In our previous posts about Leaflet.js, we coded an interactive marker map and learned how to update our data with a google spreadsheet. In this short tutorial, we will show you how to make your map searchable so users can find a specific marker.
So let’s start right away with setting up a data table with Google Spreadsheets.
Important Notice: Considering the recent disclosure of vulnerabilities in popular e-mail clients like Mozilla Thunderbird, we decided to delete this post. The current PGP implementation in email clients has vulnerabilities, that haven’t been fixed for now and will take time to get fixed. For more information about the technical side visit efail.de and for a detailed explanation, read the post by the Electronic Frontier Foundation. Thanks for your interest in this topic! We will update this post when new info is available.
Java Script libraries and other tools offer cool ways to visualize data, but sometimes, you may want an even more customizable way of presenting a topic on the web. Maybe you already have the perfect graphic, but it’s not interactive yet. In this tutorial, we’ll show you a way to add tooltips to your SVG graphics.
As an example, let’s start with a map of the locations of some data journalism newsrooms in the German speaking area. As always you can find all the code of this tutorial on our GitHub page.
This is what the finished map will look like: Read More
What? Your only coding skills are a bit of R? No problemo! What if I told you there was a way to interactively show users your most interesting R-results in a fancy web app?
Shiny to the rescue
In this tutorial, we will learn step by step how to code the shiny app on Germany’s air pollutants emissions that you can see below. Read More
In part one of this tutorial, you learned about what distance and similarity mean for data and how to measure it. Now, let’s see how we can implement distance measures in R. We’re going to look at the built-in dist() function and visualize similarities with a ggplot2 tile plot, also called a heatmap.
In your work, you might encounter a situation where you want to analyze how similar your data points are to each other. Depending on the structure of your data though, “similar” may mean very different things. For example, if you’re working with records containing real-valued vectors, the notion of similarity has to be different than, say, for character strings or even whole documents. That’s why there’s a small collection of similarity measures to choose from, each tailored to different types of data and different purposes.