np.setdiff1d() for difference in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does np.setdiff1d() do in NumPy?

np.setdiff1d() returns the sorted, unique values in one array that are not in another array. It finds the difference between two arrays.

beginner

How does np.setdiff1d() handle duplicate values in the input arrays?

It removes duplicates and returns only unique values from the first array that are not in the second array.

beginner

Example: What is the output of np.setdiff1d([1, 2, 3, 4], [2, 4])?

The output is [1 3] because 1 and 3 are in the first array but not in the second.

intermediate

Can np.setdiff1d() be used with arrays of strings?

Yes, it works with any array of comparable elements, including strings, returning unique elements from the first array not in the second.

intermediate

Why is the output of np.setdiff1d() always sorted?

Because np.setdiff1d() sorts the unique values before returning them to provide consistent and predictable output.

What does np.setdiff1d(a, b) return?

A All elements from both arrays combined

B Elements in <code>b</code> not in <code>a</code>

C Common elements in both <code>a</code> and <code>b</code>

D Elements in <code>a</code> not in <code>b</code>

np.setdiff1d(a, b) returns elements that are in a but not in b.

If a = [1, 2, 2, 3] and b = [2], what does np.setdiff1d(a, b) return?

A [1, 3]

B [1, 2, 3]

C [2]

D [3]

Duplicates are removed, so only unique elements in a not in b are returned: 1 and 3.

Is the output of np.setdiff1d() always sorted?

A Yes

B No

C Only if arrays are sorted

D Depends on input type

The function always returns sorted unique values for consistency.

Can np.setdiff1d() be used with string arrays?

A Only with boolean arrays

B Yes

C Only with numeric arrays

D No

It works with any comparable data type, including strings.

What happens if all elements of a are in b when using np.setdiff1d(a, b)?

A Returns <code>a</code> unchanged

B Returns <code>b</code>

C Returns an empty array

D Raises an error

If no elements in a are unique compared to b, the result is an empty array.

Explain how np.setdiff1d() works and give a simple example.

Think about finding what is left in one list after removing items found in another.

Describe a real-life situation where you might use np.setdiff1d().

Imagine you have two lists and want to find what is only in one of them.

Practice

1.

What does the function np.setdiff1d(arr1, arr2) do?

easy

A. Finds elements in arr1 that are not in arr2

B. Finds elements common to both arr1 and arr2

C. Combines arr1 and arr2 into one array

D. Sorts arr1 in descending order

Solution

1. Step 1: Understand the function purpose

   np.setdiff1d(arr1, arr2) returns elements unique to arr1 that are not found in arr2.

2. Step 2: Compare with options

   Finds elements in arr1 that are not in arr2 matches this behavior exactly, while others describe different operations.

3. Final Answer:

   Finds elements in arr1 that are not in arr2 -> Option A

4. Quick Check:

   Unique elements in arr1 = D [OK]

Hint: Remember: setdiff1d finds what is only in first array [OK]

Common Mistakes:

• Confusing setdiff1d with intersection
• Thinking it merges arrays
• Assuming it sorts in descending order

2.

Which of the following is the correct syntax to find elements in a not in b using np.setdiff1d()?

a = np.array([1, 2, 3])
b = np.array([2, 3, 4])

easy

A. np.setdiff1d(a + b)

B. np.setdiff1d(b, a)

C. np.setdiff1d(a)

D. np.setdiff1d(a, b)

Solution

1. Step 1: Identify correct parameter order

   The first argument is the array to find unique elements from; the second is the array to exclude elements from.

2. Step 2: Match with options

   To find elements in a not in b, use np.setdiff1d(a, b), which is np.setdiff1d(a, b).

3. Final Answer:

   np.setdiff1d(a, b) -> Option D

4. Quick Check:

   First array minus second array = A [OK]

Hint: First argument is the array to subtract from [OK]

Common Mistakes:

• Swapping the order of arrays
• Passing only one array
• Trying to add arrays inside setdiff1d

3.

What is the output of the following code?

import numpy as np
x = np.array([5, 3, 9, 1])
y = np.array([3, 7, 1])
result = np.setdiff1d(x, y)
print(result)

medium

A. [1 3 5 7 9]

B. [5 9]

C. [3 7]

D. [1 5 9]

Solution

1. Step 1: Identify elements in x not in y

   Elements in x are [5, 3, 9, 1]. Elements in y are [3, 7, 1]. The elements in x but not in y are 5 and 9.

2. Step 2: Check output format

   np.setdiff1d returns a sorted array without duplicates, so output is [5 9].

3. Final Answer:

   [5 9] -> Option B

4. Quick Check:

   Unique elements in x = A [OK]

Hint: Output is sorted unique elements from first array only [OK]

Common Mistakes:

• Including elements from second array
• Not sorting output
• Confusing with intersection output

4.

Find the error in this code snippet:

import numpy as np
arr1 = np.array([1, 2, 3])
arr2 = np.array([2, 3, 4])
result = np.setdiff1d(arr1 arr2)
print(result)

medium

A. Missing comma between arguments in setdiff1d

B. Arrays must be lists, not numpy arrays

C. Function name is misspelled

D. print statement syntax is incorrect

Solution

1. Step 1: Check function call syntax

   The call np.setdiff1d(arr1 arr2) is missing a comma between arr1 and arr2.

2. Step 2: Verify other parts

   Arrays are correctly numpy arrays, function name is correct, and print syntax is valid in Python 3.

3. Final Answer:

   Missing comma between arguments in setdiff1d -> Option A

4. Quick Check:

   Comma separates arguments = C [OK]

Hint: Check commas between function arguments carefully [OK]

Common Mistakes:

• Forgetting commas between parameters
• Thinking numpy arrays are invalid inputs
• Assuming print needs parentheses in Python 3

5.

You have two arrays representing IDs of users who visited two different websites:

site1 = np.array([101, 102, 103, 104, 105])
site2 = np.array([103, 104, 106])

How can you find the IDs of users who visited only the first site?

hard

A. np.setdiff1d(site2, site1)

B. np.intersect1d(site1, site2)

C. np.setdiff1d(site1, site2)

D. np.union1d(site1, site2)

Solution

1. Step 1: Understand the problem

   We want users who visited site1 but not site2.

2. Step 2: Apply np.setdiff1d

   Using np.setdiff1d(site1, site2) returns elements in site1 not in site2.

3. Step 3: Check other options

   np.setdiff1d(site2, site1) reverses the order, giving users only in site2. Options C and D find common or combined users, not unique to site1.

4. Final Answer:

   np.setdiff1d(site1, site2) -> Option C

5. Quick Check:

   Unique to first array = B [OK]

Hint: Use setdiff1d with first array as main set [OK]

Common Mistakes:

• Swapping arrays order
• Using intersection instead of difference
• Using union which combines all