Combining conditions in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a mask selecting values greater than 5.

NumPy

import numpy as np
arr = np.array([2, 7, 4, 10, 3])
mask = arr [1] 5

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

A<

B>

C<=

D==

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' which selects smaller values.

Using '==' which selects only values equal to 5.

The operator > selects values greater than 5.

2fill in blank

medium

Complete the code to select values greater than 3 and less than 8 using logical AND.

NumPy

import numpy as np
arr = np.array([2, 7, 4, 10, 3])
mask = (arr > 3) [1] (arr < 8)

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

A^

B|

C&

D~

Attempts:

3 left

💡 Hint

Common Mistakes

Using '|' which means OR instead of AND.

Using '^' which means XOR and gives wrong results.

The operator & is used for element-wise logical AND in NumPy arrays.

3fill in blank

hard

Fix the error in combining conditions with parentheses.

NumPy

import numpy as np
arr = np.array([1, 5, 8, 3, 7])
mask = (arr > 3) [1] (arr < 8)

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

A&

Band

C|

Dor

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'and' which causes a ValueError in NumPy arrays.

Forgetting parentheses around each condition.

Use & with parentheses for element-wise logical AND in NumPy arrays. Python keywords 'and'/'or' do not work element-wise.

4fill in blank

hard

Fill both blanks to create a mask selecting values less than 4 or greater than 7.

NumPy

import numpy as np
arr = np.array([2, 5, 3, 9, 7])
mask = (arr [1] 4) [2] (arr > 7)

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

A<

B>

C|

D&

Attempts:

3 left

💡 Hint

Common Mistakes

Using '&' instead of '|' which selects values satisfying both conditions.

Using '>' in the first blank which selects wrong values.

Use < to select values less than 4 and | for logical OR to combine conditions.

5fill in blank

hard

Fill all three blanks to create a dictionary of words and their lengths for words longer than 3 letters and containing 'a'.

NumPy

words = ['apple', 'bat', 'cat', 'dog', 'ant']
result = { [1]: [2] for word in words if len(word) [3] 3 and 'a' in word }

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

Aword

Blen(word)

C>

Dword.upper()

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'word.upper()' as key changes the word unnecessarily.

Using '<' instead of '>' in the length condition.

The dictionary keys are the words themselves (word), values are their lengths (len(word)), and the condition checks if length is greater than 3 (>).

Practice

1. Which of the following is the correct way to combine two conditions a > 5 and b < 10 in NumPy to select elements where both are true?

easy

A. Use (a > 5) & (b < 10)

B. Use a > 5 & b < 10 without parentheses

C. Use (a > 5) | (b < 10)

D. Use a > 5 or b < 10

Solution

1. Step 1: Understand combining conditions in NumPy

   NumPy requires each condition to be in parentheses when using & (AND) or | (OR) operators.

2. Step 2: Identify correct syntax for AND condition

   The correct way to combine a > 5 and b < 10 with AND is (a > 5) & (b < 10).

3. Final Answer:

   Use (a > 5) & (b < 10) -> Option A

4. Quick Check:

   Parentheses + & = correct AND condition [OK]

Hint: Always put each condition in parentheses when combining [OK]

Common Mistakes:

• Omitting parentheses around conditions
• Using Python 'and' instead of '&' for arrays
• Using 'or' instead of '|' for arrays

2. Which of the following is the correct syntax to select elements from a NumPy array arr where values are NOT equal to 0 and less than 10?

easy

A. arr[arr != 0 & arr < 10]

B. arr[(arr != 0) & (arr < 10)]

C. arr[(arr != 0) | (arr < 10)]

D. arr[~arr != 0 & arr < 10]

Solution

1. Step 1: Use parentheses for each condition

   Each condition must be enclosed in parentheses: (arr != 0) and (arr < 10).

2. Step 2: Combine with AND operator

   Use & to combine conditions for selecting elements satisfying both.

3. Final Answer:

   arr[(arr != 0) & (arr < 10)] -> Option B

4. Quick Check:

   Parentheses + & + correct conditions = syntax correct [OK]

Hint: Use parentheses around each condition and '&' for AND [OK]

Common Mistakes:

• Missing parentheses causing syntax errors
• Using bitwise NOT (~) incorrectly
• Using Python 'and' instead of '&'

3. Given the code:

import numpy as np
arr = np.array([1, 5, 8, 12, 3, 7])
result = arr[(arr > 3) | (arr == 1)]
print(result)

What is the output?

medium

A. [5 8 12 7]

B. [1 5 8 12 3 7]

C. [5 8 12]

D. [1 5 8 12 7]

Solution

1. Step 1: Evaluate each condition on the array

   arr > 3 is True for 5, 8, 12, 7; arr == 1 is True for 1.

2. Step 2: Combine conditions with OR operator

   Elements where either condition is True are selected: 1, 5, 8, 12, 7.

3. Final Answer:

   [1 5 8 12 7] -> Option D

4. Quick Check:

   OR condition selects 1 and all >3 values [OK]

Hint: OR (|) selects elements matching either condition [OK]

Common Mistakes:

• Forgetting to include elements equal to 1
• Using AND (&) instead of OR (|)
• Misreading the array values

4. What is wrong with this code snippet?

import numpy as np
arr = np.array([2, 4, 6, 8])
filtered = arr[arr > 3 && arr < 8]
print(filtered)

medium

A. Missing parentheses around conditions

B. Using Python 'and' instead of '&'

C. Using '&&' instead of '&' for combining conditions

D. No error, code runs fine

Solution

1. Step 1: Identify operator error

   NumPy uses bitwise operators '&' and '|' for element-wise logical operations, not '&&'.

2. Step 2: Correct operator usage

   Replace '&&' with '&' and add parentheses around each condition.

3. Final Answer:

   Using '&&' instead of '&' for combining conditions -> Option C

4. Quick Check:

   '&&' is invalid in NumPy, use '&' with parentheses [OK]

Hint: Use '&' not '&&' for NumPy condition combining [OK]

Common Mistakes:

• Using '&&' from other languages
• Not adding parentheses around conditions
• Using Python 'and' instead of '&'

5. You have a NumPy array data = np.array([10, 15, 20, 25, 30, 35]). You want to select elements that are either less than 20 or greater than or equal to 30, but NOT equal to 15. Which code correctly filters data?

hard

A. data[((data < 20) | (data >= 30)) & (data != 15)]

B. data[(data < 20) | (data >= 30) & (data != 15)]

C. data[(data < 20) & (data >= 30) & (data != 15)]

D. data[~((data < 20) | (data >= 30) & (data == 15))]

Solution

1. Step 1: Combine OR conditions inside parentheses

   Use (data < 20) | (data >= 30) to select elements less than 20 or greater or equal to 30.

2. Step 2: Exclude elements equal to 15 with AND

   Combine with & (data != 15) to exclude 15.

3. Final Answer:

   data[((data < 20) | (data >= 30)) & (data != 15)] -> Option A

4. Quick Check:

   Parentheses + OR + AND + NOT = correct filter [OK]

Hint: Group OR conditions, then AND with NOT condition [OK]

Common Mistakes:

• Missing parentheses causing wrong precedence
• Using AND instead of OR for first condition
• Incorrect negation of 15