A portrait made of data: Braunschweig
date:Prologue
The city of Braunschweig has undergone significant changes in recent years. I aim to visualize these changes and their perception in the public using various data sources. This blog post marks the beginning of a series that focuses on a data-based portrait of Braunschweig.
To accomplish this, I will initially utilize the following data sources:
For accessing the OpenData datasets, I have implemented a simple REST client based on the DKAN Portal API. At the time of this publication, it only supports read-only access, allowing the retrieval, download, and processing of datasets from Python.
GovData/Open Data is the result of Open Data legislation and the Open Data strategy, requiring authorities of the immediate federal administration to publicly provide collected data.
I intend to access historical Google Trends results through the unofficial pytrends API. The challenge here will be to systematically draw conclusions based on search terms and relate the results to the OpenData datasets.
Traceability
For better traceability of my analyses, the data can also be analyzed under google.colab itself. The prerequisite is a Google account with age verification. The use of Colab is free as long as no additional packages are purchased.
When using the notebooks, it must be considered that all APIs I use are unofficial implementations, which means changes to the interface of the data sources can lead to malfunctions.