Predictive Hacks

Replace Missing Values with the mean value of the column in R

Assume that you are dealing with a Data Frame with missing values, and you want to replace them with the mean value of the corresponding column. Let’s consider the following Data Frame:

df<-data.frame(id=seq(1,10), ColumnA=c(10,9,8,7,NA,NA,20,15,12,NA), 
           ColumnB=factor(c("A","B","A","A","","B","A","B","","A")),
           ColumnC=factor(c("","BB","CC","BB","BB","CC","AA","BB","","AA")),
           ColumnD=c(NA,20,18,22,18,17,19,NA,17,23)
)

df

Clearly, we want to consider only the numeric variables. Let’s see how we can do it in one-line code.

df[sapply(df, is.numeric)] <- lapply(df[sapply(df, is.numeric)], function(x) ifelse(is.na(x), mean(x, na.rm = TRUE), x))
df

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