Data Wrangling with Python Test

Candidates Assessed

23726+

Organizations Served

127+

iMocha's data wrangling with Python test is the ideal pre-hire test for recruiters and hiring managers to assess candidates objectively. This test is useful for hiring Data Scientists, Data Science Engineer, Data Science Developer, Data Science Associate, Data Analyst and, Data Visualization Specialist. Our test helps recruiters to increases interview-to-selection ratio by 62% and reduce time-to-hire by 45%.

Test Summary

Data wrangling with Python test helps to screen the candidates who possess traits as follows:

Excellent Python programming skills for data wrangling and correction
Understanding of data, filtering unwanted data, using pivot, and melting the shifted data sets
Ability to use Python libraries like NumPy, Pandas, ScKit-learn for data wrangling
Excellent knowledge of data science concepts, steps, methods, and functions in Python

Data Wrangling with Python test for data wrangling with Python contains a coding simulator which will automatically evaluate and provide a score for the candidate’s written codes by compiling multiple test cases that generate discrete output. You will also get a detailed report for each test case execution along with execution-time and execution memory usage for the program written by the candidate. The Code-Replay feature records the coding screen of the candidate so that the reviewer can understand the coding and thinking patterns of the candidate.

The Coding test for data wrangling with Python may contain coding questions and innovative AI-LogicBox (Pseudo coding platform) questions to assess a candidate's coding skills in a fun & quick way.

Test Duration: 15 minutes

No. of Questions: 1

Level of Expertise: Entry/Mid/Expert

Useful for hiring

Data Scientists
Data Science Engineer
Data Science Developer
Data Science Associate
Data Analyst
Data Visualization Specialist

Topics Covered

Python

Data Wrangling with Python test assesses candidate's proficiency in Python

Data Science

Coding test for data wrangling with Python evaluates candidate's ability to deal with vast volumes of data using modern tools and techniques to find unseen patterns, derive meaningful information, and make business decisions

Data Wrangling

Data Wrangling with Python test gauges candidates skills of cleaning and unifying messy and complex data sets for easy access and data analysis

Sample Questions

Choose from our 100,000+ question library or add your own questions to make powerful custom tests

Question types:

Coding

Topic:

Data Wrangling (Mean Imputation)

Difficulty:

Easy

Q 1. Impute the missing Values

Mean Imputation is a method in which the missing value on a certain variable is replaced by the mean of the available cases.
You are given a list of numbers, there are certain values missing from the list. All you need to do is impute the missing values using the Mean Imputation method.

Input Format
Input 1: An integer “n”, giving the size of the list.
Input 2: n space-separated values of the list in which missing values are represented by “Nan”.

Output Format
Output the list in the space-separated format after mean Imputation. Note: round of the output values to 2 digits after the decimal

Sample Input

10
Nan 13 18 14 15 19 20 16 15 Nan

Sample Output

16.25 13 18 14 15 19 20 16 15 16.25

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Related Skills

Trusted By

“As a Talent Acquisition Manager, I observed that my team spent too much time in interviewing irrelevant candidates. So our team created an Aptitude evaluation test called Uneecops Common Aptitude Test (UCAT) with the help of iMocha. Now, we share the test with the candidates & based on the assessment report we were able to filter 170 good candidates from the pool of 300.”