Exploratory data analysis
Exploratory Data Analysis (EDA) is a crucial step when you start exploring your data. It can give you an overall overview of its main characteristics, such as minimum and maximum values, as well as mean and median values. Also, it can help you to detect patterns, data inconsistencies, and outliers.
One of the first steps when exploring your data is to apply EDA techniques so you can get a better understanding of the data you want to process. The main goals of applying this technique are as follows:
- To maximize insight into a dataset
- To uncover the underlying structure
- To extract important variables
- To detect outliers and anomalies
There are four ways in which we can categorize EDA:
- Single variable, non-graphical: Here, the data analysis is applied to just one variable. The main purpose of univariate analysis is to describe the data and find patterns that exist within it.
- Single variable, graphical: Graphical methods...
