Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
AECharts
Flourish
Pie Chart Maker
LivingCharts
PieChartMaker.co
AEInfographics
PieChartMaker.me
Charts Factory
AECharts is a web-based tool for creating animated chart videos. Users paste or upload data, choose a template, customize the styling, and export a polished MP4 โ no video editing software or design skills required.
The workflow is simple: bring in your data via paste, CSV, Excel, or Google Sheets. AECharts parses it automatically. Select a chart type and template, customize colors, fonts, labels, and animation speed in a live-preview editor.
When you're done, export a full MP4 video ready for presentations, social media, or reports.
Chart types include: - Vertical and horizontal bar charts for category comparisons - Line charts for time-series trends - Pie charts for part-to-whole relationships - Bar race charts for animated rankings over time - Gauge, waffle, and Sankey diagrams for specialized use cases
The rendering engine is built on PixiJS (WebGL) and GSAP animations, producing smooth, high-quality output. Templates are designed to follow data visualization best practices out of the box.
User accounts are backed by Firebase with automatic cloud saving โ no save button, no lost work. Your file library persists across sessions with full edit history.
AECharts is built for marketers, founders, journalists, and content creators who want to turn data into compelling visual stories without the overhead of motion graphics tools. Where Datawrapper and Flourish made static charts accessible to non-designers, AECharts does the same for animated video.
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AECharts's answer:
AECharts is unique because it turns raw data into ready-to-share animated chart videos in seconds.
Upload CSV or paste data โ get MP4/WebM charts instantly
Built for video, not dashboards. Perfect for Reels, TikTok, YouTube, slides
Fully customizable charts: colors, labels, axes, animations
No After Effects, no templates, no design skills needed
Exports lightweight videos optimized for social and web
Runs in the browser. No installs. No login required
Made for creators, journalists, marketers, and analysts who need visual data fast
Most chart tools make images. AECharts makes motion.
AECharts's answer:
Choose AECharts over competitors because itโs the fastest way to turn data into shareable animated visuals with zero design work.
Video-first output: Unlike static chart tools, AECharts generates MP4/WebM animations ready for social platforms and presentations.
No software to install: Works entirely in the browser โ no plugins, downloads, or steep learning curves.
Auto smart layouts: Automatically positions labels, colors, and axes so charts look polished without tweaking.
Speed and simplicity: Seconds from data to video versus hours in traditional design tools.
Custom branding: Easy control of fonts, colors, transitions to match your style.
Lightweight exports: Optimized video files for web, mobile, and social engagement.
In short: AECharts delivers animated, on-brand data visuals faster and easier than any alternative.
AECharts's answer:
People who need data to work on video.
Content creators making Reels, TikToks, YouTube, Shorts
Journalists and media pages posting data stories
Marketers creating social ads and explainer videos
Analysts who want charts that move, not just screenshots
They care about speed, shareability, and visual impact, not dashboards or BI tools.
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 / 4 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 / 7 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 / 8 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 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 / 10 months ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Flourish - Powerful, beautiful, easy data visualisation
NumPy - NumPy is the fundamental package for scientific computing with Python
Pie Chart Maker - Craft stunning, customizable pie charts in a snap! - PieChartMaker
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.
LivingCharts - Create animated charts and turn your data into engaging videos without coding.