![]() Flot is also limited to line and bar charts. This gives you much more flexibility than other charting packages, but there is a steeper learning curve. The nice thing about Flot is that you have access to plenty of callback functions so you can run your own code and style the results when readers hover, click, mouseout, and other common events. It’s a jQuery library, so if you’re already familiar with jQuery, it’s easy to manipulate the calls back, styling and behaviour of the graphics. It works in all browsers that support canvas-which means most of the popular ones, with some extra libraries to get canvas to work as VML in older browsers. Flotįlot is a great library for line graphs and bar charts. The portion for static images has been deprecated, but the Google Chart API is a good way to create dynamic visualizations 4. As a jumping-off point, it is a great tool to know how to use. You will probably find the right visualization for your needs as long as you are comfortable with the Google look and not in need of extreme customisation. However, the API has just about everything but the kitchen sink, from bar charts and line graphs to maps and even QR codes. Static images didn’t have the same issues, so I’m sorry to see them go. They are robust and work on all browsers supporting SVG, canvas and VML, but one big problem is that they are generated on the client side, which creates problems for devices without JavaScript, offline use-or just when saving in different formats. ![]() The portion of the toolset for static images has been deprecated, so the Google Chart Tools site now only offers tools for dynamic charts. All of the following toolkits accept at least one of the two formats as input. You’ll need to understand their structures and how to get data in or out of them. CSV/JSONĬSV (Comma-Separated Values) and JSON (JavaScript Object Notation) aren’t actual visualization tools, but they are common formats for data. This will get your familiar with what is possible before stepping off and using the API directly for your own projects. Google ‘eats its own dog food’, so the spreadsheet can generate the same charts as the Google Chart API. Nevertheless, as a means of rapidly communicating ideas, Excel should be part of your toolbox.Įxcel comes as part of the commercial Microsoft Office suite, so if you don’t have access to it, Google’s spreadsheets-part of Google Docs and Google Drive-can do many of the same things. As an entry-level tool, it can be a good way of quickly exploring data, or creating visualizations for internal use, but the limited default set of colours, lines and styles make it difficult to create graphics that would be usable in a professional publication or website. You can actually do some pretty complex things with Excel, from ‘heat maps’ of cells to scatter plots. ![]() Excel It isn’t graphically flexible, but Excel is a good way to explore data: for example, by creating ‘heat maps’ like this one If you deal with visualizations every day, you’ll quickly find yourself advancing beyond them, but not everyone will, so you’ll always be dealing with data coming in from sources you’d rather not deal with. If you are just getting started, these tools are musts to understand. You might not think of Excel as a visualization package, for example-but it’s capable of surprisingly complex results. Entry-level toolsĪt the entry level, we’ll be looking at unexpected uses for familiar tools. Almost everything here is available for free, and some you have probably installed already. In this article, I want to introduce you to 20 different tools for creating visualizations: from simple charts to complex graphs, maps and infographics. Beyond following blogs, you need to practise-and to practise, you need to understand the tools available. One of the most common questions I get asked is how to get started with data visualizations. Originally published at Creative Bloq on September 17, 2012.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |