Search test library by skills or roles
⌘ K

About the test:

The NumPy online test uses multiple-choice questions to evaluate a candidate's knowledge and skills related to NumPy arrays and operations, indexing and slicing, linear algebra and statistics, broadcasting, ufuncs and vectorization, and data input and output. The test aims to assess the candidate's proficiency in NumPy and their ability to apply numerical computing and data analysis techniques using Python.

Covered skills:

  • Array Creation
  • Array Operations
  • Linear Algebra
  • Broadcasting
  • Array Indexing and Slicing
  • Math Functions
  • File Handling
  • Performance Optimization

9 reasons why
9 reasons why

Adaface Numpy Test is the most accurate way to shortlist Python Developers



Reason #1

Tests for on-the-job skills

The Numpy Online Test helps recruiters and hiring managers identify qualified candidates from a pool of resumes, and helps in taking objective hiring decisions. It reduces the administrative overhead of interviewing too many candidates and saves time by filtering out unqualified candidates at the first step of the hiring process.

The test screens for the following skills that hiring managers look for in candidates:

  • Able to efficiently create and manipulate arrays using numpy
  • Thorough understanding of array indexing and slicing concepts
  • Proficient in performing various array operations
  • Comfortable working with math functions and performing mathematical computations using numpy
  • Strong grasp of linear algebra concepts and applications in numpy
  • Familiarity with file handling and reading/writing data using numpy
  • Understanding of broadcasting in numpy and its benefits
  • Able to optimize performance and improve execution speed of numpy computations
Reason #2

No trick questions

no trick questions

Traditional assessment tools use trick questions and puzzles for the screening, which creates a lot of frustration among candidates about having to go through irrelevant screening assessments.

View sample questions

The main reason we started Adaface is that traditional pre-employment assessment platforms are not a fair way for companies to evaluate candidates. At Adaface, our mission is to help companies find great candidates by assessing on-the-job skills required for a role.

Why we started Adaface
Reason #3

Non-googleable questions

We have a very high focus on the quality of questions that test for on-the-job skills. Every question is non-googleable and we have a very high bar for the level of subject matter experts we onboard to create these questions. We have crawlers to check if any of the questions are leaked online. If/ when a question gets leaked, we get an alert. We change the question for you & let you know.

How we design questions

These are just a small sample from our library of 10,000+ questions. The actual questions on this Online NumPy Test will be non-googleable.

🧐 Question

Medium

Array Manipulation and Summation
Array Manipulation
Mathematical Operations
Solve
Consider the following code snippet:
 image
What will be the value of G after executing the code?

Medium

Matrix Eigenvalues and Diagonalization
Linear Algebra
Matrix Operations
Solve
Consider the following code snippet:
 image
After running this code, which of the following statements is true regarding the B matrix?

Medium

ZeroDivisionError and IndexError
Exceptions
Solve
What will the following Python code output?
 image

Medium

Session
File Handling
Dictionary
Solve
 image
The function high_sess should compute the highest number of events per session of each user in the database by reading a comma-separated value input file of session data. The result should be returned from the function as a dictionary. The first column of each line in the input file is expected to contain the user’s name represented as a string. The second column is expected to contain an integer representing the events in a session. Here is an example input file:
Tony,10
Stark,12
Black,25
Your program should ignore a non-conforming line like this one.
Stark,3
Widow,6
Widow,14
The resulting return value for this file should be the following dictionary: { 'Stark':12, 'Black':25, 'Tony':10, 'Widow':14 }
What should replace the CODE TO FILL line to complete the function?
 image

Medium

Max Code
Arrays
Solve
Below are code lines to create a Python function. Ignoring indentation, what lines should be used and in what order for the following function to be complete:
 image

Medium

Recursive Function
Recursion
Dictionary
Lists
Solve
Consider the following Python code:
 image
In the above code, recursive_search is a function that takes a dictionary (data) and a target key (target) as arguments. It searches for the target key within the dictionary, which could potentially have nested dictionaries and lists as values, and returns the value associated with the target key. If the target key is not found, it returns None.

nested_dict is a dictionary that contains multiple levels of nested dictionaries and lists. The recursive_search function is then called with nested_dict as the data and 'target_key' as the target.

What will the output be after executing the above code?

Medium

Stacking problem
Stack
Linkedlist
Solve
What does the below function ‘fun’ does?
 image
A: Sum of digits of the number passed to fun.
B: Number of digits of the number passed to fun.
C: 0 if the number passed to fun is divisible by 10. 1 otherwise.
D: Sum of all digits number passed to fun except for the last digit.
🧐 Question🔧 Skill

Medium

Array Manipulation and Summation
Array Manipulation
Mathematical Operations

2 mins

NumPy
Solve

Medium

Matrix Eigenvalues and Diagonalization
Linear Algebra
Matrix Operations

3 mins

NumPy
Solve

Medium

ZeroDivisionError and IndexError
Exceptions

2 mins

Python
Solve

Medium

Session
File Handling
Dictionary

2 mins

Python
Solve

Medium

Max Code
Arrays

2 mins

Python
Solve

Medium

Recursive Function
Recursion
Dictionary
Lists

3 mins

Python
Solve

Medium

Stacking problem
Stack
Linkedlist

4 mins

Python
Solve
🧐 Question🔧 Skill💪 Difficulty⌛ Time
Array Manipulation and Summation
Array Manipulation
Mathematical Operations
NumPy
Medium2 mins
Solve
Matrix Eigenvalues and Diagonalization
Linear Algebra
Matrix Operations
NumPy
Medium3 mins
Solve
ZeroDivisionError and IndexError
Exceptions
Python
Medium2 mins
Solve
Session
File Handling
Dictionary
Python
Medium2 mins
Solve
Max Code
Arrays
Python
Medium2 mins
Solve
Recursive Function
Recursion
Dictionary
Lists
Python
Medium3 mins
Solve
Stacking problem
Stack
Linkedlist
Python
Medium4 mins
Solve
Reason #4

1200+ customers in 75 countries

customers in 75 countries
Brandon

With Adaface, we were able to optimise our initial screening process by upwards of 75%, freeing up precious time for both hiring managers and our talent acquisition team alike!


Brandon Lee, Head of People, Love, Bonito

Reason #5

Designed for elimination, not selection

The most important thing while implementing the pre-employment Online NumPy Test in your hiring process is that it is an elimination tool, not a selection tool. In other words: you want to use the test to eliminate the candidates who do poorly on the test, not to select the candidates who come out at the top. While they are super valuable, pre-employment tests do not paint the entire picture of a candidate’s abilities, knowledge, and motivations. Multiple easy questions are more predictive of a candidate's ability than fewer hard questions. Harder questions are often "trick" based questions, which do not provide any meaningful signal about the candidate's skillset.

Science behind Adaface tests
Reason #6

1 click candidate invites

Email invites: You can send candidates an email invite to the Online NumPy Test from your dashboard by entering their email address.

Public link: You can create a public link for each test that you can share with candidates.

API or integrations: You can invite candidates directly from your ATS by using our pre-built integrations with popular ATS systems or building a custom integration with your in-house ATS.

invite candidates
Reason #7

Detailed scorecards & benchmarks

View sample scorecard
Reason #8

High completion rate

Adaface tests are conversational, low-stress, and take just 25-40 mins to complete.

This is why Adaface has the highest test-completion rate (86%), which is more than 2x better than traditional assessments.

test completion rate
Reason #9

Advanced Proctoring


Learn more

About the Numpy Assessment Test

Why you should use Pre-employment Numpy Online Test?

