if input arrays have duplicates?

np.intersect1d automatically removes duplicates from the intersection result, as shown in step 3 of the execution_table where duplicates are removed before returning.

Are the elements in the output always sorted?

Yes, np.intersect1d returns a sorted array of common elements, confirmed in step 3 where sorting happens before output.

Visual Quiz - 3 Questions

Look at the execution_table at step 2, what is the intermediate result?

A [3 4]

B [1, 2]

C [5, 6]

D [2, 3]

💡 Hint

Check the 'Intermediate Result' column at step 2 in execution_table.

At which step does np.intersect1d remove duplicates and sort the result?

A Step 1

B Step 2

C Step 3

D Step 4

💡 Hint

Look at the 'Action' column describing sorting and duplicate removal.

If arr1 was [1, 2, 2, 3] and arr2 was [2, 2, 4], what would the final result be?

A [2, 2]

B [2]

C [1, 2]

D [1, 2, 4]

💡 Hint

np.intersect1d removes duplicates in the output, see variable_tracker for 'result'.

Concept Snapshot

np.intersect1d(arr1, arr2)
- Finds common elements in two arrays
- Removes duplicates automatically
- Returns sorted intersection array
- Useful for comparing datasets
- Output is always 1D sorted array

Full Transcript

This visual execution traces np.intersect1d which finds common elements between two numpy arrays. First, it takes two input arrays. Then it finds elements present in both arrays. Next, it removes duplicates and sorts the common elements. Finally, it returns the sorted array of unique common elements. The example code shows arrays [1, 2, 3, 4] and [3, 4, 5, 6] intersecting to [3, 4]. Key points are that duplicates are removed and output is sorted. The variable tracker shows how the result variable changes from empty to the final intersection. The quizzes test understanding of intermediate results, sorting step, and duplicate removal behavior.