Practice Lab Objectives - 1.3.1 | Module 1: ML Fundamentals & Data Preparation | Machine Learning
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is the primary function to load a CSV file into Pandas?

πŸ’‘ Hint: Think about how we import data.

Question 2

Easy

True or False: A DataFrame is a one-dimensional structure.

πŸ’‘ Hint: Consider the shape of a DataFrame.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

Which of the following is a method to load data into a Pandas DataFrame?

  • pd.read_data()
  • pd.read_csv()
  • pd.load_data()

πŸ’‘ Hint: This method is essential for reading data files.

Question 2

True or False: Exploratory Data Analysis (EDA) is only about visualization.

  • True
  • False

πŸ’‘ Hint: Remember, EDA encompasses both analysis and visualization.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Create a Jupyter Notebook that loads the Iris dataset, performs basic EDA, and visualizes the results using histograms and scatter plots. Describe your findings.

πŸ’‘ Hint: Document each method used for EDA and the resulting insights you draw from the visualizations.

Question 2

Identify and explain the steps needed to handle missing data in the Titanic dataset, including decisions about deletion and imputation.

πŸ’‘ Hint: Consider what impact each decision might have on your dataset's integrity.

Challenge and get performance evaluation