The Online NumPy Test makes use of scenario-based questions to test for on-the-job skills as opposed to theoretical knowledge, ensuring that candidates who do well on this screening test have the relavant skills. The questions are designed to covered following on-the-job aspects:

  • Array Creation
  • Array Indexing and Slicing
  • Array Operations
  • Math Functions
  • Linear Algebra
  • File Handling
  • Broadcasting
  • Performance Optimization
  • Integrating Numpy with Python
  • Data Manipulation with Numpy

Once the test is sent to a candidate, the candidate receives a link in email to take the test. For each candidate, you will receive a detailed report with skills breakdown and benchmarks to shortlist the top candidates from your pool.

What topics are covered in the Numpy Online Test?

  • Array Creation

    Array creation refers to the process of initializing arrays with data. It includes functions such as np.array(), np.zeros(), np.ones(), and np.arange() that allow users to create arrays of desired shapes and fill them with specific values. This skill is measured in the test to assess the candidate's ability to create and manipulate arrays efficiently, which is essential in many data manipulation and analysis tasks.

  • Array Indexing and Slicing

    Array indexing and slicing involve accessing and extracting specific elements or portions of an array. The numpy library provides various indexing techniques like integer array indexing, Boolean array indexing, and advanced indexing using integers or arrays of indices. Assessing this skill in the test helps evaluate the candidate's proficiency in extracting and manipulating array data based on specific requirements.

  • Array Operations

    Array operations refer to mathematical and logical operations performed on arrays, such as addition, subtraction, multiplication, division, exponentiation, and comparisons. These operations can be performed element-wise or matrix-wise, allowing for efficient computation on large datasets. Including this skill in the test helps measure a candidate's ability to perform basic array operations, which are fundamental in data analysis and scientific computing.

  • Math Functions

    Math functions in numpy include various mathematical operations like trigonometric functions, logarithmic functions, exponential functions, and statistical functions. These functions allow for efficient computation and manipulation of numerical data in arrays. Evaluating this skill in the test helps assess a candidate's understanding and application of mathematical functions for data processing and analysis.

  • Linear Algebra

    Linear Algebra in numpy involves operations related to vectors, matrices, and linear equations. It includes functions for matrix multiplication, matrix inversion, finding eigenvalues and eigenvectors, solving linear equations, and performing matrix decompositions. Measuring this skill in the test helps determine a candidate's knowledge and proficiency in essential linear algebra operations used in various fields such as machine learning and scientific computing.

  • File Handling

    File handling in numpy refers to the ability to read and write array data from and to external files. Numpy provides functions like np.loadtxt() and np.savetxt() that enable reading and writing arrays in different file formats. Assessing this skill in the test helps evaluate a candidate's capability to handle data stored in files, which is crucial in real-world data processing and analysis tasks.

  • Broadcasting

    Broadcasting is a powerful numpy feature that allows arithmetic operations to be performed between arrays of different shapes. It eliminates the need for explicit loops and enables efficient computation with arrays of different sizes. Testing this skill helps measure a candidate's understanding and usage of broadcasting, which is essential to avoid unnecessary code complexity and improve computational efficiency.

  • Performance Optimization

    Performance optimization in numpy involves implementing techniques to improve the efficiency and speed of computations. This may include vectorizing operations, using optimized numpy functions, using appropriate data types, and employing algorithms tailored for performance. Evaluating this skill in the test helps determine a candidate's ability to optimize code execution, which is crucial when dealing with large datasets or computationally intensive tasks.

  • Full list of covered topics

    The actual topics of the questions in the final test will depend on your job description and requirements. However, here's a list of topics you can expect the questions for Online NumPy Test to be based on.

