Anna University 3rd Semester: Data Science Data Types Quiz
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Questions and Answers

Which data type includes numbers like 5, -12, and 3.14?

  • Date and time data type
  • Floating-point data type (correct)
  • Rational data type
  • Categorical data type
  • Why are strings and booleans categorized as categorical data types?

  • Because they can only represent two values
  • Having no order or hierarchy
  • Due to their unlimited length
  • Being non-numeric in nature (correct)
  • What makes up a datetime data type?

  • Integers and booleans
  • Rational numbers
  • Date, time, and datetime components (correct)
  • Strings and floats
  • How would you convert a string to an integer in Python?

    <p><code>int('7')</code></p> Signup and view all the answers

    Study Notes

    Anna University 3rd Semester: Foundation of Data Science - Data Types

    As you prepare for the Anna University's Data Science third semester exam in the academic year of 2022-2023, understanding the fundamentals of data types is crucial to your success. Let's dive into the basics and important questions you should be familiar with.

    Data Types

    Data types are categories that organize the data to which operations and algorithms can be applied. Anna University's curriculum will cover the following data types:

    • Numerical Data Types: Integers (e.g., 5, -12), floating-point numbers (e.g., 3.14, 1.5), and rational numbers (e.g., 1/2, 7/3).
    • Categorical Data Types: String data (e.g., "John", "Female"), boolean data (e.g., True, False), and enumeration data (e.g., days of the week).
    • Date and Time Data Types: Structured data that includes date, time, and datetime components.

    Important Questions

    1. Define and distinguish between the following data types: integers, floats, and rationals (3 marks).
    2. Explain why strings and booleans are considered categorical data types (3 marks).
    3. List and classify the components that make up a datetime data type (3 marks).
    4. Describe the concept of type conversion and give an example of how to convert a string to an integer using Python (4 marks).
    5. Explain the steps to convert a datetime object to a string in Python (4 marks).
    6. Discuss the importance of choosing the appropriate data type for data analysis and give an example of how incorrect data typing can lead to incorrect analysis (4 marks).
    7. Describe the concept of type inference in Python and explain how it works (4 marks).
    8. Discuss the impact of data types on the performance of algorithms and give an example to demonstrate this (4 marks).

    In addition to these questions, be prepared to discuss data typing in other programming languages and data processing tools. Remember that understanding data types is fundamental to your success in subsequent courses on data manipulation, analysis, and modeling. Happy studying!

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    Description

    Prepare for Anna University's Data Science third semester exam by mastering the fundamentals of data types. This quiz covers numerical, categorical, date and time data types, along with important questions on definitions, conversions, and implications of data typing.

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