Explore Data Using R

It is always a good idea to check the features of the data we want to analyze before starting our analysis. It helps to have a general idea about the data, and in light of our findings, we can create a strategy by outlining what we can and can’t do.

Most of the time, blindly beginning to work on data leads to failures and a waste of time because data frames often include null values, misspelled data, incorrect formatting, unmatched data types, and so on.

In such cases, data needs to go through some transformation before analysis. For example, we can’t run numeric calculations on numbers in string format. Such problems sometimes cost more than just time and effort; even our mental resilience may take damage. For these reasons, it’s best to always take time to learn about the data we want to work with.