Handling missing values

The following makes use of the zoo package. You may need to install it from CRAN using the code install.packages("zoo") if you want to run this on your computer. (The package is already installed on the notebook container, however.)

library(zoo)

Attaching package: 'zoo'

The following objects are masked from 'package:base':

    as.Date, as.Date.numeric

The file “zpresidents.RData” was created in an earlier example.

load("zpresidents.RData")

# Leads to an error:
presidents.o <- na.omit(presidents)

Error in na.omit.ts(presidents):
time series contains internal NAs

zpresidents.o <- na.omit(zpresidents)

c("Original length" = length(zpresidents),
  "Length after dropping NAs"  = length(zpresidents.o))

          Original length Length after dropping NAs 
                      120                       114 

plot(zpresidents,lty=3)
lines(na.contiguous(zpresidents),lwd=2)
/book/data-management-r/07-dates-times-timeseries/handling-missing-values/6ed0fe39df3a3951488d743ddd82dabe24be42a475d12e9d4da7059f5c934b72.png 
plot(zpresidents,lwd=2)
lines(na.approx(zpresidents),lty=2)
lines(na.spline(zpresidents),lty=3)
/book/data-management-r/07-dates-times-timeseries/handling-missing-values/9b1a7d659002547b24acbaacef854575ede75195ffcdb569e63b1653f008a9ba.png