04pallav
9/13/2017 - 9:27 PM

Drop rows with missing values

Drop rows with missing values

####calculating percenatge of missing values
pMiss <- function(x){sum(is.na(x))/length(x)*100}
apply(data,2,pMiss) # by column 
apply(data,1,pMiss) # by row 

mean(is.na(x))*100   #for whole dataframe

drops <- c("f147","f119","f122")
cleanDF=merged[ , !(names(merged) %in% drops)]

cleanDF=cleanDF[-which(rowMeans(is.na(cleanDF)) > 0.25),]


library(tidyr)
merged %>% drop_na()