This is the story of how we made sure that tracking local school holidays in Python becomes possible for data scientists, using workalendar (code example below). But let’s start at the beginning: When we write models that interpret and forecast meter data, we often encounter demand patterns that change drastically during holiday periods. When this…
We believe open source software is a corner-stone of modern IT, and we’re proud that this month, we were able to contribute. Here, we describe how much work is behind such a simple bugfix. We use many libraries every day, one of them being Pandas, the popular data analysis / manipulation library for Python. With…
This news probably isn’t exciting to you, but we believe it should be: A microgrids industry is about to emerge, and it’s not just hospitals and military facilities. Big players like Schneider Electric are preparing to roll out a microgrid service offering applicable to buildings with an electrical load under 5 MW – this represents…
We’re improving drinking water distribution with data, together with MeterInsight and Brabant Water N.V. ! We’ll be using smart algorithms on sensor data in real time to detect consumption anomalies and provide informative historical reports.
Probabilistic forecasts give you insights into possible futures. In this post, I suggest that the best plot type to show them all at a glance is a ridgeline plot. Areas of doubt and uncertainty In data-driven operations, decisions are based on numeric expectations about what the future holds. Usually, these expectations come from point forecasts…
It’s great to be enthusiastic about technology. But to actually help our customers, we should put more emphasis on being helpful – customer value comes before enthusiasm for your subject.
