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Data Scientist with Python Test
Clock
Test duration:
60
min
Notes
No. of questions:
23
Tie
Level of experience:
Entry/Mid/Senior

Data Scientist with Python Test

Python data science coding test is for recruiters and hiring managers to assess a data scientist's Python skills. Our Python data science coding test helps many enterprises to identify the right fit candidates and reduce time-to-hire by 40% and hiring costs by 45%.

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Organizations Served
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About

Data Scientist with Python Test

Data science experts have continued with their increasing development in Python for data analysis. This process mostly includes learning the Python fundamentals in the data science domain along with learning a few Python data science libraries, for example, NumPy, Pandas, Matplotlib, Scikit-Learn, etc. During this process, building a portfolio is also important, i.e., adapting Data Cleansing Projects, Data Visualization Projects, Machine Learning Projects, etc. Hence, Python is used at every step in the data science process. For e.g., data scientists can use Python and Panda’s library to clean and sort the data into a data frame (table), which is ready for analysis, exploring, and visualizing the data.

Python data science coding test helps tech recruiters and hiring managers to assess candidates’ data science with Python skills. Data scientist with Python technical test is designed by experienced Subject Matter Experts (SMEs) to evaluate and hire data scientists with Python as per the industry standards.

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How it works

Test Summary

Python Data Science coding test helps to screen the candidates who possess traits as follows:

  • Good experience in Python languages and their libraries like NumPy, Panda, etc.
  • Knowledge of data mining and data visualization techniques
  • Strong knowledge of data wrangling, analysis, and sorting of data in Data Science
  • Understanding of regression algorithms and techniques
  • Knowledge of SQLite concepts

Data scientist with Python test has a powerful reporting feature that will help you get an instant result and share this result with your recruiting team. You can use a ready-to-use assessment or ask us to custom-make the skills assessment as per your job description.

Data science with Python tests may contain MCQs (Multiple Choice Questions), MCQs (Multiple Answer Questions), Fill in the Blanks, Whiteboard Questions, Audio / Video Questions, AI-LogicBox (AI-based Pseudo-Coding Platform), Coding Simulators, True or False Questions, etc.

Test Duration
60
No. of Questions
23
Level of Expertise
Entry/Mid/Senior
Useful for hiring
  • Data Scientist using Python
  • Python Data Analyst
  • Python Developer
  • Machine Learning Developer
Topics Covered
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Python and Libraries

Our Python data science test assesses a candidate's ability to work on Python and also checks knowledge of libraries.

SQLite

The Python coding test for data science checks proficiency in SQLite coding to understand a candidate's knowledge of handling data.
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Data Mining, Data Wrangling, and Correction

iMocha's Python Data Science coding test evaluates the ability to data analysis, data mining & wrangling to draw the right conclusion and support decision making
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Classification and Regression Algorithms

Python Data science test assesses a candidate's knowledge of Classification and Regression to evaluate the relationship between two or more independent variables
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Sample Question
Choose from our 100,000+ questions library or add your own questions to make powerful custom tests.

Question types :

Multiple Option

Topic:

Matplotlib

Difficulty:

Hard

Question:

You are trying to plot a bar chart on a polar axis with given colors for every bar. You want to set the intensity of colors to 0.5. Which of the following is the correct way to do so?
Refer to the given sample bar chart on the polar axis with a color intensity of 0.5.


Bar chart image


Options

  • polar_bar(theta, radii, width=width, color=colors, alpha=0.5)
  • bar(theta, radii, width=width, color=colors, alpha=0.5)
  • bar(theta, radii, width=width, color=colors, intensity=0.5)
  • polar_bar(theta, radii, width=width, color=colors, intensity=0.5)
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questions to the test

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