R programming for beginners | Handling missing values #rprogramming

R programming for data analysis. Section 3. Basic data management. Lecture 5.Handling missing values in data frame In R, missing values are represented by the symbol NA. recoding determined values to missing. grade$Math[grade$Math == 999] = NA grade$Physics[grade$Physics == 999] = NA grade$Chemistry[grade$Chemistry == 999] = NA grade$Date[grade$Date == "999"] = NA identifying observations in data frame that contain missing values is.na(grade[,7:10]) Once you’ve identified missing values, you need to eliminate them in some way before analyzing your data further. The reason is that arithmetic expressions and functions that contain missing values yield missing values Excluding missing values from analyses using na.rm=TRUE option sum(grade$Physics, na.rm=TRUE) remove any observation with missing data by using the na.omit() test = na.omit(grade) Main sections in this playlist - R programming for beginners Section 1 Get started with R environment Section 2 R data structure, create datasets Section 3 Basic data management Section 4 Advanced data management Section 5 Using R graphic ggplot2 Section 6 dplyr() #rprogramming #rstudio #dataframe #missingvalue #variable #rdatacode