How to clean and manipulate data in R?

Cleaning and manipulating data in R is a crucial step in the data analysis process. To clean data, you can use functions like `na.omit()` to remove missing values and `complete.cases()` to identify complete cases in your dataset. Manipulating data involves reshaping, merging, and aggregating data to extract valuable insights. Functions such as `dplyr` and `tidyr` packages in R provide useful tools for data manipulation tasks like filtering, arranging, and summarizing data. By mastering these techniques, you can ensure that your data is accurate, complete, and ready for analysis.
This mind map was published on 15 May 2024 and has been viewed 9 times.

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