Anna University 3rd Semester: Data Science Data Types Quiz

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!