Practice Dataframe: Two-dimensional Labeled Table (4.3.2) - Chapter 4: Understanding Pandas for Machine Learning

Practice: DataFrame: Two-Dimensional Labeled Table

Lesson 4.3.2Understanding Pandas for Machine Learning

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9 questions

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Exercise
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6 sample questions

Question 1.
What is a DataFrame in Pandas?
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Think about how data is organized.
Question 2.
How do you access a column named 'Age' in a DataFrame?
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Use square brackets to access the column.
3Question 3.
What is the main purpose of a DataFrame in Pandas?
- To store one-dimensional data
- To analyze data
- To represent two-dimensional labeled data
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Think about the shape of the data.
4Question 4.
True or False: A DataFrame can only contain numeric data.
- True
- False
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Remember that multiple data types can co-exist in a DataFrame.
Question 5.
Create a DataFrame for a store inventory with three items (item name, price, quantity in stock). Then filter out items that are out of stock.
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Use the same structure we followed for creating DataFrames.
Question 6.
Imagine you have student data with 'Name', 'Score', and 'Pass/Fail' status. Create a DataFrame and calculate the average score of all students who passed.
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Think about how to filter and then perform a calculation.

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