Absolutely everything* you need to know about online mapping tools

Absolutely everything* you need to know about online mapping tools

This is post 3 of 3 in the series “Data Work 101” It can be a little intimidating to try to make an online map as a newbie. With a ton of tools that range in complexity and attractiveness, it’s easy to get caught up figuring out which path to take. Let’s break down 10 of the most popular tools for building online maps and figure out what’s best for you. I talk about base layers a fair amount below – that’s just the map that’s underneath your markers, lines or polygons. * “Absolutely everything” is perhaps an overstatement. I originally intended this to be a breakdown of all things mapping-related, but it turns out there’s far too much to say for one post. Stay tuned for later Data Work 101 posts! Mapping Tool Roundup SVG (Scalable Vector Graphics) SVG is a image format that deals with shapes instead of pixels (more details here). If you had a map of the United States, for example, each state would be a shape that could be edited individually. You could pick the Alabama shape and color it green, and then turn Connecticut orange and New Mexico purple. You’d need to use a vector editing program like Adobe Illustrator or Inkscape to do the coloring, but it’d be super simple and require no programming. When finished, you’d export to PNG and be on your way to mapping fame. Pros: No programming necessary Dead simple – just point and click Easy to place text on top Cons: Not scalable (imagine manually coloring all 3000+ counties in the US!) Imprecise, using a color gradient would prove a nightmare Updating the data would require you to color each and every...
Absolutely everything* you need to know about picking a first programming language

Absolutely everything* you need to know about picking a first programming language

This is post 2 of 3 in the series “Data Work 101” When you’re getting into programming, one of the most stressful parts is right at the beginning: Which programming language should you pick? If you ask a coder for advice, nine times out of ten they’re going to recommend the language they use; it works for them, so it should work for you just as well, right? Well, not really. It isn’t that you can’t write a program in any language (you can!); it’s that down the road when you start to use the programming language, you might run into a bump or two. If you’re looking for a job, you might want to pick a more popular language. If you’re looking to get into a specific field – say data analysis or game design or interactive visualizations – you’ll want to pick a language that’s better suited for the task. Let’s take a look at the pieces that make up a programming language, and then examine a few of the more popular languages to figure out what’s a good fit for you. We picked Python for the majority of what we do in the Lede Program – maybe you’ll see why! What’s a programming language? In their heart of hearts, computers talk something like this: 00101110100101010010010 Whether you’re multiplying huge numbers or Googling cat pictures, every single computer instruction is broken up into an unreadable series of 1’s and 0’s called binary code. Since humans aren’t so good at communicating in binary, we invented programming languages to serve as an intermediary. Programming languages that are closer to binary code are called low-level languages, while more human-seeming languages are high-level. The CPU in...

Data Work 101: Absolutely everything* you need to know to work with code or data

This is post 1 of 3 in the series “Data Work 101” When I talk to people who are curious about the world of programming, or working with data, or who even just like looking at visualizations, they always have one big question: How can I do that? Unfortunately, these conversations usually happen at a bar or a party, and since it’s generally thought of as impolite to put strangers to sleep, I can never quite give them the full story. The quick, party-friendly version begins and ends with “Well, it depends on what you’re interested in.” But now I’m taking the opportunity to fill in the bits in the middle! If you’re interested in getting into data, programming or visualization, this series is for you. And it may be for you even if you aren’t into that (yet), too. What is this guide? This is not a guide to teach you concrete skills. When you’re curious about becoming a woodworker, you don’t jump right into learning how to use a bandsaw – you take a look at some tools, figure out what you want to make, and then get on into things. Before you decide what to learn, you need to know why you’d learn it and how all of the pieces fit together. That’s what this guide is: It’s the front of the 1,000-piece puzzle box that helps you understand how all the pieces go together. We’ll be talking here about theory, about tools, about everything in the world of programming and data except walkthroughs and tutorials. You decide what’s best for you, then you can head off and learn it! Table of Contents This is just off of the top of my head – I’ll be adding links and switching things up as we go...