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Data Visualization

Dr. Aihua Li

In the era of big data, acquiring the ability to analyze and visually represent “Big Data” in a compelling manner is crucial. Therefore, it is essential for data scientists to develop the skills in producing and critically interpreting digital maps, charts, and graphs. Data visualization is an increasingly important topic in our globalized and digital society. It involves graphically representing data or information, enabling decision-makers across various industries to comprehend complex concepts and processes that may otherwise be challenging to grasp. DSCI 605 Data visualization serves as the foundation for understanding principles, concepts, techniques, and tools used to visualize information in large, intricate data sets. It also provides hands-on experience in visualizing big data using the open-source software R. Through the course, students will learn to evaluate the effectiveness of visualization designs and think critically about decisions, such as color choice and visual encoding. Additionally, students will create their own data visualizations and become proficient in using R.

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In the era of big data, acquiring the ability to analyze and visually represent “Big Data” in a compelling manner is crucial. Therefore, it is essential for data scientists to develop the skills in producing and critically interpreting digital maps, charts, and graphs. Data visualization is an increasingly important topic in our globalized and digital society. It involves graphically representing data or information, enabling decision-makers across various industries to comprehend complex concepts and processes that may otherwise be challenging to grasp. DSCI 605 Data visualization serves as the foundation for understanding principles, concepts, techniques, and tools used to visualize information in large, intricate data sets. It also provides hands-on experience in visualizing big data using the open-source software R. Through the course, students will learn to evaluate the effectiveness of visualization designs and think critically about decisions, such as color choice and visual encoding. Additionally, students will create their own data visualizations and become proficient in using R.

The course comprises four sections. The first section caters to learners with minimal or no experience in R, establishing the groundwork for data visualization with R. The second section introduces preliminary data visualization techniques, allowing students to gain hands-on experience with common visualization practices for Exploratory Data Analysis (EDA) using ggplot2. This section emphasizes data exploration before delving into advanced data mining. The third section builds upon existing data visualization skills by delving into advanced data visualization topics, including interactive data visualization, time series plotting, and spatial mapping.

The primary objective of the first three sections is to equip students with a well-developed set of skills, enabling them to create a wide range of visualizations in R. The final section focuses on completing a final project, where students apply the skills, theory, and experiences gained from the previous sections. The project entails developing a data visualization that effectively communicates a compelling story to the audience and readers.

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What's inside

Syllabus

Introduction to Data Visualization and Getting Started with R
In the first module, we will learn what is data visualization, why data visualization is necessary in data science field, what data visualization will do and what skills data visualization need. We will first get started with R by learning R basic and R Markdown to prepare the data visualization in the course.
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Graphics Components for Data Visualization
Understanding the elements and components of data visualization is essential for data visualization because it provides a systematic framework for creating effective and meaningful visual representations of data.In this module, we will explore the grammar of graphics, explain some rational, and introduce principles in data visualization, as well as describe the common Exploratory Data Analysis (EDA) idioms' features and applications.
ggplot2
Let's get our hands wet with real data visualization-producing a graph. In this module, we will explore the powerful data visualization package ggplot2. In this module, you will learn basic usages of ggplot() function, the fill and color aesthetics, and learn to create a histogram using ggplot() and setting suitable bin numbers or bin width.
Embed Images and Tables in R Markdown Files
Now you have conducted the basic data wrangling, documented your work in R Markdown, and created your first data visualization in previous modules. In this module, you will learn to embed, create and refer to images and tables in R Markdown. In addition, you will learn to produce scatter plots, which further enrich your visualization experience and enhance your visualization skills.
Boxplot and Multiple-view Layout
This module will continue for one of the common EDA idioms-box plots to enrich your data visualization experience and will explore new technique-layout multiple plots on one page. In this module, you will learn to produce boxplots using ggplot(), interpret boxplots and arrange multiple plots on one page.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides a foundational understanding of data visualization in the age of big data
Utilizes the open-source software R for hands-on experience in visualizing big data
Focuses on evaluating and critically interpreting data visualizations
Suitable for learners with minimal or no experience in R
Provides a comprehensive overview of data visualization principles, concepts, techniques, and tools
Culminates in a final project where students apply their skills to create a compelling data visualization

