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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What command do you use to load a CSV file in Pandas?
💡 Hint: Remember the function name starts with 'read'.
Question 2
Easy
How can you check for missing values in a DataFrame?
💡 Hint: Look for functions that analyze the DataFrame for null values.
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
What command do you use to read a csv file?
- pd.read_file()
- pd.load_csv()
- pd.read_csv()
💡 Hint: Focus on which function reads data.
Question 2
True or False: You must clean a dataset before analyzing it.
- True
- False
💡 Hint: Clean data leads to better insights.
Solve 3 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Using the student data CSV, write a complete Python function that loads the data, handles missing values, calculates the average marks of students segmented by gender, plots the results, and saves the cleaned data back to a new CSV file.
💡 Hint: Break down the problem into individual steps as highlighted in our project.
Question 2
Discuss how you might visualize three different metrics from the student dataset. Create a plan for generating distinct types of charts for each.
💡 Hint: Think about the story each visual chart would help tell.
Challenge and get performance evaluation