pandas for Python - A Quick Guide - Data Transformation

pandas for Python - A Quick Guide - Data Transformation

Assessment

Interactive Video

Information Technology (IT), Architecture, Social Studies

University

Practice Problem

Hard

Created by

Wayground Content

FREE Resource

This video tutorial covers the conversion of data to categorical data types using pandas. It explains how to convert string data to categories and discretize continuous variables. The tutorial highlights the advantages of using categorical data, such as reduced memory usage and enabling comparison operations. It also demonstrates the process of discretizing continuous variables into categorical variables using the pandas cut function.

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7 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What is categorical data type in pandas and why is it important?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

How can you find the frequency of each label in a categorical column?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

What method can be used to convert a column to categorical data type?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

Explain the advantages of converting string data to categorical data.

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

What is discretization and how is it applied to continuous variables?

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6.

OPEN ENDED QUESTION

3 mins • 1 pt

Describe the process of using the cut function to categorize salary data.

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7.

OPEN ENDED QUESTION

3 mins • 1 pt

How does converting to categorical data reduce memory usage?

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