How to do it...

Once the files are ready, load the Hmisc package and read the files as follows:

  1. Load the CSV data from the files:
> housing.dat <- read.csv("housing-with-missing-value.csv",header = TRUE, stringsAsFactors = FALSE)
  1. Check summary of the dataset:
> summary(housing.dat)            

The output would be as follows:

  1. Delete the missing observations from the dataset, removing all NAs with list-wise deletion:
> housing.dat.1 <- na.omit(housing.dat)

Remove NAs from certain columns:

> drop_na <- c("rad")> housing.dat.2 <-housing.dat [complete.cases(housing.dat [ , !(names(housing.dat)) %in% drop_na]),]
  1. Finally, verify the dataset with summary ...

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