1.4 data cleaning and manipulation in r and excel
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Data cleaning and manipulation in R Data cleaning and manipulation in Excel Dr. Mohamed Ayoub Mortagy, MD www.simpleresearch.net [email protected]
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1.4 data cleaning and manipulation in r and excel
- 2. 4- Data cleaning and manipulation in R and Excel Dr. Mohamed Ayoub Mortagy, MD www.simpleresearch.net [email protected]
- 3. Data cleaning and manipulation in excel tutorial
- 4. Data cleaning and manipulation in R tutorial
- 5. Data cleaning in R •Create new column •Rename new column •Change data variable type of a column •dplyr library • select(`col name 1`, `col name 2`, `col name 3`) • df <- df%>%mutate_if(is.character, as.factor)
- 6. Renaming factor levels ➔ library (dplyr) recode_factor(datavariable, old1 = “new1 ”, old2 = “new2 ”)
- 7. Changing order of factor levels factor(df$v1, levels = c(“level1", “level2", "level3"))
- 8. Create new column using ifelse • Ifelse( condition, what happens if condition is true, what happens if condition is false)
- 9. Another method for ifelse more than 2 levels New_col <- ifelse(oldcol < 3, “low", ifelse(oldcol>= 5.1 & oldcol<= 8, “medium", “high"))
- 10. Dealing with missing data • Library(tidyr) • drop_na() • new_variable = replace_na(old_variable, 0)) • zoo library • na.aggregate()