9 Hidden Plotly Tricks Every Data Scientist Needs to Know

Author(s): Mukundan Sankar

Originally published on Towards AI.

Why Your Current Visualizations Aren’t Telling the Full Story

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When it comes to data visualization, Plotly is one of my go-to tools. It’s intuitive, interactive, and offers endless possibilities. But there are several hidden techniques in Plotly that many people don’t fully explore — these can take your visualizations from good to extraordinary. I will cover 9 “hidden” or advanced techniques or “hidden” techniques that people don’t talk about enough in Plotly. For accessibility, I will use the famous UCI Machine Learning Repository datasets. I will definitely explain to you why these are “hidden”, the value of using these charts, and the insights. Along the way, I’ll explain why these tricks are “hidden,” what value they bring, and how they unlock insights that simpler visuals just can’t deliver.

Why It’s Hidden:

Why did I include the correlation matrix as the first one? Every data analyst or scientist uses correlation to visualize the relationships in the data. Most data professionals visualize correlations using default heatmaps but skip the step of tailoring them to highlight meaningful relationships. Adding annotations and custom color scales brings a layer of clarity often overlooked.

What it Does:

I computed the correlation matrix using the… Read the full blog for free on Medium.

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Published via Towards AI