Pandas for Everyone: Python Data Analysis, 2nd Edition

3

Plotting Basics

Data visualization is as much a part of the data processing step as the data presentation step. It is much easier to compare plotted values than to compare numerical values. By visualizing data we can get a better intuitive sense of the data than would be possible by looking at tables of values alone. Additionally, visualizations can bring to light hidden patterns in data, that you, the analyst, can use for model selection.

Learning Objectives

The concept map for this chapter can be found in Figure A.3.

• Explain why visualizing data is important

• Create various statistical plots for exploratory data analysis

• Use plotting functions from the matplotlib, seaborn, and pandas libraries

• Identify when to use univariate, bivariate, ...