Relational visualization reveals how variables interact and affect each other using scatter plots, essential for understanding variable dependencies in datasets.
Distribution visualization highlights the statistical distribution of data, providing insights into the frequency of data points across ranges with histograms.
Comparison visualization employs box charts to compare continuous features with categorical ones, helping identify outliers that may influence the accuracy of analyses.
Compositional visualization is important for understanding how different parts make up a whole, although less detailed in the initial article's explanation.
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