Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
Darkonium AI
Siemens
Hexagon
AVEVA Workflow Management
Dark Pools AI
Nucleum AI
Twin AI
Darkonium AI is a specialist technology consultancy that transforms UK manufacturing and logistics operations by tackling the root causes of inefficiency and financial distress.
Using a powerful combination of NVIDIA Omniverse digital twins and our proprietary AI optimisers, we create a virtual, physics-accurate replica of your entire operationโfrom production lines to multi-site supply chains. This allows us to safely simulate thousands of scenarios to find and validate optimal workflows, eliminating guesswork and real-world risk.
Our data-driven approach delivers drastic, measurable improvements, proven to slash energy consumption by 15-40%, cut material waste by up to 93%, and reduce costly downtime by up to 65%.
We serve two key markets: solvent manufacturers seeking a competitive edge and insolvency practitioners aiming to maximise the value of distressed assets. Our key differentiator is a flexible commercial model, including a unique self-funding, success-fee option that eliminates upfront capital risk for our clients. This is particularly effective in insolvency scenarios, where we turn operational failure into a self-funding recovery.
We partner with clients through a phased, de-risked process, starting with a rapid "Digital Readiness Report" to identify and prioritise the highest-value opportunities. Backed by credentials from UKRI and Made Smarter, we make UK businesses more resilient, profitable, and competitive.
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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.
Siemens - Discover Siemens as a strong partner, technological pioneer and responsible employer.
NumPy - NumPy is the fundamental package for scientific computing with Python
Hexagon - Hexagon - Box Version
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.
AVEVA Workflow Management - AVEVA (formerly Skelta from Wonderware) is a full-fledged Workflow Management software that increases the efficiency at which tasks are executed at the workplace.