9.3.2 - Understanding Dataset Properties
Enroll to start learning
You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.
Practice Questions
Test your understanding with targeted questions
What does the df.head() function do?
💡 Hint: Think about its purpose in exploring the dataset.
What information does df.shape provide?
💡 Hint: Remember, it's a tuple.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What does df.tail() do?
💡 Hint: Think about what you want to see from the bottom of the dataset.
Does df.describe() provide categorical data information?
💡 Hint: Focus on the type of analysis `describe` performs.
1 more question available
Challenge Problems
Push your limits with advanced challenges
You have a DataFrame with 5000 rows and 7 columns. After performing df.info(), one column shows 'object' data type while the others are 'int64'. What does this tell you?
💡 Hint: Consider why data types matter in analysis.
If df.describe() shows a high standard deviation for a column, what might that imply about the data?
💡 Hint: Think about what standard deviation reveals about data distribution.
Get performance evaluation
Reference links
Supplementary resources to enhance your learning experience.