
Appian
Camunda
Kintone
Bizagi
Scoop Solar
Ultimate Forms
K2
Intellect
Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
Appian
MatplotlibBased on our record, Matplotlib seems to be a lot more popular than Appian. While we know about 114 links to Matplotlib, we've tracked only 7 mentions of Appian. 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.
AI coding adoption at enterprise scale is hard because the real project is not installing a tool. It is redesigning trust, review, ownership, and delivery discipline around a new source of code generation. That's where platforms like Retool, ToolJet, Appian, etc. shine. - Source: dev.to / 4 months ago
You are process-heavy and regulated, and your app is basically a workflow engine: Appian. - Source: dev.to / 5 months ago
Does any of you use a low-code tool like Retool or Appian? If so, what is the most common use case? Source: over 3 years ago
Look for use case inspiration in the Solutions area of appian.com and within the AppMarket. See if you can build proof of concepts of some of these. Source: over 3 years ago
There are low code database driven website creation systems out there at the moment e.g. OutSystems and Appian however they have very limited free trials (e.g. auto-disable after a few days of no use), and then the paid options are again too expensive. Although I will note that they seem to be great in terms of their usability and would be perfect for creating a simple interface without too much diving into code. Source: about 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
Camunda - The Universal Process Orchestrator
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Kintone - Build business apps and supercharge your company's productivity with kintone's all-in-one...
NumPy - NumPy is the fundamental package for scientific computing with Python
Bizagi - Bizagi is a Business Process Management (BPMS) solution for faster and flexible process automation. It's powerful yet intuitive BPM Suite is designed to make your business more agile.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.