What Is Exploratory Data Analysis?

Exploratory Data Analysis (EDA) is the process of examining and analyzing a dataset to discover patterns, relationships, and trends.

It is an iterative process where the analyst visualizes the data and generates hypotheses about relationships in the data.

EDA involves statistical and graphical techniques to gain insight into the data. The goal of EDA is to identify interesting patterns and relationships in the data that may not be apparent at first glance.

EDA is an important step in the data analysis process, as it helps to identify potential outliers, missing data, and other issues that may impact the accuracy of the analysis.

EDA can help identify trends and relationships in the data, such as correlations between variables or changes over time. EDA can also be used to identify potential problems with the data, such as missing values or outliers.

EDA is an exploratory process, which means that the analyst may need to iterate through multiple analyses to fully understand the data.

EDA can be performed using a variety of tools and techniques, including statistical software packages and data visualization tools.