np.setdiff1d() for difference in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to find elements in array1 that are not in array2 using np.setdiff1d().

NumPy

import numpy as np
array1 = np.array([1, 2, 3, 4, 5])
array2 = np.array([3, 4, 6])
difference = np.[1](array1, array2)
print(difference)

Drag options to blanks, or click blank then click option'

Aunique

Bunion1d

Cintersect1d

Dsetdiff1d

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.union1d() which returns all unique elements from both arrays.

Using np.intersect1d() which returns common elements.

Using np.unique() which just returns unique elements of one array.

The np.setdiff1d() function returns the sorted, unique values in the first array that are not in the second array.

2fill in blank

medium

Complete the code to find the difference between two arrays and store it in 'diff'.

NumPy

import numpy as np
arr1 = np.array([10, 20, 30, 40])
arr2 = np.array([20, 50])
diff = np.[1](arr1, arr2)
print(diff)

Drag options to blanks, or click blank then click option'

Aintersect1d

Bsetdiff1d

Cunion1d

Dsort

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.intersect1d() which returns common elements.

Using np.union1d() which returns all unique elements combined.

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

3fill in blank

hard

Fix the error in the code to correctly find the difference between arrays using np.setdiff1d().

NumPy

import numpy as np
x = np.array([5, 6, 7, 8])
y = np.array([7, 9])
diff = np.setdiff1d(x, [1])
print(diff)

Drag options to blanks, or click blank then click option'

Anp.array([7, 9])

B[7, 9]

Cy

Dx

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the first array again as the second argument.

Passing a list literal instead of the array variable.

The second argument to np.setdiff1d() should be the array to compare against, which is y here.

4fill in blank

hard

Fill both blanks to create a dictionary with words as keys and their lengths as values, but only for words longer than 3 characters.

NumPy

words = ['apple', 'bat', 'carrot', 'dog']
lengths = {word: [1] for word in words if [2]
print(lengths)

Drag options to blanks, or click blank then click option'

Alen(word)

Bword

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as the value instead of its length.

Using the word variable in the condition instead of its length.

The dictionary comprehension uses len(word) for values and filters words with length greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary of words and their lengths, but only include words with length greater than 3.

NumPy

words = ['sun', 'moon', 'star', 'sky']
lengths = { [1]: [2] for w in words if len(w) [3] 3}
print(lengths)

Drag options to blanks, or click blank then click option'

Aw.upper()

Blen(w)

C>

Dw

Attempts:

3 left

💡 Hint

Common Mistakes

Using uppercase words as keys instead of original words.

Using the word variable as value instead of length.

Using wrong comparison operators.

The dictionary keys are the words themselves (w), values are their lengths (len(w)), and the condition filters words longer than 3 characters (> 3).

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