np.take() and np.put() for advanced selection in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select elements from array 'a' at indices 1 and 3 using np.take().

NumPy

import numpy as np

a = np.array([10, 20, 30, 40, 50])
indices = [1, 3]
selected = np.[1](a, indices)
print(selected)

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

Atake

Bput

Cselect

Dchoose

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.put() instead of np.take() for selection.

Trying to use np.select() which is for conditions.

np.take() selects elements from an array at specified indices.

2fill in blank

medium

Complete the code to replace elements at indices 0 and 2 in array 'a' with values 100 and 200 using np.put().

NumPy

import numpy as np

a = np.array([1, 2, 3, 4, 5])
indices = [0, 2]
values = [100, 200]
np.[1](a, indices, values)
print(a)

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

Aput

Btake

Cinsert

Dreplace

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.take() which only selects elements.

Trying to use np.insert() which inserts elements shifting others.

np.put() replaces elements at given indices with new values.

3fill in blank

hard

Fix the error in the code to correctly select elements at indices 2 and 4 from array 'a' using np.take().

NumPy

import numpy as np

a = np.array([5, 10, 15, 20, 25])
indices = (2, 4)
selected = np.[1](a, indices)
print(selected)

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

Aput

Btake

Cget

Dfetch

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.put() which is for assignment, not selection.

Using non-existent functions like np.get() or np.fetch().

np.take() accepts tuples or lists for indices to select elements.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each word to its length only if the length is greater than 3.

NumPy

words = ['apple', 'bat', 'cat', 'dog', 'elephant']
lengths = {word: [1] for word in words if [2]

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 word instead of len(word) for the value.

Using word > 3 which compares string to number.

We map each word to its length (len(word)) only if length is greater than 3 (len(word) > 3).

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their values only if the value is positive.

NumPy

data = {'a': 1, 'b': -2, 'c': 3}
result = { [1]: [2] for k, v in data.items() if v [3] 0 }

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

Ak.upper()

Bv

C>

Dk.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using k.lower() instead of k.upper().

Using v < 0 which filters negative values.

We map uppercase keys (k.upper()) to their values (v) only if value is greater than zero (v > 0).

Practice

1. What does np.take() do in NumPy?

easy

A. Selects elements from an array using specified indices

B. Changes elements in an array at specified indices

C. Sorts the elements of an array

D. Creates a new array filled with zeros

Solution

1. Step 1: Understand the function purpose

   np.take() is used to pick elements from an array by their index positions.

2. Step 2: Compare with other options

   Only Selects elements from an array using specified indices describes selecting elements by indices, while others describe different functions.

3. Final Answer:

   Selects elements from an array using specified indices -> Option A

4. Quick Check:

   np.take() = select elements [OK]

Hint: np.take() picks by index, np.put() changes by index [OK]

Common Mistakes:

• Confusing np.take() with np.put()
• Thinking np.take() modifies the array
• Mixing np.take() with sorting functions

2. Which of the following is the correct syntax to replace elements at indices [1, 3] in array a with values [10, 20] using np.put()?

easy

A. np.put(a, [1, 3], [10, 20])

B. np.put([1, 3], a, [10, 20])

C. np.put(a, [10, 20], [1, 3])

D. np.put(a, 10, [1, 3, 20])

Solution

1. Step 1: Recall np.put() syntax

   The correct syntax is np.put(array, indices, values) to replace elements at given indices.

2. Step 2: Match syntax with options

   np.put(a, [1, 3], [10, 20]) matches the correct order: array, indices, values.

3. Final Answer:

   np.put(a, [1, 3], [10, 20]) -> Option A

4. Quick Check:

   np.put(array, indices, values) [OK]

Hint: np.put(array, indices, values) replaces elements [OK]

Common Mistakes:

• Swapping the order of arguments
• Passing values as indices
• Using wrong data types for indices or values

3. What is the output of the following code?

import numpy as np
a = np.array([5, 10, 15, 20, 25])
indices = [0, 2, 4]
result = np.take(a, indices)
print(result)

medium

A. [10 20 25]

B. [5 15 25]

C. [5 10 15]

D. [0 2 4]

Solution

1. Step 1: Understand np.take() with given indices

   np.take(a, [0, 2, 4]) selects elements at positions 0, 2, and 4 from array a.

2. Step 2: Extract elements from array

   Elements at these positions are 5 (index 0), 15 (index 2), and 25 (index 4).

3. Final Answer:

   [5 15 25] -> Option B

4. Quick Check:

   np.take() picks elements by index [OK]

Hint: np.take() returns elements at given indices [OK]

Common Mistakes:

• Confusing indices with values
• Expecting output as original array
• Mixing up index positions

4. Identify the error in this code snippet:

import numpy as np
a = np.array([1, 2, 3, 4])
np.put(a, [1, 4], [10, 20])
print(a)

medium

A. Syntax error in np.put() usage

B. Values list length does not match indices length

C. Index 4 is out of bounds for array of size 4

D. np.put() cannot modify arrays in-place

Solution

1. Step 1: Check array size and indices

   Array a has size 4, valid indices are 0 to 3. Index 4 is invalid.

2. Step 2: Understand np.put() behavior

   np.put() tries to assign values at given indices. Using index 4 causes an IndexError.

3. Final Answer:

   Index 4 is out of bounds for array of size 4 -> Option C

4. Quick Check:

   Index error due to invalid index [OK]

Hint: Check indices are within array size before np.put() [OK]

Common Mistakes:

• Ignoring array size limits
• Assuming np.put() auto-expands array
• Confusing index and value positions

5. Given a = np.array([1, 2, 3, 4, 5]), how can you use np.put() and np.take() together to replace elements at indices [0, 2] with [10, 20] and then retrieve these updated elements?

hard

A. np.take(a, [10, 20]); np.put(a, [0, 2])

B. np.take(a, [0, 2], [10, 20]); np.put(a, [0, 2])

C. np.put([0, 2], a, [10, 20]); np.take([0, 2], a)

D. np.put(a, [0, 2], [10, 20]); np.take(a, [0, 2])

Solution

1. Step 1: Use np.put() to update elements

   np.put(a, [0, 2], [10, 20]) replaces elements at indices 0 and 2 with 10 and 20.

2. Step 2: Use np.take() to retrieve updated elements

   np.take(a, [0, 2]) returns the updated elements at those indices.

3. Final Answer:

   np.put(a, [0, 2], [10, 20]); np.take(a, [0, 2]) -> Option D

4. Quick Check:

   Put updates, take retrieves updated values [OK]

Hint: Put first to update, then take to get new values [OK]

Common Mistakes:

• Mixing argument order in np.put()
• Using np.take() to update values
• Confusing arrays and indices in functions