    Array Creation
    Array Indexing
    Array Slicing
    Array Operations
    Math Functions
    Linear Algebra
    File Handling
    Broadcasting
    Performance Optimization
    Array Reshaping
    Array Concatenation
    Array Splitting
    Array Sorting
    Array Filtering
    Array Transposition
    Array Stacking
    Array Broadcasting Rules
    Matrix Multiplication
    Eigenvalues and Eigenvectors
    Singular Value Decomposition
    Vectorization
    Element-wise Operations
    Dot Product
    Cross Product
    Transpose
    Inverse
    Matplotlib Integration
    Random Number Generation
    Array Access and Updates
    Array Comparison
    Array Masking
    Vector Norms
    Matrix Determinant
    Kronecker Product
    File Reading
    File Writing
    Broadcasting Rules
    Array Elementwise Operations
    Array Reduction
    Array Broadcasting
    Array Broadcasting Rules
    Performance Profiling
    Memory Management
    Parallel Processing
    Caching
    Array Verification
    Array Iteration
    Array Tiling
    Array Tapering
    Array Shuffling
    Array Synchronization
    Array Memory Allocation
    Test Case Generation

What roles can I use the Numpy Online Test for?

  • Python Developer
  • NumPy Developer
  • Data Analyst
  • Data Scientist
  • Machine Learning Engineer

How is the Numpy Online Test customized for senior candidates?

For intermediate/ experienced candidates, we customize the assessment questions to include advanced topics and increase the difficulty level of the questions. This might include adding questions on topics like

  • Error Handling in Numpy
  • Working with Multidimensional Arrays
  • Understanding Broadcasting Rules
  • Implementing Linear Algebra Operations
  • Handling Large Data with Numpy
  • Optimizing Numpy Code for Efficiency
  • Using Numpy for Scientific Computing
  • Memory Management in Numpy
  • Parallel Processing in Numpy
  • Advanced Array Manipulation Techniques
Singapore government logo

The hiring managers felt that through the technical questions that they asked during the panel interviews, they were able to tell which candidates had better scores, and differentiated with those who did not score as well. They are highly satisfied with the quality of candidates shortlisted with the Adaface screening.


85%
reduction in screening time

Numpy Hiring Test FAQs

Can I combine multiple skills into one custom assessment?

Yes, absolutely. Custom assessments are set up based on your job description, and will include questions on all must-have skills you specify. Here's a quick guide on how you can request a custom test.

Do you have any anti-cheating or proctoring features in place?

We have the following anti-cheating features in place:

  • Non-googleable questions
  • IP proctoring
  • Screen proctoring
  • Web proctoring
  • Webcam proctoring
  • Plagiarism detection
  • Secure browser
  • Copy paste protection

Read more about the proctoring features.

How do I interpret test scores?

The primary thing to keep in mind is that an assessment is an elimination tool, not a selection tool. A skills assessment is optimized to help you eliminate candidates who are not technically qualified for the role, it is not optimized to help you find the best candidate for the role. So the ideal way to use an assessment is to decide a threshold score (typically 55%, we help you benchmark) and invite all candidates who score above the threshold for the next rounds of interview.

What experience level can I use this test for?

Each Adaface assessment is customized to your job description/ ideal candidate persona (our subject matter experts will pick the right questions for your assessment from our library of 10000+ questions). This assessment can be customized for any experience level.

Does every candidate get the same questions?

Yes, it makes it much easier for you to compare candidates. Options for MCQ questions and the order of questions are randomized. We have anti-cheating/ proctoring features in place. In our enterprise plan, we also have the option to create multiple versions of the same assessment with questions of similar difficulty levels.

I'm a candidate. Can I try a practice test?

No. Unfortunately, we do not support practice tests at the moment. However, you can use our sample questions for practice.

What is the cost of using this test?

You can check out our pricing plans.

Can I get a free trial?

Yes, you can sign up for free and preview this test.

I just moved to a paid plan. How can I request a custom assessment?

Here is a quick guide on how to request a custom assessment on Adaface.

customers across world
Join 1200+ companies in 75+ countries.
Try the most candidate friendly skills assessment tool today.
g2 badges
Ready to use the Adaface Online NumPy Test?
Ready to use the Adaface Online NumPy Test?
logo
40 min tests.
No trick questions.
Accurate shortlisting.
Terms Privacy Trust Guide
ada
Ada
● Online
Previous
Score: NA
Next
✖️