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Data Science and Machine Learning with R - Data Types and Structures in R Section Overview

Data Science and Machine Learning with R - Data Types and Structures in R Section Overview

Assessment

Interactive Video

•

Information Technology (IT), Architecture

•

University

•

Practice Problem

•

Hard

Created by

Wayground Content

FREE Resource

The video tutorial covers data types and structures in R, including characters, numerics, integers, and logicals. It explains atomic vectors, missing data representation, and coercion. The tutorial also introduces matrices, lists, data frames, and tibbles, highlighting their importance in data science and machine learning. Key functions and features of these data structures are discussed, providing a comprehensive understanding of R's capabilities.

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4 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

Explain the concept of lists in R and how they differ from atomic vectors.

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

What are data frames and why are they important in R?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

How do Tibbles improve upon traditional data frames in R?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the purpose of the Tribble function in R?

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