np.array() from Python lists in NumPy - Mini Project: Build & Apply

Create a NumPy Array from Python Lists

📖 Scenario: You work in a small bakery that tracks daily sales of different bread types. The sales data is recorded as Python lists for each day.You want to use NumPy to analyze this data more easily.

🎯 Goal: Create a NumPy array from the given Python lists of daily bread sales.

📋 What You'll Learn

Use the np.array() function to convert Python lists into a NumPy array.

Create the array exactly from the provided lists.

Print the resulting NumPy array.

💡 Why This Matters

🌍 Real World

In many jobs, data comes as lists or tables. Converting these into NumPy arrays helps with fast calculations and analysis.

💼 Career

Data scientists and analysts often convert raw data into arrays to prepare for statistical analysis, machine learning, or visualization.

1

Create Python lists for daily sales

Create two Python lists called day1_sales and day2_sales with these exact values: day1_sales = [10, 15, 7] and day2_sales = [12, 18, 9].

NumPy

# Create the Python lists day1_sales and day2_sales with the exact values
# Your code here

Hint

Use square brackets [] to create lists with the exact numbers.

2

Import NumPy library

Import the NumPy library using the standard alias np.

NumPy

day1_sales = [10, 15, 7]
day2_sales = [12, 18, 9]

# Import NumPy as np
# Your code here

Hint

Use import numpy as np to import the library.

3

Create a NumPy array from the lists

Use np.array() to create a NumPy array called sales_array from the two lists day1_sales and day2_sales combined inside another list.

NumPy

import numpy as np

day1_sales = [10, 15, 7]
day2_sales = [12, 18, 9]

# Create sales_array using np.array() from [day1_sales, day2_sales]
# Your code here

Hint

Pass a list containing day1_sales and day2_sales to np.array().

4

Print the NumPy array

Print the variable sales_array to display the NumPy array of sales data.

NumPy

import numpy as np

day1_sales = [10, 15, 7]
day2_sales = [12, 18, 9]

sales_array = np.array([day1_sales, day2_sales])

# Print sales_array
# Your code here

Hint

Use print(sales_array) to show the array.

Practice

1. What does np.array() do when given a Python list?

easy

A. It converts the list into a numpy array for easier math operations.

B. It changes the list into a Python dictionary.

C. It sorts the list in ascending order.

D. It removes duplicates from the list.

Solution

1. Step 1: Understand the purpose of np.array()

   np.array() is designed to convert Python lists into numpy arrays.

2. Step 2: Recognize the benefit of numpy arrays

   Numpy arrays allow fast, element-wise math operations that lists do not support.

3. Final Answer:

   It converts the list into a numpy array for easier math operations. -> Option A

4. Quick Check:

   np.array() converts lists to arrays [OK]

Hint: np.array() turns lists into arrays for math [OK]

Common Mistakes:

• Thinking np.array() sorts the list
• Confusing arrays with dictionaries
• Assuming it removes duplicates

2. Which of the following is the correct syntax to create a numpy array from a Python list [1, 2, 3]?

easy

A. np.array{1, 2, 3}

B. np.array[[1, 2, 3]]

C. np.array(1, 2, 3)

D. np.array([1, 2, 3])

Solution

1. Step 1: Recall correct function call syntax

   np.array() requires parentheses and a list inside, like np.array([1, 2, 3]).

2. Step 2: Identify syntax errors in other options

   np.array{1, 2, 3} uses curly braces which is invalid; C passes multiple arguments instead of one list; D uses double brackets incorrectly.

3. Final Answer:

   np.array([1, 2, 3]) -> Option D

4. Quick Check:

   np.array() needs a list inside parentheses [OK]

Hint: Use parentheses and a list inside for np.array() [OK]

Common Mistakes:

• Using curly braces instead of parentheses
• Passing multiple arguments instead of a single list
• Using double brackets incorrectly

3. What will be the output of this code?

import numpy as np
lst = [[1, 2], [3, 4]]
arr = np.array(lst)
print(arr.shape)

medium

A. (1, 4)

B. (4,)

C. (2, 2)

D. Error

Solution

1. Step 1: Understand the input list shape

   The list has 2 sublists, each with 2 elements, so shape is 2 rows and 2 columns.

2. Step 2: Check numpy array shape property

   np.array converts nested lists into 2D arrays with shape (2, 2).

3. Final Answer:

   (2, 2) -> Option C

4. Quick Check:

   Nested list shape = (2, 2) [OK]

Hint: Shape matches nested list dimensions [OK]

Common Mistakes:

• Thinking shape is (4,)
• Assuming shape is (1, 4)
• Expecting an error for nested lists

4. What is wrong with this code snippet?

import numpy as np
lst = [1, 2, 3]
arr = np.array(lst, 5)
print(arr)

medium

A. The list contains integers which are not allowed.

B. np.array() does not take a second positional argument like 5.

C. The print statement is missing parentheses.

D. The list must be nested to convert to an array.

Solution

1. Step 1: Check np.array() function signature

   np.array() takes the data as the first argument; a second positional argument like 5 is invalid.

2. Step 2: Identify the error caused by extra argument

   Passing 5 as a second positional argument causes a TypeError.

3. Final Answer:

   np.array() does not take a second positional argument like 5. -> Option B

4. Quick Check:

   Extra positional arguments cause error [OK]

Hint: np.array() takes one main argument: the list [OK]

Common Mistakes:

• Thinking list must be nested
• Forgetting print() needs parentheses (Python 3)
• Believing integers are not allowed in arrays

5. You have a list of lists representing daily temperatures for a week:

temps = [[20, 22, 19], [21, 23, 20], [19, 21, 18], [22, 24, 21], [20, 22, 19], [18, 20, 17], [21, 23, 20]]

How can you convert this into a numpy array and find the average temperature for each day?

hard

A. import numpy as np
temps_arr = np.array(temps)
daily_avg = temps_arr.mean(axis=1)
print(daily_avg)

B. import numpy as np
temps_arr = np.array(temps)
daily_avg = temps_arr.mean(axis=0)
print(daily_avg)

C. import numpy as np
daily_avg = np.array(temps).sum()
print(daily_avg)

D. import numpy as np
temps_arr = np.array(temps)
daily_avg = temps_arr.max(axis=1)
print(daily_avg)

Solution

1. Step 1: Convert list of lists to numpy array

   Use np.array(temps) to create a 2D array where each row is a day.

2. Step 2: Calculate average temperature per day

   Use mean(axis=1) to compute average across columns (hours) for each row (day).

3. Final Answer:

   import numpy as np temps_arr = np.array(temps) daily_avg = temps_arr.mean(axis=1) print(daily_avg) -> Option A

4. Quick Check:

   mean(axis=1) averages rows (days) [OK]

Hint: Use mean(axis=1) to average rows (days) [OK]

Common Mistakes:

• Using mean(axis=0) which averages columns (hours)
• Using sum() without axis for average
• Using max() instead of mean()