Data visualization has been a growing trend in the past few years, and it doesn’t show any sign of slowing down.
So, if you have been trying and failing to find the right one for your needs, you are in luck, as this blog post will educate you to choose the best JS visualization library for you.
This process typically involves converting raw data into visual representations such as charts, graphs, and diagrams.
This pictorial form of data is often in high resolution, allowing viewers to make sense of the information being conveyed.
A charting library is a tool that makes it easier to create visualizations like charts, graphs, and diagrams.
These libraries take raw data and convert it into visual representations that can be used in charts, graphs, or other visualizations.
The charting libraries featured in this article are primarily focused on 2D representations. Some of the most common types of visualizations include:
A data chart is represented by rectangular bars with a length proportional to the values they represent.
A chart that uses bubbles instead of bars to visualize data.
A chart that uses a line to visualize the change in numerical data over time, such as stock prices or the amount of carbon dioxide in the atmosphere over the years.
A chart that uses pie-shaped wedges to represent parts of a whole.
A visual representation of geographical data often maps.
Each of these libraries has its strengths and weaknesses. However, all of them are capable of creating stunning data visualizations that can bring your data to life.
This data transformation makes it easy for the reader to understand the results with a glance.
Ease of use:
The most important thing to analyze is the ease of use. Analyze if the tool is easy to use? Can you get up and running quickly, or do you need to spend a lot of time learning the API?
This will give you a clear vision if the chosen tool is right for you or not?
The next thing to question is the flexibility of the tool. How flexible is the library? Can you create the exact visualization you want, or are there some limitations?
You don’t want to be stuck with a basic library. Thus, it is essential to evaluate what features the library provides.
A dynamic tool will always be beneficial as it can give you the best value for your money and time. It can also enhance user engagement by strengthening the UI and UX of your web design.
Last but surely not least, we have the documentation. Thus, always question how good is the documentation?
Is it easy to find what you’re looking for, or do you need to spend a lot of time searching for answers?
Once you are done considering these factors, you can narrow down your options and choose the best JS visualization library for your project.
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Now we can finally get to the list of the best of the best. So without further ado, let’s jump right into it.
1. NVD3 – A Charting Library for HTML and SVG
NVD3 is a charting library that uses HTML and SVG to generate charts, allowing cross-browser compatibility.
This library uses the data-driven design principles behind D3.js to create charts that can be customized to a high degree.
This library is particularly well-suited for displaying financial data, as it can generate a wide variety of standard chart types, such as bar, line, scatter charts, candlestick and hexagram charts to represent financial data.
2. D3.js – Data-Driven Documents
D3.js focuses on transforming data into visual representations, either as static images or interactive HTML/SVG documents, meaning that D3.js can also be used for creating visualizations without static images.
D3.js is remarkably flexible, and an expansive library of reusable charts can be used with data visualization projects.
Vue-Charting is a data visualization library explicitly built for Vue.js. It comes with a selection of charts, ranging from bar charts to candlestick charts, that can be used out of the box after some minimal configuration.
Vue-charting works with your Vue.js app through Vue.js’s built-in component syntax, making it easy to integrate into your project.
Depending on the Chart you want to use, you will need to install the corresponding NPM package and then simply import it into the component file for your Chart.
4. Ad Hoc
While ad hoc charts are designed to work out of the box for many types of charts, it also provides several options for customization, allowing you to pick and choose how you want to build your charts.
Chart.js ships with a wide selection of chart types, such as line, column, or area charts, pie and donut charts, gauge charts, and more.
Chart.js also allows you to create custom chart types if you don’t see what you need in the chart library.
6. React Chart
Once you’ve chosen the chart type you want to use, you need to pass in data representing the information that the Chart will display.
This data needs to be formatted specifically for the Chart to work correctly.
7. React Plotly
React Plotly is a React wrapper for the Plotly charting library. It allows you to build interactive charts using Plotly’s charting library.
If you have never used Plotly before, you can create an account and use the data visualization tool to create the charts you want to use.
Once you have created the charts you want, you can use a tool like CSV2JSON to convert the data from CSV to JSON format. Then, you can feed the JSON data into your React app to create the Chart.
8. Google Charts
It is an online tool that allows you to create and customize charts and graphs for data visualization. The integration of Google charts is straightforward, with various features.
Highcharts is another library that can be used for data visualization. It is easy to use and has a wide range of features.
Moreover, supports charts and graphs, such as bar charts, pie charts, line graphs, etc. It also has features for exporting data to different formats, such as PDF, Excel, CSV, etc.
It is a commercial library that provides various charts and graphs for data visualization. It is easy to use and has a wide range of features, making it an excellent choice for data visualization.
Frequently Asked Questions (FAQs)
However, you can quickly generate visual representation by integrating raw data with the library.
It is also effortless to use, making it a good choice for those new to data visualization.
You must have significant knowledge of integrating the raw data using a specified library.
However, you don’t need to be a master of coding, as the syntax of aligning data with the tool for data representation is straightforward.
This way, you can pick the JS visualization library for your project and make your project stand out with visualizations that are more engaging than ever before.