np.unique() for unique elements in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

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

np.unique() finds all the unique elements in an array and returns them sorted.

intermediate

How can you get the indices of the unique elements in the original array using np.unique()?

Use the parameter return_index=True. It returns the indices of the first occurrences of the unique values.

intermediate

What does np.unique(array, return_counts=True) return?

It returns two arrays: one with unique elements and one with the count of each unique element in the original array.

beginner

True or False: np.unique() always returns the unique elements in sorted order.

True. The unique elements returned by np.unique() are sorted by default.

beginner

How can np.unique() help in real-life data cleaning?

It helps find all distinct values in data, like unique customer IDs or unique product names, which is useful to remove duplicates or analyze categories.

What does np.unique() return by default?

A Only the first element

B All elements including duplicates

C All unique elements sorted

D Random elements

np.unique() returns all unique elements sorted by default.

Which parameter returns the count of each unique element in np.unique()?

A return_counts

B return_index

C return_inverse

D return_sorted

return_counts=True returns the count of each unique element.

If you want the indices of unique elements in the original array, which parameter do you use?

A return_inverse

B return_index

C return_positions

D return_counts

return_index=True gives indices of the first occurrence of unique elements.

Does np.unique() modify the original array?

A No, it returns the original array unchanged

B Yes, it sorts the original array

C Yes, it removes duplicates in place

D No, it returns a new array

np.unique() returns a new array with unique elements; it does not change the original array.

What type of data is np.unique() most useful for?

A Finding duplicates in data

B Sorting numbers only

C Calculating averages

D Creating random arrays

np.unique() helps find unique values, which is useful to identify duplicates.

Explain how you would use np.unique() to find unique values and their counts in a dataset.

Think about the parameters that give you extra information besides unique values.

Describe a real-world example where finding unique elements with np.unique() is helpful.

Consider situations like customer lists or product inventories.

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