Global MCQ Practice

Part of: Miscellaneous Indian Gk set 243

Which of the following language is mostly used in Data science?

Category: Miscellaneous Indian Gk

Hint: Consider the popularity and library support for data analysis and machine learning.

Correct Answer: C) Python

Exam Relevance: UPSC, SSC, Bank PO, MBA Entrance

Difficulty: Easy

Explanations:
  • Extensive Library Support: Python has a vast ecosystem of libraries and frameworks that are specifically designed for data science tasks. Some of the most popular libraries include Pandas for data manipulation, NumPy for numerical operations, SciPy for scientific computing, and Scikit-learn for machine learning. These libraries provide a wide range of functionalities that make it easier to perform complex data analysis tasks.
  • Community and Resources: Python has a large and active community of developers and data scientists who contribute to its development and provide extensive resources such as tutorials, documentation, and forums. This community support is invaluable for learning and troubleshooting.
  • Integration with Other Tools: Python can easily integrate with other tools and platforms used in data science, such as Jupyter Notebooks, which provide an interactive environment for data analysis and visualization.
  • Flexibility: Python is a versatile language that can be used for a wide range of tasks beyond data science, such as web development, automation, and more. This flexibility makes it a valuable skill for data scientists who may need to work on various projects.
    • Option Analysis:
    • Option A: C is a low-level language that is not typically used for data science due to its complexity and lack of specialized libraries for data analysis.
    • Option B: C++ is a more advanced language than C but still lacks the extensive library support and ease of use that Python offers for data science tasks.
    • Option C: Python is the correct answer because it is widely used in data science due to its simplicity, extensive library support (such as Pandas, NumPy, and SciPy), and strong community resources.
    • Option D: Ruby is not commonly used in data science, as it lacks the specialized libraries and community support that Python has for data analysis and machine learning.

    Mnemonic: Pandas, NumPy, SciPy: Python's data science libraries

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