Archive for the JavaScript chart tutorials

How to Build Box Plot Using JavaScript: Visualizing World Happiness September 22nd, 2020 by Wayde Herman

A box plot visualizing world happiness report data, the cover image for a guide on how to build interactive box plots with JavaScript HTML5Data visualization is an important and sometimes undervalued tool in a data scientist’s toolkit. It allows us to gain an understanding and intuition about the data, through exploratory data analysis, which influences preprocessing, feature engineering, and the correct machine learning algorithm choice. It also helps to better evaluate models and even allows you to spot areas in the data where models could have poor performance.

Taking data visualization one step further by adding interactivity is even more advantageous. By adding interactive elements to your visualizations you create a more engaging experience. This in turn makes a user ‘explore’ visualizations instead of just reading them!

In this tutorial, I will be covering how to build an interactive data visualization, specifically a box plot as an example, using JavaScript and a charting library. I will begin by first briefly covering the basics of box plots before going through the steps of building one and then finally using the technique in a fun example to investigate the distribution of happiness between the different regions of the planet in an attempt to answer the question: ‘Where should you live to be happier?’.

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Connecting a MySQL Database to a JS Chart Using PHP August 4th, 2020 by Wayde Herman

Connecting MySQL Database to JS Chart Using PHPWhen using a charting library like AnyChart, which makes visualizing data so quick and easy, often the most challenging step for beginners is loading data. I think this is largely a result of the fact that while the ways we output the data are quite similar, the input data is commonly very different. The data may differ in many ways including the number of features in the dataset, what type these features may be, the format of the data, and how the data is stored. It is this final issue which we will be addressing today.

There is a lot of coverage in the documentation of using a data object declared within the code as well as importing your data from a file using AnyChart’s data loader. But what about importing the data from an SQL database? This is an easily done but often misunderstood approach to handling and loading data for data visualizations.

Unfortunately, it is not possible to use JavaScript to query a database because JavaScript is a client side solution and querying a database requires a server side approach due to security concerns — you just can’t store database login and password in your JavaScript code. There are many workarounds for this problem including approaches involving PHP, Ajax, Node.js, and many more. Today we will focus on using PHP to handle this task for us when our data is stored in MySQL.

In this tutorial, we will be covering how to query a MySQL database using PHP. We will describe the steps involved and reveal that it is in fact not challenging at all, just different!

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How to Create JavaScript Network Graph July 22nd, 2020 by Wayde Herman

How to create a Network Graph using JavaScript HTML5 for the webNetwork graphs are a special, very interesting form of data visualization. Unlike more traditional chart types like bar graphs or pie charts, a network graph does a bit more than visualize numerical data. With these charts, you represent each object as a point, referred to as a node, and the connections between the objects as a line, referred to as either a link or an edge. Here, we do not focus on representing objects with the same precision we are typically used to. Instead, we are trying to discover relationships in a network or sections of a network and are less worried about individual nodes.

Right now, I will guide you through how to develop an interactive network graph for the web using JavaScript (HTML5). Inspired by one fun visualization created by Ben Sullins, I decided to take data about the last decade’s biggest TV series, Game of Thrones. It is an epic fantasy tale revolving around the quabbles of various faction-like houses. So in this tutorial, I will be visualizing the relationships in the world of Game of Thrones by showing who attacked whom. Follow me, it’s going to be a cool adventure!

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Building a JavaScript Radar Chart July 7th, 2020 by Wayde Herman

Tutorial explaining how to create and code an interactive Radar Chart in JavaScript HTML5Radar charts, which are also referred to as spider charts or radar plots, are a data visualization used to compare observations with multiple quantitative variables. Each variable is encoded to a spoke which are equidistant apart. The higher the value, the further away from the center of the chart the point is made. Radar charts are best used to compare the ‘profile’ of observations and to detect outliers within the data. They are therefore used quite a bit in sports, most notably in basketball and soccer for profiling players.

In this tutorial I will be teaching you how to build your own radar chart with JavaScript and how to use them to help with one of the toughest decisions in gaming history: which starting pokemon to choose!

That’s right, we will be building radar charts to perform data analysis on Bulbasaur, Charmander and Squirtle to determine, once and for all, which is the best choice.

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How to Create Stacked Area Chart with JavaScript June 10th, 2020 by Anastasia Zoumpliou

JS stacked area chart and percent stacked area JS chart visualizing key COVID-19 data for Italy over timeStacked area charts, a variation of classic area charts, are quite a popular form of data visualization. They work great to graphically represent how multiple variables and their totals are changing over time. In this tutorial, I will show you how to easily create an interactive JavaScript stacked area chart which will look compelling in any HTML5 project, web site or app.

To demonstrate this way, which is quite simple to master even if you only have basic HTML coding skills, I am going to visualize official data about the outbreak of the COVID-19 pandemic in Italy. The visualizations built along the tutorial will display how the numbers of cases, recoveries, and deaths have been changing — from January 31, when the first two cases were confirmed, to yesterday, June 9, when the total number of coronavirus cases in Italy reached 235,561.

