Matplotlib Performance

When generating images for ever larger growing data sets, the performance in creating and writing them to the disk is no longer negligible. Imagine a data set with 10,000 astronomical sources, each observed in 10 bands. Just writing out an image for each band would result in 100,000 images – leaving apart any analysis plots. …
Continue reading Matplotlib Performance

Customizing Jupyter Notebooks for Presentations and Reports

Jupyter Notebooks are ideal for data analysis when using Python. They allow you to analyze the data, while at the same time writing documentation. The data processing and report writing become intertwined: while you explore and analyze the data, you already have a draft of your report at hand. Unfortunately, Jupyter Notebooks are not too …
Continue reading Customizing Jupyter Notebooks for Presentations and Reports