The term "Big Data" is all over tech news. But what does it really mean? Big Data refers to the problem of trying to process and analyze large amounts of data. Generally, Big Data refers to the petabytes of data, which is over 1 million gigabytes. You are likely to face your own Big Data issues, just on a smaller scale. If you only have one web server, processing or analyzing a database of only one gigabyte can be overwhelming.
Another part of the Big Data problem is the source and format of the data. It is coming from many sources and it's not easy to match all of the data points. You probably have years of transactional data in a MySQL database, as well as APIs to Google Analytics, Facebook, Twitter, and any other services your company uses.
Once you can figure out how to process the data, you need to do something with it. That's where jqPlot comes in. Using charts to display large datasets makes it easier to see trends or correlations in the data. jqPlot allows you to create charts quickly so that you can move on to analyze your data.
Many technical books give examples that don't match anything you might deal with in the real world. I'm writing this book about the various problems we face working in the fictional company jQ Big Box Electronics. We will work through real-world examples that reflect the reality of the "Big Data" world we live in. I hope that placing these examples in a practical context will help you understand the rationale for using a certain chart for a particular dataset and build on the skills you will acquire from this book.
Chapter 1, Getting Started, will briefly give an introduction on how to create a jqPlot object and how the plugin handles data. Then, we'll start creating our first charts, as well as looking at different options for formatting lines and marks.
Chapter 2, More Line Charts, Area Charts, and Scatter Plots, discusses the different ways in which you can load data into your chart, including using AJAX to a remote service. Then, we'll move on to discussing what area charts and scatter plots are, and their best uses.
Chapter 3, Bar Charts and Digging into Data, discusses the best uses of bar charts. We'll also see different options for axis and tick labels including rotatable labels. We'll finish up with clickable data points and will look at how to use these to drill down into more complicated data.
Chapter 4, Horizontal and Stacked Bar Charts, teaches you about horizontal and stacked bar charts. We'll also look at axis padding and positioning of data point labels.
Chapter 5, Pie Charts and Donut Charts, discusses the specific uses of pie charts and donut charts. We'll also see some specific options for pie charts.
Chapter 6, Spice Up Your Charts with Animation, Tooltips, and Highlighting, teaches how to animate your own charts and how to create tooltips. We'll also cover data point highlighting and cursor highlighting.
Chapter 7, Stock Market Charts – OHLC and Candlestick Charts, discusses OHLC and candlestick charts, and their specific uses. We'll also learn the method to format the text included in the tooltips.
Chapter 8, Bubble Charts, Block Plots, and Waterfalls, looks at some different charts that are heavier on the visualization of data over the representation of the data.
Chapter 9, Showing Real-time Data with Our Charts, discusses the methods that allow us to redraw or recreate a given plot after it is has been generated. We'll take this newfound knowledge and see how to update our charts automatically at set intervals.
Chapter 10, Beautifying and Extending Your Charts, explains how to create different themes for our plots and the various CSS options available to style our charts.
Chapter 11, Bringing it All Together, combines everything you have learned and merges the different chart types into one plot, as well as styling your new charts. You will also see how jqPlot can be extended with the new rendering plugins.
Appendix, Answers, helps us find the answers to all the learning questions found throughout the book.