The next visualization library we'll look at is called seaborn, (http://seaborn.pydata.org/index.html). It is a library that was created specifically for statistical visualizations. In fact, it is perfect for use with pandas DataFrames, where the columns are features and the rows are observations. This style of DataFrame is called tidy data, and is the most common form for machine learning applications.
Let's now take a look at the power of seaborn:
import seaborn as sns sns.pairplot(df, hue='species')
With just those two lines of code, we get the following:
Having just detailed the intricate nuances of