Data Visualization Techniques
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Data Visualization Techniques

Gain hands-on experience in creating effective visualizations
0.0 (0 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
8 students enrolled
Created by Packt Publishing
Last updated 6/2017
English
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Current price: $10 Original price: $125 Discount: 92% off
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Includes:
  • 2.5 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Understand, validate, and optimize your data for effective visualizations
  • Know how and when to use line charts, bar charts, dot plots, scatter plots, and distribution plots
  • Find out the best ways to maximize the impact of basic chart types
  • See how and when to use dot density, choropleth, and categorical maps
  • Get to know to optimize map displays
  • Create, build, and optimize network graphs using connected data
View Curriculum
Requirements
  • In this course you will learn data visualization best practices starting with understanding, preparing, validating, and matching your source data to the most appropriate display types. We will then work through examples of how to create compelling charts, including simple types such as line and bar charts, followed by more advanced charts including dot plots, box plots, and bullet graphs. Following this, you will learn how to create exceptional maps for geographic data, with a focus on dot density, choropleth, and categorical map types. Our final section will teach you how to visualize connected data sets using powerful network graphs.
Description

This course will focus on building a variety of data visualizations using multiple tools and techniques. This is where we will put the theory together with actual hands-on experience of creating effective visualizations. Our efforts will be spent on choosing the best display types for our dataset, and then applying best practice principles to our selected charts, maps, or network graphs. We’ll spend considerable time on some of the most useful chart types, followed by a section where we explore the multiple uses of maps as visualizations. Our final section focuses on understanding network graphs, a powerful tool for displaying relationship data.

About The Author

Ken Cherven has been creating data visualizations for more than 10 years using a variety of tools, including Excel, Tableau, Cognos, D3, Gephi, Sigma.js, and Exhibit, along with geospatial tools such as Mapbox, Carto, and QGIS. Tableau is used on a daily basis in his current position, where he has built dozens of performance dashboards to track both marketing and operational metrics. He has also built many visualizations for his personal websites, especially utilizing Gephi and Sigma.js to explore and visualize network data.

He is very interested in tools related to the exploration of network data, typically using Gephi for most of his current output. Text analysis is also an area of interest, where he’s used tools such as Aylien, RapidMiner, R, and Exploratory to begin understanding and visualizing underlying patterns in political speeches, email transmissions, and book content.His experience in building data visualizations has intersected with many technologies, including a variety of SQL-based tools and languages including Oracle, MySQL, and SQLServer.

He frequently edits and styles network information using HTML and CSS, along with a bit of JavaScript. He is also highly engaged in the world of data visualization, including but not limited to his daily work experience. His work is based on a thorough understanding of visualization principles learned through extensive reading and practice. He also uses his websites to display and promote visualizations, which he shares with a wider audience. He has previously authored two books on Gephi for Packt, and has also presented at multiple data visualization conferences.

Who is the target audience?
  • This course is for data enthusiasts who possess a basic understanding of data visualization and are looking to learn different techniques. Basic knowledge of HTML, CSS, and JavaScript would be helpful, but is not required. Some experience with database, spreadsheet, and presentation software will also prove useful, but this is not critical to following along.
Students Who Viewed This Course Also Viewed
Curriculum For This Course
24 Lectures
02:35:45
+
Matching Your Data to the Best Display Type
5 Lectures 30:17

This video provides an overview of the entire course.

Preview 03:25

In this video, we emphasize the importance of understanding your source data, including its origin, layout, and field structure.
Understanding the Data
06:52

In this video, we focus on the steps involved in preparing data for a visualization, including modifying field types, validating data values, and creating derived values to enhance our data visualization opportunities.
Preparing the Data
07:09

In this video, our focus is on data validation, an important step in the pre-visualization process. We will discuss several data validation approaches to ensure clean data for our visualizations.
Validating the Data
05:57

Once our data prep and validation is complete, we should focus on selecting the best possible display type to represent the existing dataset.
Selecting the Best Display Option
06:54
+
Building Beautiful Visualizations from Basic Chart Types
7 Lectures 41:37
In this video, the focus is on optimizing line charts of various forms for maximum visual impact. We’ll look at simple, multiple, sparklines, and small multiple versions of line charts.
Preview 07:09

Bar charts can be used in many situations to compare categorical data in a highly effective, easy to understand manner. In this video, we’ll look at simple bar charts, as well as stacked charts, sparkbars, and small multiple bar charts.

