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.
Dieses Notebook ist ein einfach gehaltenes Mini-Tutorial zur Vorstellung grundlegender Funktionen von Jupyter, Python, Pandas und matplotlib, um ein Gefühl für die Analyse von Softwaredaten mit diesen Bibliotheken zu bekommen. Daher ist das gewählte Beispiel so gewählt, dass wir typische Aufgaben während einer Datenanalyse bearbeiten…
Thanks for the active participation and great feedback! Here you can find the slides of my talk “Software Analytics for Practitioners” at JAX 2018 (mostly in German) as well as a place for further discussions and feedback…