Matplotlib VS Upvoty
Compare Matplotlib VS Upvoty and see what are their differences
Seranova AI helps home service businesses automate review outreach, stay on top of customer conversations, and grow reputation without extra headcount.
featured
Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
Upvoty
Canny.io
UserVoice
Nolt.io
Featurebase
productboard
Frill
hellonext.co
With Upvoty you are able to collect and manage valuable feedback from your users in 1 simple overview. You can also share your product roadmap to show your users what's next. Turn user feedback into actionable product optimizations! Try it for free!
Matplotlib UpvotyEasily migrated from another tool, our team and users are loving Upvoty thus far, now 5 months in.
We use upvoty for a few months now, every month they add some new cool features. They listen to their customers very carfully. They should be, otherwise their tool does not work :-D
I have been waiting a long time for a beautiful and easy to use feedback tool - Upvoty is it. Upvoty also nails all the little things.
This tool really helps our customers provide feedback and priorities to our Product, and Development teams. We were able to implement this directly into our app which creates a seamless experience for our users.
Based on our record, Matplotlib seems to be a lot more popular than Upvoty. While we know about 114 links to Matplotlib, we've tracked only 1 mention of Upvoty. 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
๐ฌ User feedback: From the very start, we listened really carefully to the feedback of our users (of course by using our own product - upvoty.com). This resulted in us building a product that was valuable and people actually wanted to pay for it. Source: over 4 years ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Canny.io - Canny helps you collect and organize feature requests to better understand customer needs and prioritize your roadmap.
NumPy - NumPy is the fundamental package for scientific computing with Python
UserVoice - UserVoice integrates easy-to-use feedback, helpdesk, and knowledge base management tools in one platform that empowers users to speak and companies to understand.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.
Nolt.io - A fast & beautiful way to collect user feedback