Building Powerful Bar Charts
06:33

Dot plots can be employed in specific situations to display data that might otherwise be shared using bar charts. We’ll discuss when and how to create these useful displays.
Designing Effective Dot Plots
04:49

Distribution plots display large numbers of data point observations, making them very useful for spotting anomalies in a series. In this video, we’ll discuss how and when to use these plots in our data visualization efforts.
Building Distribution Plots
06:35

Scatterplots are an essential component of the data visualization toolkit, providing the best approach to visualizing data points along the x- and y-axes. In this video, we’ll examine their use, as well as the use of bubble plots, a variation on the scatterplot approach.
Creating Effective Scatterplots
05:34

Box plots facilitate the summarization of the same sort of data we will often display using distribution plots. In this video, we’ll discuss and examine how to use box plots for showing aggregate patterns and key statistical distribution metrics.

Working with Box Plots
05:49

Bullet graphs represent a recent effort to elegantly display data values relative to target or other threshold values. In this video, we’ll examine their use and show relevant examples.
Mastering Bullet Graphs
05:08
+
Creating Outstanding Maps
6 Lectures 42:24
In this video, we emphasize the importance of understanding your map data. We will examine some map datasets of both point and polygon varieties and what their structure looks like.
Preview 09:25

Dot density maps are one of the most important display types for geospatial data. These maps are based on lat/lon data, or sometimes centroid data, and are highly useful for displaying frequency data at discrete geographic levels.
Building Dot Density Maps
08:12

Categorical maps are a specialized type of Choropleth map, where map values are highlighted based on the specific categorical data in a dataset. This might be based on political preferences, top car brands, or any dataset where we can display a single ranked value.
Creating Categorical Maps
06:56

Choropleth maps are most frequently used to display numeric data using polygon-based geographic boundaries. We will look at use cases and examples of Choropleth maps in this video.
Designing Choropleth Maps
07:33

Maps require some enhancements in order to become fully useful data visualizations. These enhancements are often in the form of titles, legends, annotations, or other embellishments that support the meaning in the map.
Enhancing Your Map
05:22

This video discusses well-designed maps that should be shared with a larger community of viewers in order to communicate important stories as well as to solicit critical feedback and dialogue.
Sharing a Map
04:56
+
Building Powerful Network Graphs
6 Lectures 41:27
In this video, we discuss the unique structure of network data and how to create network datasets for visualization. Locating and downloading existing network data files is also covered.
Preview 07:50

This video will focus on the building of a network graph, using the type of dataset created in the previous video. We will have a brief look at network structure, layout algorithms, and graph statistics.

Building a Network Graph
05:43

Graph statistics can be used primarily to understand the structure of the graph and its members. These same statistics can also be used to help make the graph more visually compelling and able to communicate stories.
Understanding Graph Metrics
08:15

As with conventional charts, size can be used to communicate powerful visual stories. In this video, we’ll take a look at how size can be used in network graphs, and discuss the use of graph statistics in sizing elements.
Styling the Graph by Sizing Elements
05:46

As with conventional charts, color can be a powerful tool in communicating visual stories. In this video, we’ll look at the use of color in network graphs, and discuss the use of graph statistics in coloring elements.
Styling the Graph Using Color
07:27

Network graphs, similar to other visualizations, gain power through being shared with a wider audience. This video will show a number of options for sharing completed graphs and their data structures.
Sharing the Graph
06:26
About the Instructor
Packt Publishing
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Tech Knowledge in Motion

Packt has been committed to developer learning since 2004. A lot has changed in software since then - but Packt has remained responsive to these changes, continuing to look forward at the trends and tools defining the way we work and live. And how to put them to work.

With an extensive library of content - more than 4000 books and video courses -Packt's mission is to help developers stay relevant in a rapidly changing world. From new web frameworks and programming languages, to cutting edge data analytics, and DevOps, Packt takes software professionals in every field to what's important to them now.

From skills that will help you to develop and future proof your career to immediate solutions to every day tech challenges, Packt is a go-to resource to make you a better, smarter developer.

Packt Udemy courses continue this tradition, bringing you comprehensive yet concise video courses straight from the experts.