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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.
Reshape Data Frame from Wide to Long Format in R (2 Examples) | melt & gather Functions in RStudio
##### Example data data_wide ＜- data.frame(ID1 = c("A", "A", "B", "C", "B"), # Create example data ID2 = c("b", "c", "c", "a", "d"), ...