In case you have additional questions, kindly let me know in the comments below. You have so many advanced options in the program that will delete Cache, Cookies, Junk, Tracing Files, Temporary Files, System History, Logs, and the list keep goes on. In summary: In this tutorial you have learned how to prepare and clean bad data frames for survey data and other types of data sets in R. R-Wipe & Clean is a Mac OS X program that enables the users to remove junk files in the machine. They provide additional functions and commands for the application of data cleaning techniques and are very useful when it comes to the preparation and handling of data frames. You may also use the search icon on the top-right side of the Statistics Globe menu bar as a cheat sheet, in case you are looking for specific and more detailed advice on a certain topic step-by-step.įurthermore, I recommend having a look at packages such as dplyr, tidyverse, and stringr. Replace Specific Characters in String in R.Reshape Data Frame from Long to Wide Format.Only Import Selected Columns of Data in R.Insert Character Pattern at Particular Position of String.In addition, you might want to read the related posts to this topic on Statistics Globe. I have recently released a video on my YouTube channel, which demonstrates the R programming code and the instruction text of this tutorial in some more detail. Note that this tutorial has only shown a brief introduction to different data cleaning techniques. Let’s first have a closer look at the names of our data frame columns:ĭata$col3 <- "a" # Merge categoriesĭata$col3 <- "a" # Merge categoriesĪs shown in Table 11, we have created another version of our data frame where the categories “b” and “c” have been replaced by the category “a”. In the following examples, I’ll show some tricks on how to edit and improve the structure of this data set.Įxample 1 explains how to clean the column names of a data frame. It visualizes that our exemplifying data is constituted of ten rows and five variables.Īs you might already have noticed, some parts of this data set are not formatted properly.
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