The data explosion in recent years has led to a corresponding need for businesses and organizations to communicate information in a way that’s accessible and engaging to different audiences. Visual content is becoming an increasingly popular means for sharing data.
Data visualization relies on visual representations like graphs or charts to convey raw data. Presenting data in a visual manner makes it easier to understand and faster to process, even for those who aren’t mathematically inclined or trained in analytics. Each visual data representation tells a story about the data, which can lead to more informed business decisions and favorable outcomes.
There are many different kinds of data visualizations, such as maps, histograms, scatter plots, and pie charts. Those who know how to present information in visually engaging stories have the power to help make sense of past events, provide insights on current trends, and offer predictions for the future.
What is a Data Visualization Library?
Data visualization libraries are designed to help users break down complicated ideas and create visualizations that depict this information. Choosing a data visualization library plays an important role when working with large or complicated datasets, as it can affect the kinds of insights taken from the data. There are many options to choose from, so it’s important to learn about the specific features of each to decide which library is best for your data visualization needs.
- Interactive capabilities
- Rich interfaces that feature drag-and-drop components
- Because it is an interpreted language, it is quicker to use than other programming languages.
- Regular updates
- Prompt feedback to visitors
- The versatility of use through Node.js servers
- Apache Echarts: This free, open-source data visualization and charting library makes it easy to add interactive, intuitive charts into visualizations that will be posted online. It also provides options for customizing charts. Echarts can handle large datasets and is well-documented in English. Users such as Intel and Amazon rely on this library for their data visualization needs.
- Highcharts: Because it is completely based on native browser technologies, Highcharts doesn’t need client-side plugins such as Flash. It performs well in all modern browsers, even mobile devices.
- Toast UI Chart: This statistical data visualization library offers users an identical look in all browsers. It performs quickly and is easy to use, and includes options to customize themes.
- Victory: This library designed for modular charting was designed for React and React Native. It provides users with simple ways to customize labels and apply distinct datasets for specific graphs. In addition, Victory has a range of cross-platform applications, as well as several user-friendly components that can help simplify the charting process. This flexible, robust library doesn’t require extensive coding knowledge and offers a variety of options to create engaging and informative graphs.
- Recharts: This compostable charting library built on React components allows users to customize charts and add effective interactions to various chart elements. Its API is easy to use and can support multiple types of shapes, charts, and components.