1_cleaning_data.r

# IMPORT BY USING THE SUITABLE ENCODING
fifa = read.csv("0_raw_downloaded_data.csv")

# DELETING THE UNECCESSARY ROWS
fifa <- fifa[, -c(2,5,7,11,14,16,17,18,19,21,24,25,26,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54)]

#CHECK FOR THE CLASS
sapply(colnames(fifa), function(x) class(fifa[[x]]))

#REPLACING CATEGORICAL MISSING VALUE
for (j in which(fifa$Name == '')) {
  fifa$Name[j] <-fifa$Name[j-1]
}
for (j in which(fifa$Nationality == '')) {
  fifa$Nationality[j] <-fifa$Nationality[j-1]
}
for (j in which(fifa$Club == '')) {
  fifa$Club[j] <-fifa$Club[j-1]
}
for (j in which(fifa$Preferred.Foot == '')) {
  fifa$Preferred.Foot[j] <-fifa$Preferred.Foot[j-1]
}
for (j in which(fifa$Body.Type == '')) {
  fifa$Body.Type[j] <-fifa$Body.Type[j-1]
}
for (j in which(fifa$Position == '')) {
  fifa$Position[j] <-fifa$Position[j-1]
}

#REPLACING NUMERICAL MISSING VALUES
for(i in c(8,9, 14:50))
{
  m <- mean(fifa[,i], na.rm = TRUE)
  fifa[is.na(fifa[,i]), i] <-m
  fifa[[i]] = lapply(fifa[[i]], function(x){replace(x,x==0,m)})
  fifa[[i]] = unlist(lapply(fifa[[i]], as.numeric))
}
for(i in c(3,5,6,13))
{
  m=as.integer(mean(fifa[,i], na.rm = TRUE))
  fifa[is.na(fifa[,i]), i] <-m
  fifa[[i]] = lapply(fifa[[i]], function(x){replace(x,x==0,m)})
  fifa[[i]] = unlist(lapply(fifa[[i]], as.numeric))
}
#CHECK IF THERE IS ANY MISSING VALUES
print(any(is.na(fifa)))

#VIEW THE CLEANED DATA
View(fifa)

#WRITE THE CLEANED DATA INTO A NEW FILE
write.csv(fifa, "1_cleaned_data.csv", row.names = FALSE)