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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()



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