Visualizing data

There are a number of reasons for why we visually represent the data. At the data exploration stage, we can gain an immediate understanding of data properties. Visual representation serves to highlight patterns in data and suggest modeling strategies. Exploratory graphs are usually made quickly and in large numbers. We are not so much concerned with aesthetic or stylistic issues, but we simply want to see what the data looks like.

Beyond using graphs to explore data, they are a primary means of communicating information about our data. Visual representation helps clarify data properties and stimulate viewer engagement. The human visual system is the highest bandwidth channel to the brain, and visualization is the most efficient ...

Get Python: Deeper Insights into Machine Learning now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.