np.unique() for unique values in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to find unique values in the array.

NumPy

import numpy as np
arr = np.array([1, 2, 2, 3, 4, 4, 5])
unique_values = np.[1](arr)
print(unique_values)

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

Aunique

Bsort

Carray

Dmean

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.sort() instead of np.unique()

Trying to use list methods instead of numpy functions

The np.unique() function returns the sorted unique elements of an array.

2fill in blank

medium

Complete the code to find unique values and return their counts.

NumPy

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

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

Areturn_index

Breturn_sorted

Creturn_inverse

Dreturn_counts

Attempts:

3 left

💡 Hint

Common Mistakes

Using return_index instead of return_counts

Not setting any argument and expecting counts

The return_counts=True argument makes np.unique() return the counts of each unique value.

3fill in blank

hard

Fix the error in the code to get unique values from a 2D array.

NumPy

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

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

Aaxis

Breturn_index

Caxis=0

Dreturn_counts

Attempts:

3 left

💡 Hint

Common Mistakes

Using return_counts instead of axis

Passing axis as a keyword argument value instead of parameter name

The axis parameter specifies the axis along which to find unique rows or columns in a 2D array.

4fill in blank

hard

Fill both blanks to create a dictionary of unique values and their counts from a list.

NumPy

import numpy as np
words = ['apple', 'banana', 'apple', 'orange', 'banana', 'banana']
unique_words, counts = np.unique(words, [1]=True)
word_count = { [2]: counts[i] for i, [2] in enumerate(unique_words) }
print(word_count)

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

Areturn_counts

Breturn_index

Cword

Dcount

Attempts:

3 left

💡 Hint

Common Mistakes

Using return_index instead of return_counts

Using count as dictionary key instead of word

Use return_counts=True to get counts, then create a dictionary with words as keys and counts as values.

5fill in blank

hard

Fill all three blanks to filter unique numbers greater than 3 and create a list of them.

NumPy

import numpy as np
numbers = np.array([1, 2, 3, 4, 5, 5, 6])
unique_nums = np.unique(numbers)
filtered = [num for num in unique_nums if num [1] [2]]
result = [3](filtered)
print(result)

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

A>

B3

Clist

Dset

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>'

Forgetting to convert filtered result to list

Filter unique numbers greater than 3 using > and 3, then convert the filtered result to a list.

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