Array arithmetic (element-wise) in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to add two arrays element-wise.

Data Analysis Python

import numpy as np

arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])
result = arr1 [1] arr2
print(result)

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

A+

B-

C*

D/

Attempts:

3 left

💡 Hint

Common Mistakes

Using '-' instead of '+' causes subtraction, not addition.

Using '*' multiplies element-wise, not adds.

Using the + operator adds two arrays element-wise in NumPy.

2fill in blank

medium

Complete the code to multiply two arrays element-wise.

Data Analysis Python

import numpy as np

arr1 = np.array([2, 4, 6])
arr2 = np.array([1, 3, 5])
result = arr1 [1] arr2
print(result)

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

A+

B//

C*

D-

Attempts:

3 left

💡 Hint

Common Mistakes

Using '+' adds arrays instead of multiplying.

Using '//' performs integer division, not multiplication.

The * operator multiplies arrays element-wise in NumPy.

3fill in blank

hard

Fix the error in the code to subtract two arrays element-wise.

Data Analysis Python

import numpy as np

arr1 = np.array([10, 20, 30])
arr2 = np.array([1, 2, 3])
result = arr1 [1] arr2
print(result)

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

A+

B-

C*

D/

Attempts:

3 left

💡 Hint

Common Mistakes

Using '+' adds arrays instead of subtracting.

Using '*' multiplies arrays instead of subtracting.

The - operator subtracts arrays element-wise in NumPy.

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.

Data Analysis Python

words = ['apple', 'bat', 'carrot', 'dog']
lengths = {word: [1] for word in words if len(word) [2] 3}
print(lengths)

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

Alen(word)

B>

C<

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' filters words shorter than 3 characters.

Using 'word' instead of 'len(word)' gives the word itself, not its length.

The dictionary comprehension uses len(word) to get the length and filters words with length greater than 3 using >.

5fill in blank

hard

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

Data Analysis Python

words = ['apple', 'bat', 'carrot', 'dog']
result = { [1]: [2] for word in words if len(word) [3] 3 }
print(result)

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

Aword.upper()

Blen(word)

C>

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'word' instead of 'word.upper()' for keys.

Using '<' instead of '>' for filtering.

The dictionary comprehension uses word.upper() as keys, len(word) as values, and filters words longer than 3 with >.

Practice

1. What does element-wise addition of two arrays mean in simple terms?

easy

A. Combining the arrays end to end without any math

B. Adding each number in one array to the corresponding number in the other array

C. Multiplying each number in one array by the total sum of the other array

D. Adding all numbers in both arrays together as a single sum

Solution

1. Step 1: Understand element-wise operation

   Element-wise means doing the operation on each pair of matching positions in two arrays.

2. Step 2: Apply to addition

   For addition, each number in the first array is added to the number in the same position in the second array.

3. Final Answer:

   Adding each number in one array to the corresponding number in the other array -> Option B

4. Quick Check:

   Element-wise addition = add matching elements [OK]

Hint: Think pair by pair addition, not total sums [OK]

Common Mistakes:

• Confusing element-wise with total sum
• Thinking arrays are joined instead of added
• Mixing addition with multiplication

2. Which of the following is the correct syntax to add two NumPy arrays a and b element-wise?

easy

A. c = a + b

B. c = a.add(b)

C. c = add(a, b)

D. c = a & b

Solution

1. Step 1: Recall NumPy addition syntax

   NumPy supports element-wise addition using the + operator directly between arrays.

2. Step 2: Check options

   c = a + b uses a + b, which is correct. c = a.add(b) is invalid syntax. c = add(a, b) requires importing add function explicitly. c = a & b uses bitwise AND, not addition.

3. Final Answer:

   c = a + b -> Option A

4. Quick Check:

   Use + for element-wise addition in NumPy [OK]

Hint: Use + operator for element-wise addition in NumPy [OK]

Common Mistakes:

• Using bitwise operators instead of +
• Trying to call add as a method on array
• Forgetting to import add function if used

3. What is the output of this code?

import numpy as np
x = np.array([1, 2, 3])
y = np.array([4, 5, 6])
z = x * y
print(z)

medium

A. [4 5 6]

B. [5 7 9]

C. [4 10 18]

D. [1 2 3 4 5 6]

Solution

1. Step 1: Understand element-wise multiplication

   Multiplying two arrays with * multiplies each element in the first array by the corresponding element in the second array.

2. Step 2: Calculate each element

   1*4=4, 2*5=10, 3*6=18, so the result is [4, 10, 18].

3. Final Answer:

   [4 10 18] -> Option C

4. Quick Check:

   Element-wise multiply = multiply matching elements [OK]

Hint: Multiply arrays element by element with * operator [OK]

Common Mistakes:

• Adding instead of multiplying
• Concatenating arrays instead of multiplying
• Confusing output format with list instead of array

4. The following code throws an error. What is the main reason?

import numpy as np
x = np.array([1, 2, 3])
y = np.array([4, 5])
z = x + y
print(z)

medium

A. You forgot to convert arrays to lists first

B. You must use np.add() instead of + operator

C. The print statement syntax is incorrect

D. Arrays have different sizes, so element-wise addition is not possible

Solution

1. Step 1: Check array sizes

   Array x has 3 elements, y has 2 elements. Element-wise operations require arrays to be the same size or broadcastable.

2. Step 2: Understand error cause

   Since sizes differ and no broadcasting applies here, addition fails with a ValueError.

3. Final Answer:

   Arrays have different sizes, so element-wise addition is not possible -> Option D

4. Quick Check:

   Array sizes must match for element-wise ops [OK]

Hint: Check array lengths before element-wise operations [OK]

Common Mistakes:

• Assuming + works regardless of size
• Thinking np.add fixes size mismatch
• Blaming print syntax for error

5. You have two arrays representing daily sales for two stores:

store1 = np.array([10, 20, 30, 40])
store2 = np.array([5, 15, 25, 35])

You want to find the total sales per day by adding these arrays element-wise. Then, you want to apply a 10% tax on the total sales. Which code correctly does this?

hard

A. total = store1 + store2
final = total * 1.10
print(final)

B. total = store1 + store2
final = total + 0.10
print(final)

C. total = store1 * store2
final = total * 1.10
print(final)

D. final = (store1 + store2) / 1.10
print(final)

Solution

1. Step 1: Calculate total sales element-wise

   Add store1 and store2 arrays element-wise using + operator to get daily totals.

2. Step 2: Apply 10% tax

   Multiply the total sales array by 1.10 to add 10% tax to each day's total.

3. Final Answer:

   total = store1 + store2 final = total * 1.10 print(final) -> Option A

4. Quick Check:

   Add then multiply by 1.10 for tax [OK]

Hint: Add arrays first, then multiply by 1.10 for tax [OK]

Common Mistakes:

• Adding 0.10 instead of multiplying by 1.10
• Multiplying arrays instead of adding
• Dividing instead of multiplying for tax