Learn D3, Leaflet and Serverless

In this course, Colby is going to do a deep dive into creating a full store for your products. You'll learn how to set up and use GraphCMS as your content management system. You'll learn about the Cloudinary UI extension and how to use it to host your images. You'll learn about Snipcart and using the useSnipcart hook to handle the cart state and the checkout. You'll learn how to implement Stripe as your payment gateway. And lastly, you'll learn how to deploy a Next js app to vercel from github with environment variables.

snipcart

Ecommerce Product Management & Storefront with GraphCMS, Snipcart, & Next.js

Starting from a prebuilt frontend, Jason Lengstorf guides you through the creation of a "Corgi Up-boop App" that uses Netlify Functions and Hasura. You can view [the deployed final product on Netlify](https://egghead-serverless-functions.netlify.app/).

You'll set up the Netlify CLI, and configure a local development environment before writing and deploying functions with a few different use cases.

The first example function bypasses CORS restrictions to retrieve corgi data from an example third-party API.

Next, you'll configure environmental variables to securely communicate with the Unsplash API without exposing private keys to the client.

Serverless functions don't persist data by themselves, so we will use  Hasura to create a GraphQL API for tracking the number of "boops" each corgi receives.

This course is an excellent illustration of the speed of Serverless functions, and how fast you can implement functionality in your web applications.

An all-in-one workflow that combines global deployment, continuous integration, and automatic HTTPS.

netlify

Build a Corgi Up-boop Web App with Netlify Serverless Functions and Hasura

If you've ever worked on a website for a business, there's a good chance you've included a map.

A Google Map embed is sufficient for showing a location, but doesn't leave you many customization options.

React Leaflet to the rescue!

In this course, Colby Fayock will guide you through a series of lessons and challenges that will build your map making skills as you build out a web app for a fictional restaurant.

You'll get practice with handling API keys and using React Hooks to implement a custom interactive map complete with metadata and additional overlays.

This course has built-in challenges that you are encouraged to pause and work through, but feel free to just watch.

React is one of the web’s most popular frameworks for building JavaScript applications. 

If you know what you’re doing, React can drastically simplify how you build, use, and maintain code.

Whether you’re a React newbie or you’re ready for advanced techniques, you can level-up with egghead. Explore our in-depth courses, lessons, and community resources to build more powerful applications and crack open your career.

react

Build Maps with React Leaflet

In this collection, you'll learn the basics of creating a new map in your React application with React Leaflet. We'll walk through adding the map itself as well as adding markers with popups, different shapes, and increasingly complex features to your map!

Mapping with React Leaflet

D3, or Data Driven Documents, is the defacto standard for data visualization on the web. It's an incredibly powerful library that gives you all the tools you need to build just about visualization you can dream of.

D3 is not a collection of predefined charts. Instead, it's a robust set of utilities you can use to ingest and transform data, to map that data to screen values, and ultimately to manipulate the DOM to render your visuals.

When working with React, D3's desire to manipulate the DOM is at odds with React's goal of rendering the UI as a function of state. So how do we handle this? Simply put, we use D3 for everything up to the point where we want to render our output, and then we hand all that data to React for rendering.

In this course, we'll start from scratch and build out an SVG bar chart for some sample data. We'll lean on D3 for its tools and then hand that data off to React for rendering.

Create A Bar Chart with React and D3

Create a serverless application and deploy it in under thirty minutes!

We'll be using Netlify, Vite, TypeScript, and React in our project. This stack synergizes extremely well for rapidly developing professional-quality applications. 

If you haven't heard of Vite, it's the French word for quick! It's also a build tool that consists of a dev-server and an extremely fast bundler. It makes for a rapid development loop.

As for the rest. Netlify makes hosting fast and easy with serverless functions and continuous deployment. React enables you to quickly create reusable components. And TypeScript helps you write cleaner code that is easier to refactor. 

So get started and learn how to use this stack in your own applications!

Deploy a Serverless API React Application with TypeScript

In this course we will learn and demonstrate the fundamental concepts and APIs of D3, on our way to building several common chart types. We’ll start with the building blocks upon which all D3 visualizations are built; things like scales, interpolators, and selections. We’ll see how to load data with D3, and how to put its full name, Data Driven Documents, into action. We’ll build column and bar charts, scatter plots, and area charts. Most importantly, we’ll gain an understanding of the conventions and patterns that underlie all D3 projects and examples, enabling you to dissect, understand, and build virtually any D3 visualization on the internet.

