Interactive Data Visualization with Plotly in R

2019/2020

Учебный год

ENG

Обучение ведется на английском языке

3

Кредиты

Кто читает:

Департамент социологии

Статус:

Курс по выбору

Когда читается:

2-й курс, 2 модуль

Преподаватель

Камалов Эмиль Альфредович

Course Syllabus

Abstract

This blended course allows the student to deepen their expertise in data visualization methods using R by completing related courses in datacamp.com The course covering following topics: 1. Introduction to the Tidyverse (optional) https://www.datacamp.com/courses/introduction-to-the-tidyverse 2. Interactive Data Visualization with plotly in R https://www.datacamp.com/courses/interactive-data-visualization-with-plotly-in-r 3. Intermediate Interactive Data Visualization with plotly in R https://www.datacamp.com/courses/intermediate-interactive-data-visualization-with-plotly-in-r

Learning Objectives

• Introduction to the programming language R, focused on a powerful set of tools known as the Tidyverse
• Learn how to create and customize interactive graphics in plotly using the R programming language
• Extend your understanding of plotly to create animated and linked interactive graphics, which will enable you to communicate multivariate stories quickly and effectively

Expected Learning Outcomes

• Acquire knowledge and skills of structuring and visualizing data using Tidyverse and Plotly packages in R

Course Contents

• Introduction to the Tidyverse
• Intermediate Interactive Data Visualization with plotly in R
• Interactive Data Visualization with plotly in R
• Applying Plotly functions to the data visualization

Assessment Elements

• Datacamp
• Exam
  Final exam is consist of tasks were students are expected to apply method and functions of plotly package in R. Students might be asked to use data of their own research projects

Interim Assessment

• Interim assessment (2 module)
  0.3 * Datacamp + 0.7 * Exam

Bibliography

Recommended Core Bibliography

• Andy Meyer. (2018). Using R and the Tidyverse to Generate Library Usage Reports. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.41E60AEE
• Роберт И., Кабаков - R в действии. Анализ и визуализация данных в программе R - Издательство "ДМК Пресс" - 2014 - 588с. - ISBN: 978-5-97060-077-1 - Текст электронный // ЭБС ЛАНЬ - URL: https://e.lanbook.com/book/58703

Recommended Additional Bibliography

• Daniel Kaplan. (2018). Teaching Stats for Data Science. The American Statistician, (1), 89. https://doi.org/10.1080/00031305.2017.1398107