Marker.io
BugHerd
Usersnap
Userback
Bird Eats Bug
Pastel
Markup.io
Bugasura
Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
Collect website feedback from your team, clients, and users.
Get feedback with screenshots & technical metadata directly into your favorite project management tool.
Say goodbye to messy emails, spreadsheets and powerpoint. There is a better way!
Marker.io
MatplotlibBased on our record, Matplotlib seems to be a lot more popular than Marker.io. While we know about 114 links to Matplotlib, we've tracked only 8 mentions of Marker.io. 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.
Marker.io is a feedback tool that allows users to attach product comments to a given UI component in an app. Itโs overlaid on the UAT environment, and allows users to export screenshots and logs alongside their review comments. User feedback comments can be automatically converted to tickets. - Source: dev.to / over 1 year ago
This is a really nice note and solution of the problem. What is the difference from your competitor https://marker.io/? - Source: Hacker News / over 3 years ago
I'm looking for a free and/or open source self-hosted alternative to marker.io for visual bug tracking/reporting. Source: over 3 years ago
Also keep an eye on this discussion to make issue forms available on private repos. Until this is possible, marker.io & Linear are a solution. Source: about 4 years ago
I work for a really small startup ( https://marker.io ) that focuses on drastically improving website feedback workflows for agencies/ clients. In some cases agencies say:. Source: over 4 years ago
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
BugHerd - BugHerd: The Website Feedback Tool for Agencies
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Usersnap - Usersnap is a customer feedback software for SaaS companies that need to constantly improve and grow their products.
NumPy - NumPy is the fundamental package for scientific computing with Python
Userback - Userback empowers product teams to collect, understand, and act on user feedback with unprecedented speed and clarity.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.