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Building a JavaScript Scatter Plot Module May 27th, 2020 by Wayde Herman

Tutorial title image of a JavaScript Scatter Plot module (scatter chart)Scatter plots are a great way to visualize data. Data is represented as points on a Cartesian plane where the x and y coordinate of each point represents a variable. These charts let you investigate the relationship between two variables, detect outliers in the data set as well as detect trends. They are one of the most commonly used data visualization techniques and are a must have for your data visualization arsenal!

In this tutorial, I will teach you how to build your very own interactive scatter plot charts using JavaScript.

Ever wondered whether the population of the United States of America were dog people? Well, you’re about to find out! To help you learn more about building scatter plots I will be using the Cat vs Dog Popularity in US dataset. This dataset contains the percentage of homes with dogs and cats for each US state.

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Creating Choropleth Map Data Visualization Using JavaScript, on COVID-19 Stats May 6th, 2020 by Anastasia Zoumpliou

Creating a choropleth map data visualization using JavaScript (JS HTML5)These days you see choropleth maps in a variety of webpages and utilized for various subjects. Have you wondered how such data visualizations are built? Are you interested in making them by yourself? If so, stay with me through this JS charting tutorial, where I will show you how to create an interactive JavaScript choropleth map from scratch but with ease.

Basic knowledge of HTML5 and JS is always helpful, but even if you are a beginner in this field, understand these four simple steps and you will be able to quickly get a good-looking cross-platform interactive choropleth map data visualization for your app or website!

What exactly are choropleth maps? When you break down the word, you see that choro- (“choros”) means “area” and pleth- (“plethos”) means “multitude.” Exactly, these maps are used to visualize statistical data related to multiple geographic areas. Each area is colored or shaded differently according to the value of the given data, making it easy to grasp how a measurement varies across a territory.

For this JS mapping tutorial, I will use open COVID-19 data to show the distribution of confirmed cases and deaths around the world by country. I will start with a basic choropleth map that will graphically represent the confirmed cases. Then I will add a legend, customize the tooltip, and add bubbles to visualize the number of deaths.

Let’s get started!

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Creating JavaScript Column and Bar Charts on COVID-19 Data April 6th, 2020 by Jay Stevenson

Laptop with a JavaScript chart visualizing the latest COVID-19 data illustrating a tutorial on how to create JavaScript column and bar chartsNeed compelling JS charts for your website or app? Start with the basics! Complete this quick data visualization tutorial and you’ll learn how to easily create JavaScript column and bar charts that will look great in any HTML5-based project, allowing for easy comparisons.

Chart examples to be built and demonstrated in this tutorial will be visualizing the latest novel coronavirus cases data from JHU CSSE as COVID-19 is the most topical issue nowadays.

Keep reading and you’ll see JS charting is actually very simple. Especially if you have at least a very basic understanding of programming (more than that is awesome but far from necessary).

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Making a JS Candlestick Chart in Four Simple Steps March 25th, 2020 by Anastasia Zoumpliou

A JS Candlestick Chart on the screen of a laptopDo you have trading data, looking for a way to effectively visualize it for your website or app project? If so, a JS candlestick chart could be your best pick. This tutorial will break down the process needed to create such a chart into simple steps and provide a detailed explanation of the code. Keep reading even if you are new to programming, because only a basic understanding is needed to follow along and master such a JavaScript (HTML5) based data visualization technique.

Also called a Japanese candlestick chart, this chart type is one of the most popular forms of financial and stock data visualization. Each candlestick represents information about the open, high, low, and close price of the day. Candlestick charts are widely used in technical analysis of price movement patterns.

Complete this tutorial and you will be able to create a compelling interactive candlestick chart in JavaScript real quick, with ease.

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How to Create JavaScript Bubble Chart — Tutorial for Web Developers March 3rd, 2020 by Wayde Herman

Making a JS bubble chart is described step by step in this tutorial for web developersHave you ever wanted to create a bubble chart using JavaScript but did not know how? Then this tutorial is for you! Carry on reading to learn more about bubble charts and how we can build them quickly and painlessly.

Bubble charts are an extension of the scatter plot. Most commonly, they display three variables which are expressed as the horizontal distance of the point (x), the vertical distance of the point (y), and the size of the point (z). A bubble chart is a great visualization technique to let users compare data points. When designed well, it can be really eye-catching and engaging.

In this tutorial, I will teach you how to build your very own interactive JS bubble chart and bring it to life through customization. All examples will be available with the full code.

For this “getting started” guide, I have decided to explore the data of the top 30 grossing movies. Let’s look at the amount of money each movie has grossed, the budget, as well as the year of release. A bubble chart is a particularly good choice for the visualization of this dataset as it will allow us to easily compare these three numeric variables in an interesting and beautiful way.

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