Tips and Tricks to Organize Jupyter Notebook Visualizations

Optimize your data science workflow by automating matplotlib output — with 1 line of code. Here’s how.

Naming things is hard. After a long enough day, we’ve all ended up with the highly-descriptive likes of “graph7(1)_FINAL(2).png” and “output.pdf" Look familiar?

We can do better — and quite easily, actually.

When we use data-oriented “seaborn-esque” plotting mechanisms, the ingredients for a descriptive filename are all there. A typical call looks like this,

sns.scatterplot(data=tips, x="total_bill", y="tip", hue="time")

Right there we …

data science data visualization jupyter-notebook matplotlib python