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Data Reshaping and Cleaning
Data reshaping and cleaning are crucial steps in any data analysis process. By mastering these techniques, users can ensure that their datasets are well-structured and ready for analysis, enhancing the overall quality of insights derived from the data.
pivot_longer & pivot_wider Functions of tidyr Package in R | Reshape Data from Wide to Long Format
data ＜- data.frame(ID1 = LETTERS[1:4], # Create example data ID2 = rep(letters[1:3], each = 4), x = 1:12, y = 21:32) ...