Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
Markdrop
BugHerd
Pastel
Webvizio
Matplotlib
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Markdrop's answer:
Markdrop combines powerful visual feedback, screen recording, and developer-ready bug reporting into a single, lightweight tool that feels invisible until you need it. Unlike bloated alternatives, Markdrop is fast, easy to integrate, and built for modern teams who care about speed and clarity with no Chrome extension or signup friction required.
Markdrop's answer:
Affordable, transparent pricing: Markdrop offers all the core features at a fraction of the cost of tools like Markup.io or Pastel.
Designed for devs and designers: Every comment can include logs, screen recordings, and environment data ready for developers to act on.
No friction for users: Share a link and anyone can leave feedback. No browser extensions, no accounts, no hassle.
Fast and privacy-respecting: Lightweight script, GDPR-compliant, and zero tracking bloat.
All-in-one: Combines comments, annotations, bug reporting, and async video so teams donโt need 3 different tools.
Markdrop's answer:
Markdrop is built for:
Founders and indie builders who want fast feedback without complex tools
Designers and PMs collecting client or stakeholder feedback
Developers who want bug reports with context, not vague screenshots
Agencies delivering websites and apps that need client review In short, itโs for lean product teams who value clarity and speed.
Markdrop's answer:
Markdrop was born out of frustration. As a solo founder building multiple products, I (Manuel) kept running into the same feedback pain, long email chains, vague bug reports, and overpriced tools that did too much or too little. So I built what I needed: a clean, no-fuss tool to drop comments directly on a site, see what users saw, and get back to shipping.
Markdrop's answer:
Which are the primary technologies used for building your product?
Frontend: Svelte 5 Backend: Cloudflare Workers, D1, and Durable Objects Database: Wrangler DB (D1) DevOps/Infra: Cloudflare Pages + R2 for static assets and file storage
Markdrop's answer:
Indie founders using Markdrop to launch and iterate faster
Agencies working with clients.
YC applicants using it to get fast design review
No-code builders collecting client feedback inside Webflow
Internal product teams replacing Slack screenshots with structured feedback
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 / 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.
BugHerd - BugHerd: The Website Feedback Tool for Agencies
NumPy - NumPy is the fundamental package for scientific computing with Python
Pastel - Sticky note-based feedback collection tool for live websites
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.
Webvizio - This free website feedback tool & website review software allows managers and teams to collaborate on website revisions in real time. Join for free now!