D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG and CSS. D3’s emphasis on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework, combining powerful visualization components and a data-driven approach to DOM manipulation.

Build Interactive JavaScript Charts with D3 v4

This course covers D3 v3. If you'd like to learn about v4 of D3 (the latest version) [click here for the course on that](https://egghead.io/courses/build-interactive-javascript-charts-with-d3-v4).

This series will gently guide you through the first steps in getting to know D3. The curve can be steep, but with a few simple tools, you'll be charting your buns off in no time flat.

Use D3 (v3) to Build Interactive Charts with JavaScript

Most of D3’s native selection APIs also return the selection (or a new selection), to enable multiple method calls to be chained together. Since the code you write isn’t on the selection prototype, chaining your methods would take some extra work. `selection.call()` will call any function reference you give it, providing the selection as the first parameter, and then it returns the selection for you to ensure chaining is supported.

Better Code Organization with selection.call() with D3 v4

Making SVGs responsive is unfortunately not as simple as adding some media queries. This lesson introduces the `viewBox` attribute, which is used to control how SVGs scale. We’ll also examine a reusable function that can be used to make nearly any visualization responsive.

Make D3 v4 Charts Responsive with the viewBox attribute

In D3, the General Update Pattern is the name given to what happens when a data join is followed by operations on the enter, update, and exit selections. When a chart's data changes over time and each update can both create new elements and destroy existing ones, the General Update pattern can help convey meaning to users. This lesson demonstrates the pattern using animated transitions on a column chart.

Animate with the General Update Pattern in D3 v4

Ensuring your charts are responsive is essential if you want them to work regardless of the user's device and screen size. In this lesson we'll learn how the viewBox attribute of SVG elements works, and apply that knowledge to make a future-proof D3 chart.

Responsive D3 charts with the viewBox attribute

Since D3 outputs standard markup, you can use familiar dev tools and inspectors to debug your visualizations. In this lesson we’ll look at how to use Chrome Dev Tools to examine the data associated with your generated markup and experiment with styles to speed up the development process.

Debug D3 v4 with Dev Tools

D3 makes it easy to add meaningful animations to your data visualizations. Whether it’s fading in new items or tweening existing shapes to display new values, adding transitions is easy. This lesson shows you how to add animations while building on your existing knowledge of D3 selections.

Animate Transitions in D3 v4

Create a line chart, then easily convert it to an area chart

Line and Area Charts with D3

Mapping abstract values to visual representations is what data visualization is all about, and that’s exactly what D3 scales do. This is usually done using pretty straightforward algorithms, but nothing is straightforward when you’re working with Date objects in JavaScript. If you’re plotting temporal data, you need to use a time scale.

Convert Dates to Numeric Values with Time Scales in D3 v4

Sometimes data needs to be converted from a continuous range, like test scores, to a discrete set of output values, like letter grades. In this lesson we’ll see how to use `d3.scaleQuantize()` to do exactly that.

Create Labels from Numeric Data with Quantize Scales in D3 v4

AngularJS is an open-source JavaScript framework, maintained by Google, that assists with running single-page applications. Its goal is to augment web-based applications with model–view–controller (MVC) capability, in an effort to make both development and testing easier.

angularjs

Integrating D3 with Angular can be very simple. In this lesson, you will learn basic integration as well as how to create D3 charts that can be packaged as AngularJS directives.

Create a D3 Chart as an Angular Directive

As of version 4, D3 is a completely modular tool, composed of many small libraries. You can use them independently or as a whole, and even create custom builds that include only the parts you need. This lesson will review the options available for installing and using D3, and will set up a local environment for rapid experimentation.

Install and Configure D3 v4

When your data contains discrete, non-numeric property values that you need to format or convert before displaying, `d3.scaleOrdinal()` is the API you need. Maybe you need to convert a “pass”/”fail” field to “green”/”red” for coloring your bubble chart? This lesson shows you exactly what to do.

Create Labels from Non-numeric Data with Ordinal Scales in D3 v4

Mapping abstract values to visual representations is what data visualization is all about, and that’s exactly what D3 scales do. Turning a test score into a column height, or a percentage into an opacity requires translating from one set of possible values to another, and linear scales perform a direct, proportional conversion of inputs to outputs. In this lesson we’ll learn the basic API of D3 scales and how to use them.

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