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Cleaning and preparing data is essential for accurate analysis from "summary" of R for Data Science by Hadley Wickham,Garrett Grolemund
Data cleaning and preparation are crucial steps in the data analysis process. Without properly cleaning and preparing your data, you run the risk of obtaining inaccurate and unreliable results. When you first acquire a dataset, it is unlikely to be in the perfect form for analysis. It may contain missing values, inconsistent formatting, outliers, or errors that need to be addressed before you can trust the results of your analysis. Cleaning and preparing your data involves a series of tasks that aim to ensure the data is accurate, complete, and in a suitable format for analysis. This may include handling missin...
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