The problem

Life is tough!

We've built many graphs already, and you should be able to draw almost anything on a screen by now.

However, our datasets have always looked perfect so far. A clean JavaScript object that always looked a bit like this:

const data = [
  { country: 'USA', value: 12 },
  { country: 'France', value: 9 },
  { country: 'Japan', value: 7 },
];

Sometimes life is as simple as this. But often, a whole bunch of complexity shows up. Here are the problems you can run into, with a link to the lesson that explains how to fix each one.

📦 Data is not always in JSON

JSON is the best-case scenario for us JavaScript developers, as it's pretty much the same thing as a JavaScript object.

But data can come in many other formats: .csv, .xlsx, GeoJSON, and more. There are tools and techniques to deal with them too!

🧹 Data can be messy

Real data has missing values, the wrong types, and the wrong shape.

Some data wrangling is almost always necessary: filtering, grouping, merging, reshaping, aggregating... Let's see how to perform those everyday tasks that make up a big part of a data analyst's life!

🛜 Data can be remote

A lot of applications visualize dynamic data. You might want to track the evolution of the Bitcoin price, or query your company's database for the latest sales.

In that case, your app fetches the data from another web server and displays it once it arrives. Let's see how this is possible with JavaScript.