Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
liveGap Charts
CanvasJS
D3.js
RAWGraphs
Plotly
ZingChart
Chart.js
Highcharts
Livegap Charts is a fast, easy-to-use online tool for creating beautiful charts and data visualizations directly in your browser. No downloads, installations, or subscriptions are requiredโjust open your browser and start designing.
Completely Free: All features available without signup. Browser-Based: Works online without installing software. Multiple Chart Types: Line, bar, stacked bars, radar, polar area, pie, doughnut, and icon charts. Customizable: Colors, labels, icons, and layouts can be easily adjusted. Live Data Support: Connect CSV or Google Sheets (Pro version) for dynamic charts. Export Options: Download charts as PNG, SVG, or use them directly in presentations and websites. Language Support: Fully supports numbers and labels in Arabic, English, and other languages.
Livegap Charts is used by thousands of users daily and ranks among the top online chart makers. Perfect for educators, students, marketers, or anyone who wants to visualize data professionally and effortlessly.
Matplotlib
liveGap ChartsliveGap Charts's answer:
liveGap Charts's answer:
Livegap Charts makes chart creation truly effortless. Unlike many alternatives, you donโt need to download software, sign up for paid plans, or learn complicated interfacesโjust open your browser and start building. It combines simplicity with powerful features, offering a wide range of chart types (bar, line, pie, radar, polar area, doughnut, and icon charts) and customization tools that let anyoneโfrom students to professionalsโcreate polished visualizations in minutes.
Itโs 100% free, fast, and browserโbased, with multilingual support including Arabic, making it accessible to a global audience. Plus, features like Google Sheets/CSV integration and export options (PNG/SVG) mean you can use your charts anywhereโpresentations, reports, websitesโwithout friction. Whether youโre visualizing data for work, school, or personal projects, Livegap Charts delivers the power of complex tools with the simplicity of a dragโandโgo interface.
liveGap Charts's answer:
Need an easy-to-use tool to create charts for assignments, reports, presentations, or classroom projects. Benefit from multilingual support, including Arabic, and quick chart creation without complex software.
Marketers, data analysts, business professionals, and researchers who require fast, professional-looking charts for reports, presentations, and websites. Appreciate features like CSV/Google Sheets integration and customizable chart styles.
People producing infographics, blog posts, or social media content that requires visualizing data clearly and attractively. Use icons and multiple chart types to make visuals more engaging.
Anyone who wants to visualize personal data, hobby stats, or simple datasets without learning programming or complex software. Attracted by the free, browser-based, and no-signup-needed approach.
liveGap Charts's answer:
Livegap Charts began as a simple idea: make data visualization easy, free, and accessible to everyone. Its founder saw that many chart tools were either too expensive, overly complex, or required software installations and steep learning curvesโbarriers for students, educators, professionals, and casual users alike.
Driven by the belief that good data deserves beautiful presentation, Livegap Charts was built as a browserโbased chart maker that works instantly without signup or downloads. Early versions focused on the essentialsโbar, line, and pie chartsโbut gradually expanded to include a wider range of chart types (like radar, polar area, and doughnut charts), customization options, and support for multilingual users, including Arabic numbers and labels.
Over time, its simplicity and power attracted thousands of daily users worldwide. The tool continued to improve with user feedback, adding features like CSV and Google Sheets integration, export options (PNG/SVG), and enhanced styling capabilities.
Today, Livegap Charts stands as a free, easyโtoโuse platform that empowers anyoneโfrom students doing school projects to professionals presenting dataโto create clear, compelling charts quickly and without barriers.
liveGap Charts's answer:
HTML5 & CSS3 โ Structure and styling of the web interface. JavaScript / ES6 โ Core logic for chart creation, interactivity, and dynamic updates. Vue.js โ For reactive UI components and live chart previews. Canvas Rendering charts in the browser for high-quality graphics.
Based on our record, Matplotlib seems to be more popular. It has been mentiond 114 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 5 months ago
Numbers are useful, but sometimes itโs easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 8 months ago
We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 9 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 10 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 11 months ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
CanvasJS - HTML5 JavaScript, jQuery, Angular, React Charts for Data Visualization
NumPy - NumPy is the fundamental package for scientific computing with Python
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.
RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...