When you come across my blog, you may be thinking “What is this guy doing”? There are some weird analyses that have somehow to do with software development. But why all this?
Here are some queries that I use regulary at meetups and conferences for showing some features of jQAssistant and Neo4j.
Here is a short video that demonstrates how you can get some insights from the history of a Git repository using Jupyter Notebook, Python, pandas and matplotlib: We take a look at exporting the necessary data reading in the dataset
In this blog post, I want to show you a nice complexity metric that works for most major programming languages that we use for our software systems – the indentation-based complexity metric.
This notebook is a simple mini-tutorial to introduce you to basic functions of Jupyter, Python, Pandas and matplotlib with the aim of analyzing software data. Therefore, the example is chosen in such a way that we come across the typical methods in a data analysis.