python for data science mcq questions

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Title: Python for Data Science: A Comprehensive MCQ Tutorial with Code Examples
Introduction:
Python has become a dominant language in the field of data science due to its simplicity, versatility, and powerful libraries. In this tutorial, we will explore multiple-choice questions (MCQs) related to Python for data science, accompanied by code examples. This tutorial is designed to help beginners and intermediate users strengthen their understanding of Python concepts crucial for data science.
Basic Python Concepts:
Q1: What is the purpose of the 'if' statement in Python?
a. Looping
b. Decision making
c. Function definition
d. Variable assignment
Code Example:
Data Types and Structures:
Q2: Which data type is mutable in Python?
a. int
b. float
c. str
d. list
Code Example:
NumPy Library:
Q3: What does NumPy stand for?
a. Numerical Python
b. Numeric Processing
c. Numerical Processing
d. Numeric Pythonic
Code Example:
Pandas Library:
Q4: What is the primary data structure in Pandas for handling tabular data?
a. Array
b. DataFrame
c. Series
d. List
Code Example:
Data Visualization with Matplotlib:
Q5: Which function is used to create a scatter plot in Matplotlib?
a. plot()
b. scatter()
c. bar()
d. pie()
Code Example:
Machine Learning with scikit-learn:
Q6: What is the purpose of the 'fit' method in scikit-learn?
a. Train the model
b. Evaluate the model
c. Make predictions
d. Visualize data
Code Example:
Conclusion:
This tutorial provided a set of multiple-choice questions along with code examples to reinforce key Python concepts essential for data science. Practice these questions and code snippets to enhance your proficiency in Python and set a strong foundation for data science applications.

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