np.unique() for unique elements in NumPy - Mini Project: Build & Apply

Find Unique Elements Using np.unique()

📖 Scenario: You work in a store and have a list of product IDs sold today. Some products were sold multiple times.You want to find out which unique products were sold to understand your sales better.

🎯 Goal: Build a small program that uses np.unique() to find unique product IDs from a list.

📋 What You'll Learn

Create a numpy array called product_ids with the exact values: [101, 203, 101, 405, 203, 507]

Create a variable called unique_products to store unique product IDs using np.unique()

Print the unique_products array to see the unique product IDs

💡 Why This Matters

🌍 Real World

Finding unique items in sales data helps stores understand what products are popular and manage inventory better.

💼 Career

Data scientists often need to clean and analyze data by identifying unique values to prepare datasets for further analysis.

1

Create the product IDs array

Create a numpy array called product_ids with these exact values: [101, 203, 101, 405, 203, 507]

NumPy

import numpy as np

# Create the product_ids array with the given values
# Your code here

Hint

Use np.array() to create the array with the exact list of numbers.

2

Use np.unique() to find unique product IDs

Create a variable called unique_products and assign it the result of np.unique(product_ids) to find unique product IDs.

NumPy

import numpy as np

product_ids = np.array([101, 203, 101, 405, 203, 507])

# Use np.unique() on product_ids and store in unique_products
# Your code here

Hint

Call np.unique() with product_ids inside the parentheses.

3

Print the unique product IDs

Write a print statement to display the unique_products array.

NumPy

import numpy as np

product_ids = np.array([101, 203, 101, 405, 203, 507])

unique_products = np.unique(product_ids)

# Print the unique_products array
# Your code here

Hint

Use print(unique_products) to show the unique product IDs.

4

Complete program to find and print unique product IDs

Combine all previous steps to create a complete program that imports numpy, creates the product_ids array, finds unique products with np.unique(), and prints the result.

NumPy

import numpy as np

product_ids = np.array([101, 203, 101, 405, 203, 507])

unique_products = np.unique(product_ids)

print(unique_products)

# Program complete

Hint

Run the full program to see the unique product IDs printed.

Practice

1. What does the np.unique() function do when applied to a NumPy array?

easy

A. Returns the shape of the array

B. Returns the sum of all elements in the array

C. Returns the maximum value in the array

D. Returns all unique elements sorted from the array

Solution

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

   The function np.unique() extracts all different values from the input array and sorts them.

2. Step 2: Compare with other options

   Options A, B, and D describe different functions like shape, sum, and max, which are not what np.unique() does.

3. Final Answer:

   Returns all unique elements sorted from the array -> Option D

4. Quick Check:

   np.unique() = unique sorted elements [OK]

Hint: np.unique() always returns sorted unique values [OK]

Common Mistakes:

• Thinking it returns counts by default
• Confusing with sum or max functions
• Assuming it returns unsorted unique values

2. Which of the following is the correct syntax to get unique elements from a NumPy array arr?

easy

A. np.unique(arr)

B. arr.unique()

C. unique(arr)

D. np.arr.unique()

Solution

1. Step 1: Recall the correct function call

   The correct way to call the unique function in NumPy is np.unique(arr).

2. Step 2: Identify incorrect syntax

   Options A, B, and C are invalid because either the method does not exist on the array object or the function is not called from the NumPy module correctly.

3. Final Answer:

   np.unique(arr) -> Option A

4. Quick Check:

   Use np.unique(array) syntax [OK]

Hint: Always call unique as np.unique(array) [OK]

Common Mistakes:

• Trying to call unique as a method on array
• Forgetting the np. prefix
• Using a non-existent unique() function without np

3. What is the output of the following code?

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

medium

A. [4 3 2 1]

B. [3 1 2 4]

C. [1 2 3 4]

D. [1 1 2 2 3 3 4]

Solution

1. Step 1: Apply np.unique() to the array

   The function extracts unique values from the array: 1, 2, 3, and 4.

2. Step 2: Note the sorting behavior

   np.unique() returns these unique values sorted in ascending order: [1 2 3 4].

3. Final Answer:

   [1 2 3 4] -> Option C

4. Quick Check:

   Unique sorted values = [1 2 3 4] [OK]

Hint: np.unique() sorts unique values automatically [OK]

Common Mistakes:

• Expecting original order instead of sorted
• Including duplicates in output
• Confusing with counts output

4. The following code is intended to print unique elements of arr but raises an error. What is the error?

import numpy as np
arr = np.array([5, 6, 5, 7])
result = arr.unique()
print(result)

medium

A. 'numpy.ndarray' object has no attribute 'unique'

B. SyntaxError: invalid syntax

C. TypeError: unique() missing 1 required positional argument

D. NameError: name 'unique' is not defined

Solution

1. Step 1: Identify the method call on the array

   The code calls arr.unique(), but NumPy arrays do not have a method named unique().

2. Step 2: Understand the correct usage

   The correct function is np.unique(arr), a function in the NumPy module, not a method of the array object.

3. Final Answer:

   'numpy.ndarray' object has no attribute 'unique' -> Option A

4. Quick Check:

   Arrays have no unique() method [OK]

Hint: np.unique() is a function, not an array method [OK]

Common Mistakes:

• Calling unique() as a method on array
• Forgetting to import numpy as np
• Using wrong function name or syntax

5. Given a 2D NumPy array arr = np.array([[1, 2, 2], [3, 1, 4]]), which code correctly finds all unique elements in the entire array?

hard

A. np.unique(arr, axis=0)

B. np.unique(arr)

C. np.unique(arr, axis=1)

D. arr.unique()

Solution

1. Step 1: Understand np.unique() on 2D arrays

   Calling np.unique(arr) flattens the array and returns all unique elements sorted.

2. Step 2: Check axis parameter effects

   Using axis=0 or axis=1 returns unique rows or columns, not unique elements overall.

3. Step 3: Identify invalid method call

   arr.unique() is invalid because arrays do not have a unique method.

4. Final Answer:

   np.unique(arr) -> Option B

5. Quick Check:

   np.unique(array) finds all unique elements [OK]

Hint: Use np.unique(arr) to get all unique elements in any array [OK]

Common Mistakes:

• Using axis parameter expecting unique elements, but it returns unique rows/columns
• Calling unique() as a method on array
• Confusing unique elements with unique rows or columns