Chapter 3 - Data Exploration

Abstract

Data exploration, also known as exploratory data analysis, provides a set of simple tools to achieve a basic understanding of a dataset. The results of data exploration can be extremely useful in grasping the structure of the data, the distribution of the values, presence of extreme values, and interrelationships within the dataset. Descriptive statistics is the process of condensing key characteristics of the dataset into simple numeric metrics. Some of the common metrics used are mean, standard deviation, and correlation. Visualization is the process of projecting the data, or parts of it, into Cartesian space or into abstract images. In the data science process, data exploration is leveraged in many different steps including preprocessing, modeling, and interpretation of the results.