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Activities

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Career center

Learners who complete Data Visualization will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts use data to solve problems and make informed decisions. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a Data Analyst.
Data Scientist
Data Scientists use their knowledge of data analysis and visualization to extract meaningful insights from large datasets. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a Data Scientist.
Business Analyst
Business Analysts use data to improve the efficiency and effectiveness of businesses. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a Business Analyst.
Statistician
Statisticians collect, analyze, and interpret data. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a Statistician.
Research Analyst
Research Analysts use data to identify trends and make predictions. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a Research Analyst.
Financial Analyst
Financial Analysts use data to analyze the financial performance of companies and make investment recommendations. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a Financial Analyst.
Operations Research Analyst
Operations Research Analysts use data to improve the efficiency and effectiveness of business operations. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as an Operations Research Analyst.
Marketing Analyst
Marketing Analysts use data to understand consumer behavior and develop marketing campaigns. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a Marketing Analyst.
Interaction Designer
Interaction Designers create user interfaces for websites and other digital products. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as an Interaction Designer.
User Experience Researcher
User Experience Researchers use data to understand how users interact with products and services. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a User Experience Researcher.
Information Architect
Information Architects design and organize websites and other digital products. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as an Information Architect.
Data Visualization Specialist
Data Visualization Specialists create visual representations of data. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a Data Visualization Specialist.
Software Engineer
Software Engineers design, develop, and maintain software applications. They work in a variety of industries, including technology, finance, healthcare, and retail. This course may be useful for learning the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course may be helpful for success as a Software Engineer.
Web Developer
Web Developers create and maintain websites. They work in a variety of industries, including technology, finance, healthcare, and retail. This course may be useful for learning the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course may be helpful for success as a Web Developer.
Graphic designer
Graphic Designers create visual content for websites, print, and other media. They work in a variety of industries, including technology, finance, healthcare, and retail. This course may be useful for learning the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course may be helpful for success as a Graphic Designer.

Reading list

We've selected 18 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Visualization.
This classic book on data visualization provides a comprehensive overview of the principles and techniques of effective data visualization. It must-read for anyone who wants to learn how to create clear and informative visualizations.
Comprehensive guide to the ggplot2 package, which is one of the most popular data visualization libraries in R. It provides a step-by-step guide to creating a wide variety of visualizations, from simple plots to complex dashboards.
Provides a comprehensive overview of the field of information visualization. It covers the different theories and techniques used to create effective visualizations, as well as how to evaluate the effectiveness of visualizations.
Provides a comprehensive overview of the design principles and best practices for data visualization.
Provides a comprehensive guide to creating interactive data visualizations for the web. It covers the different types of interactive visualizations, as well as how to use them effectively to engage users.
This practical guide focuses on creating effective data visualizations using common software such as Excel, PowerPoint, and Tableau.
Provides a comprehensive overview of the principles of data visualization. It covers the different types of charts and graphs, as well as how to use them effectively to communicate data.
Provides a comprehensive introduction to R, a programming language that is widely used for data science. It covers the basics of R, as well as more advanced topics such as data visualization, machine learning, and statistical modeling.
Provides a comprehensive overview of the principles of visual communication. It covers the different elements of visual design, as well as how to use them effectively to create clear and informative visualizations.
Provides a comprehensive overview of the field of data visualization. It covers the different theories and techniques used to create effective visualizations, as well as how to evaluate the effectiveness of visualizations.
Provides a collection of essays on data visualization. It covers a wide range of topics, from the history of data visualization to the latest trends in the field.
Provides practical guidance on how to create effective data visualizations. It covers the different types of charts and graphs, as well as how to use them effectively to communicate data.
Provides practical guidance on how to choose the right chart for every data story. It covers the different types of charts and graphs, as well as how to use them effectively to communicate data.

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