R ts with missing values

Question

I have a data frame I read from a csv file that has daily observations:

Date        Value 
2010-01-04  23.4
2010-01-05  12.7
2010-01-04  20.1
2010-01-07  18         


        

Answer 1

One option is to expand your date index to include the missing observations, and use na.approx from zoo to fill in the missing values via interpolation.

allDates <- seq.Date(
  min(values$Date),
  max(values$Date),
  "day")
##
allValues <- merge(
  x=data.frame(Date=allDates),
  y=values,
  all.x=TRUE)
R> head(allValues,7)
        Date      Value
1 2010-01-05 -0.6041787
2 2010-01-06  0.2274668
3 2010-01-07 -1.2751761
4 2010-01-08 -0.8696818
5 2010-01-09         NA
6 2010-01-10         NA
7 2010-01-11 -0.3486378
##
zooValues <- zoo(allValues$Value,allValues$Date)
R> head(zooValues,7)
2010-01-05 2010-01-06 2010-01-07 2010-01-08 2010-01-09 2010-01-10 2010-01-11 
-0.6041787  0.2274668 -1.2751761 -0.8696818         NA         NA -0.3486378 
##
approxValues <- na.approx(zooValues)
R> head(approxValues,7)
2010-01-05 2010-01-06 2010-01-07 2010-01-08 2010-01-09 2010-01-10 2010-01-11 
-0.6041787  0.2274668 -1.2751761 -0.8696818 -0.6960005 -0.5223192 -0.3486378

Even with missing values, zooValues is still a legitimate zoo object, e.g. plot(zooValues) will work (with discontinuities at missing values), but if you plan on fitting some sort of model to the data, you will most likely be better off using na.approx to replace the missing values.

Data:

library(zoo)
library(lubridate)
##
t0 <- "2010-01-04"
Dates <- as.Date(ymd(t0))+1:120
weekDays <- Dates[!(weekdays(Dates) %in% c("Saturday","Sunday"))]
##
set.seed(123)
values <- data.frame(Date=weekDays,Value=rnorm(length(weekDays)))