What are the key steps involved in exploratory data analysis?

Exploratory Data Analysis is an important step in data science. It allows analysts to better understand patterns, relationships and anomalies that exist within a dataset, before they apply complex models. EDA allows analysts to make informed decisions regarding data preprocessing and feature selection. This process includes several steps that each contribute to a thorough understanding of the data. https://www.sevenmentor.com/data-science-course-in-pune.php

Data collection and analysis is the first step of EDA. The first step in EDA is to collect and understand data from reliable sources. Analysts need to determine whether the data are categorical or numeric, and look for any missing values, errors, or duplicate records. To ensure meaningful analysis, it is important to understand the context of data, such as its origin and intended usage.