r - insert row for missing monthly data and interpolate

Question

I have a data frame as below with 5000+ rows. I am trying to insert a row where the month is missing e.g. month 6 below - and then utilise linear interpolation to calculate

Answer 1

I would simply first transform your dates into actual Dates (here taking the first of every month:

dates <- as.Date(paste(ts.data$Year, ts.data$Month, 1, sep="-"))

Do the same for the target, missing months (here just one but can work with many):

target <- as.Date("2003-06-01")

And do the approximation:

approx(dates, ts.data$TWS, target)
$x
[1] "2003-06-01"

$y
[1] 5.069365

So in the context of your dataframe (here simplified):

ts.data <- data.frame(Year=c(rep(2003,11),rep(2004,9)),Month=c((1:12)[-6],1:9),TWS=c(14.2566781,5.0413706,3.8192721,5.8706026,7.8461188, 2.3821844, 0.1995629,-1.8353604,-2.0410653,-1.4029813,-0.2206872,-0.5090872,-0.4887118,-0.7725966, 4.1831581, 2.5651040,-2.2511409,-1.6484375,-4.6508982, -5.0053745))
dates <- as.Date(paste(ts.data$Year, ts.data$Month, 1, sep="-"))
target <- as.Date("2003-06-01")
ts.data <- rbind(ts.data, 
                 data.frame(Year=2003, 
                            Month=6, 
                            TWS=approx(dates, ts.data$TWS, target)$y)
ts.data <- ts.data[order(ts.data$Year, ts.data$Month),]

Answer 2

Using data.table and zoo packages you can easily expand your data set and interpolate as long as you don't have NAs at both sizes of the year

Expend the data set

library(data.table)
library(zoo)
res <- setDT(df)[, .SD[match(1:12, Month)], by = Year]

Interpolate on whatever column you want

cols <- c("Month", "DecimDate", "TWS")
res[, (cols) := lapply(.SD, na.approx, na.rm = FALSE), .SDcols = cols]

res
#     Year GridNo GridIndex  Lon  Lat DecimDate Month        TWS
#  1: 2003   GR72        72 35.5 -4.5  2003.000     1 14.2566781
#  2: 2003   GR72        72 35.5 -4.5  2003.083     2  5.0413706
#  3: 2003   GR72        72 35.5 -4.5  2003.167     3  3.8192721
#  4: 2003   GR72        72 35.5 -4.5  2003.250     4  5.8706026
#  5: 2003   GR72        72 35.5 -4.5  2003.333     5  7.8461188
#  6: 2003     NA        NA   NA   NA  2003.417     6  5.1141516
#  7: 2003   GR72        72 35.5 -4.5  2003.500     7  2.3821844
#  8: 2003   GR72        72 35.5 -4.5  2003.583     8  0.1995629
#  9: 2003   GR72        72 35.5 -4.5  2003.667     9 -1.8353604
# 10: 2003   GR72        72 35.5 -4.5  2003.750    10 -2.0410653
# 11: 2003   GR72        72 35.5 -4.5  2003.833    11 -1.4029813
# 12: 2003   GR72        72 35.5 -4.5  2003.917    12 -0.2206872
# 13: 2004   GR72        72 35.5 -4.5  2004.000     1 -0.5090872
# 14: 2004   GR72        72 35.5 -4.5  2004.083     2 -0.4887118
# 15: 2004   GR72        72 35.5 -4.5  2004.167     3 -0.7725966
# 16: 2004   GR72        72 35.5 -4.5  2004.250     4  4.1831581
# 17: 2004   GR72        72 35.5 -4.5  2004.333     5  2.5651040
# 18: 2004   GR72        72 35.5 -4.5  2004.417     6 -2.2511409
# 19: 2004   GR72        72 35.5 -4.5  2004.500     7 -1.6484375
# 20: 2004   GR72        72 35.5 -4.5  2004.583     8 -4.6508982
# 21: 2004   GR72        72 35.5 -4.5  2004.667     9 -5.0053745
# 22: 2004     NA        NA   NA   NA        NA    NA         NA
# 23: 2004     NA        NA   NA   NA        NA    NA         NA
# 24: 2004     NA        NA   NA   NA        NA    NA         NA