Python In Practice - 15 Projects to Master Python - Data Processing and Cleaning

Python In Practice - 15 Projects to Master Python - Data Processing and Cleaning

Assessment

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Information Technology (IT), Architecture

University

Hard

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The video tutorial covers data cleaning using pandas, focusing on removing unnecessary index columns, renaming columns, and dropping rows. It explains converting data types to float for mathematical operations and converting units from inches, feet, and cubic feet to meters. The tutorial also discusses rounding data to one decimal place for better precision.

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7 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the purpose of renaming column labels in a data frame?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

Explain how to remove the index column from a data frame.

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the significance of using the 'inplace' parameter in the drop function?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

Describe the process of changing data types to float in a data frame.

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

How do you convert measurements from inches to meters in a data frame?

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6.

OPEN ENDED QUESTION

3 mins • 1 pt

What method can be used to limit decimal places in a data frame?

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7.

OPEN ENDED QUESTION

3 mins • 1 pt

Why is it important to round values when performing statistical functions?

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