np.arange() for range arrays in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a NumPy array from 0 to 4 using np.arange().

NumPy

import numpy as np
arr = np.arange([1])
print(arr)

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

A5

B10

C6

D4

Attempts:

3 left

💡 Hint

Common Mistakes

Using 4 instead of 5 will create array up to 3 only.

Confusing np.arange() with range() which behaves similarly but returns a list.

np.arange(5) creates an array starting at 0 up to but not including 5, so it includes 0,1,2,3,4.

2fill in blank

medium

Complete the code to create a NumPy array from 2 to 6 (excluding 6) using np.arange().

NumPy

import numpy as np
arr = np.arange([1], 6)
print(arr)

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

A0

B2

C1

D5

Attempts:

3 left

💡 Hint

Common Mistakes

Using 0 or 1 as start will include unwanted numbers.

Forgetting that the stop value is excluded.

np.arange(2, 6) creates an array starting at 2 up to but not including 6, so it includes 2,3,4,5.

3fill in blank

hard

Fix the error in the code to create an array from 1 to 10 with step 2 using np.arange().

NumPy

import numpy as np
arr = np.arange(1, 10, [1])
print(arr)

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

A3

B1

C2

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using step 0 causes an error.

Using step 1 gives all numbers, not skipping.

The step argument controls the gap between numbers. Step 2 means numbers increase by 2 each time.

4fill in blank

hard

Fill both blanks to create an array from 10 down to 2 (excluding 2) with step -2 using np.arange().

NumPy

import numpy as np
arr = np.arange([1], [2], -2)
print(arr)

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

A10

B2

C1

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using stop greater than start with negative step results in empty array.

Confusing stop value inclusion.

To count down from 10 to 2 (excluding 2) with step -2, start=10 and stop=2.

5fill in blank

hard

Fill all three blanks to create a NumPy array of even numbers from 0 to 8 using np.arange().

NumPy

import numpy as np
arr = np.arange([1], [2], [3])
print(arr)

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

A0

B10

C2

D8

Attempts:

3 left

💡 Hint

Common Mistakes

Using stop as 8 excludes 8 itself.

Using step 1 gives all numbers, not just even.

Start at 0, stop before 10, step by 2 to get even numbers 0,2,4,6,8.

Practice

1. What does np.arange(3) produce?

easy

A. [0, 1, 2]

B. [1, 2, 3]

C. [0, 1, 2, 3]

D. [3]

Solution

1. Step 1: Understand default start value

   If only one number is given, np.arange starts from 0 by default.

2. Step 2: Identify stop value exclusion

   The stop value 3 is excluded, so the array includes 0, 1, 2.

3. Final Answer:

   [0, 1, 2] -> Option A

4. Quick Check:

   Start=0, stop=3 excluded, so [0,1,2] [OK]

Hint: Remember: stop value is NOT included in output [OK]

Common Mistakes:

• Including the stop value in the array
• Starting from 1 instead of 0
• Confusing step with stop

2. Which of these is the correct syntax to create an array from 2 to 6 (excluding 6) with step 1 using np.arange()?

easy

A. np.arange(6, 2, 1)

B. np.arange(2, 6, 0)

C. np.arange(2, 7)

D. np.arange(2, 6, 1)

Solution

1. Step 1: Check start, stop, and step order

   Start should be less than stop for positive step; step cannot be zero.

2. Step 2: Validate each option

   np.arange(2, 6, 1) uses start=2, stop=6, step=1 correctly. np.arange(6, 2, 1) reverses start and stop. np.arange(2, 7) sets stop=7, producing [2 3 4 5 6] which includes 6. np.arange(2, 6, 0) has step=0 which is invalid.

3. Final Answer:

   np.arange(2, 6, 1) -> Option D

4. Quick Check:

   Start=2, stop=6, step=1 is correct syntax [OK]

Hint: Step must not be zero; start < stop for positive step [OK]

Common Mistakes:

• Using zero as step value
• Reversing start and stop values
• Using wrong stop value

3. What is the output of this code?

import numpy as np
arr = np.arange(1, 10, 3)
print(arr)

medium

A. [1 4 7]

B. [1 3 6 9]

C. [1 2 3 4 5 6 7 8 9]

D. [3 6 9]

Solution

1. Step 1: Understand parameters of np.arange

   Start=1, stop=10 (excluded), step=3 means numbers start at 1 and increase by 3 until less than 10.

2. Step 2: Calculate values

   Values are 1, 4 (1+3), 7 (4+3). Next would be 10 which is excluded.

3. Final Answer:

   [1 4 7] -> Option A

4. Quick Check:

   Start=1, step=3, stop=10 excluded gives [1,4,7] [OK]

Hint: Add step repeatedly until reaching stop (excluded) [OK]

Common Mistakes:

• Including stop value 10
• Adding step incorrectly
• Confusing step with stop

4. What is wrong with this code?

import numpy as np
arr = np.arange(5, 2, 1)
print(arr)

medium

A. It raises a ValueError

B. It produces an empty array

C. It produces [5, 4, 3]

D. It produces [2, 3, 4, 5]

Solution

1. Step 1: Analyze start, stop, and step values

   Start=5, stop=2, step=1 means counting up from 5 to less than 2, which is impossible.

2. Step 2: Understand np.arange behavior

   Since step is positive but start > stop, no values satisfy condition, so result is empty array.

3. Final Answer:

   It produces an empty array -> Option B

4. Quick Check:

   Positive step with start > stop gives empty array [OK]

Hint: Positive step needs start < stop to produce values [OK]

Common Mistakes:

• Expecting reversed array without negative step
• Thinking it raises error
• Confusing start and stop order

5. You want to create an array starting at 10, decreasing by 2, stopping before 0. Which np.arange() call is correct?

hard

A. np.arange(0, 10, -2)

B. np.arange(10, 0, 2)

C. np.arange(10, 0, -2)

D. np.arange(0, 10, 2)

Solution

1. Step 1: Identify start, stop, and step for decreasing sequence

   Start=10, stop=0 (excluded), step must be negative to decrease.

2. Step 2: Check each option

   np.arange(10, 0, -2) uses step=-2 correctly. np.arange(10, 0, 2) has positive step, so no values. Options C and D start at 0, which is not desired.

3. Final Answer:

   np.arange(10, 0, -2) -> Option C

4. Quick Check:

   Decreasing sequence needs negative step [OK]

Hint: Use negative step to count down in np.arange [OK]

Common Mistakes:

• Using positive step for decreasing sequence
• Swapping start and stop values
• Starting at stop value instead of start