Pandas VS Upvoty
Compare Pandas VS Upvoty and see what are their differences
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives.
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Pandas
NumPy
OpenCV
Scikit-learn
Dataiku
Exploratory
htm.java
WEKA
Upvoty
Canny
Nolt
UserVoice
productboard
hellonext.co
Feedback Fish
FeedBear
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!
Pandas 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, Pandas seems to be a lot more popular than Upvoty. While we know about 201 links to Pandas, 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.
How to Accomplish: Use statistical analysis tools and libraries (e.g., Pandas for tabular data) to calculate and visualize these characteristics. For image datasets, custom scripts to analyze object sizes or mask distributions can be useful. Tools like OpenCV can assist in analyzing image properties, while libraries like Pandas and NumPy are excellent for tabular and numerical analysis. To address class... - Source: dev.to / 20 days ago
Pandas - A powerful data analysis and manipulation library for Python. Pandas Documentation - Official documentation. - Source: dev.to / 25 days ago
It's also possible for you to give a package an alias by using the as keyword. For instance, you could use the pandas package as pd like this:. - Source: dev.to / about 2 months ago
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / 2 months ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 2 months ago
💬 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 2 years ago
NumPy - NumPy is the fundamental package for scientific computing with Python
Canny - Canny helps you collect and organize feature requests to better understand customer needs and prioritize your roadmap.
OpenCV - OpenCV is the world's biggest computer vision library
Nolt - A fast & beautiful way to collect user feedback
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
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.