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

Finding Unique Values with np.unique()

📖 Scenario: You work in a store that tracks daily sales of different fruits. Sometimes the same fruit is sold multiple times in a day. You want to find out which unique fruits were sold today.

🎯 Goal: Build a small program that uses np.unique() to find all unique fruits sold from a list of sales.

📋 What You'll Learn

Create a numpy array called sales with the exact fruit names given.

Create a variable called unique_fruits that stores the unique fruit names using np.unique().

Print the unique_fruits array to see the result.

💡 Why This Matters

🌍 Real World

Stores and businesses often need to find unique items sold or listed to analyze inventory or sales trends.

💼 Career

Data analysts and scientists use <code>np.unique()</code> to quickly find unique values in datasets for reporting and decision making.

1

Create the sales data array

Create a numpy array called sales with these exact fruit names in this order: 'apple', 'banana', 'apple', 'orange', 'banana', 'kiwi'.

NumPy

import numpy as np

# Create the numpy array called sales with the given fruits
# Your code here

Hint

Use np.array([...]) to create the array with the exact fruit names.

2

Set up the variable for unique fruits

Create a variable called unique_fruits and set it to None for now as a placeholder.

NumPy

import numpy as np

sales = np.array(['apple', 'banana', 'apple', 'orange', 'banana', 'kiwi'])

# Create the variable unique_fruits and set it to None
# Your code here

Hint

This step just prepares the variable. We will update it next.

3

Find unique fruits using np.unique()

Use np.unique() on the sales array and assign the result to the variable unique_fruits.

NumPy

import numpy as np

sales = np.array(['apple', 'banana', 'apple', 'orange', 'banana', 'kiwi'])

unique_fruits = None

# Use np.unique() on sales and assign to unique_fruits
# Your code here

Hint

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

4

Print the unique fruits

Print the variable unique_fruits to display the unique fruit names.

NumPy

import numpy as np

sales = np.array(['apple', 'banana', 'apple', 'orange', 'banana', 'kiwi'])

unique_fruits = np.unique(sales)

# Print the unique_fruits array
# Your code here

Hint

Use print(unique_fruits) to show the unique fruits.

Practice

1. What does the np.unique() function do in NumPy?

easy

A. Calculates the sum of all elements

B. Sorts the array in descending order

C. Reverses the order of elements

D. Finds all unique values in an array

Solution

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

   This function is designed to find all different (unique) values in a NumPy array or list.

2. Step 2: Compare with other options

   Sorting, summing, or reversing are different operations and not what np.unique() does.

3. Final Answer:

   Finds all unique values in an array -> Option D

4. Quick Check:

   np.unique() = unique values [OK]

Hint: Remember: unique means different values only [OK]

Common Mistakes:

• Confusing unique with sorting
• Thinking it sums values
• Assuming it reverses array

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

easy

A. np.arr.unique()

B. np.unique(arr)

C. unique(arr)

D. arr.unique()

Solution

1. Step 1: Recall the correct function call

   The function unique is part of the NumPy module and is called as np.unique().

2. Step 2: Check other options for errors

   arr.unique() is not a NumPy array method, unique(arr) misses the module prefix, and np.arr.unique() is invalid syntax.

3. Final Answer:

   np.unique(arr) -> Option B

4. Quick Check:

   Correct syntax = np.unique(arr) [OK]

Hint: Use np.unique(array) always [OK]

Common Mistakes:

• Calling unique as method on array
• Missing np prefix
• Wrong module usage

3. What is the output of this code?

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

medium

A. [1 2 3 4]

B. [3 1 2 4]

C. [4 3 2 1]

D. [1 1 2 2 3 3 4]

Solution

1. Step 1: Identify unique values in the array

   The array contains values 3, 1, 2, 3, 2, 1, 4. Unique values are 1, 2, 3, and 4.

2. Step 2: Understand np.unique() output order

   np.unique() returns sorted unique values, so output is [1 2 3 4].

3. Final Answer:

   [1 2 3 4] -> Option A

4. Quick Check:

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

Hint: Unique values are sorted by default [OK]

Common Mistakes:

• Ignoring sorting order
• Listing duplicates
• Wrong output format

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

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

medium

A. Incorrect argument name, should be count_return=True

B. List input causes error, must convert to np.array first

C. No error, code runs fine

D. np.unique() does not support return_counts argument

Solution

1. Step 1: Check input type compatibility

   np.unique() accepts lists or arrays as input without error.

2. Step 2: Verify return_counts argument

   The argument return_counts=True is valid and returns counts of unique values.

3. Final Answer:

   No error, code runs fine -> Option C

4. Quick Check:

   List input + return_counts works [OK]

Hint: np.unique accepts lists and arrays [OK]

Common Mistakes:

• Thinking list input causes error
• Wrong argument name
• Assuming return_counts unsupported

5. You have a 2D NumPy array:

arr = np.array([[1, 2, 2], [3, 1, 4]])

How do you get all unique values from this 2D array as a sorted 1D array?

hard

A. np.unique(arr)

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

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

D. arr.unique()

Solution

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

   Calling np.unique() without axis flattens the array and returns unique sorted values.

2. Step 2: Check axis arguments

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

3. Final Answer:

   np.unique(arr) -> Option A

4. Quick Check:

   Flatten and unique = np.unique(arr) [OK]

Hint: No axis means flatten and find unique [OK]

Common Mistakes:

• Using axis to get unique elements
• Calling unique as method
• Expecting 2D unique output