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The Python programming language is easy to learn and makes it possible to solve problems quickly. But it also offers advanced solutions that can make creating ...

pandas is a Python library for data analysis that has become very popular in recent years. More specifically, pandas is an in-memory analytics tool that offers ...

There are many different Python libraries that make it much easier to clean and validate data. We will use these libraries in practical examples to recognise ...

Dashboards present the most important information for achieving one or more goals. They consolidate and organise the information so that it can be viewed at a ...

Design patterns are proven solution templates for recurring problems in software architecture and development. There are Python-specific design patterns such ...

The basic design principles are indispensable for both explorative and explanatory data visualisation. Visual hierarchies can be used to focus on specific ...

Python can be used to test not only Python packages and applications, but also web services, embedded systems and hardware.

Python has become very widespread and one of the reasons is probably that it runs on many different platforms, from IoT devices to common operating systems and ...

Jupyter notebooks are ideal for exploratory data analysis. They have therefore become the de facto standard for exploratory data analysis and rapid ...

The Python for Data Science stack should be continuously adapted to current conditions and benefit from better data science workflows. In this workshop, we ...