Ignore anyone criticizing your workflow. Tools like Spyder and Jupyter can be great when working with datasets in a way that IDEs aren't quite suited for. Vari

Ignore anyone criticizing your workflow. Tools like Spyder and Jupyter can be great when working with datasets in a way that IDEs aren't quite suited for. Variable explorers and integrated charting/plotting can be fantastic for visualizing and understanding your data. Cells in Jupyter are great for quickly iterating on data cleaning code. When I was part of a scientific applications team at a past employer (state agency), we used Jupyter heavily while developing the core code for the data processing pipelines. We were reading and processing data from instruments based on (bad) docs and notes from a former employee who reverse-engineered the format, so there was a lot of edge-case finding and testing. The notebooks fleshed out with comments and notes in Markdown upon completion and were saved within our repo as interactive documentation, demonstrating the more complicated processing steps in a far more approachable fashion.