database - Interpolate to obtaining certain value in R

Question

I'm working with a data frame of 1501 x 35 values, and the data is like in the following table:

Date	1	3	4	5	6
10/02/20	0.04919382	0.04962555	0.04579872	0.0354689	0.048592
20/05/20	0.04909930	0.04957330	0.0458772	0.04741	0.052167
12/08/20	0.04909930	0.04957330	0.04525272	0.035544	0.045489
18/10/20	0.04915135	0.04957330	0.047822	0.03485484	0.024452

question from:https://stackoverflow.com/questions/65840281/interpolate-to-obtaining-certain-value-in-r

Answer 1

I believe what you want is this. At the moment there's nothing to interpolate, you need a NA column first. You could append one after the second position.

(d <- as.data.frame(append(d, list(X2=NA), 2)))
#         Date         X1 X2         X3         X4         X5       X6
# 1 2020-02-10 0.04919382 NA 0.04962555 0.04579872 0.03546890 0.048592
# 2 2020-05-20 0.04909930 NA 0.04957330 0.04587720 0.04741000 0.052167
# 3 2020-08-12 0.04909930 NA 0.04957330 0.04525272 0.03554400 0.045489
# 4 2020-10-18 0.04915135 NA 0.04957330 0.04782200 0.03485484 0.024452

Now you want to apply the approx function row-wise, i.e. with MARGIN=1. The logic is, that you feed it with a sequence of length of the values to interpolate, i.e. of the x of each apply iteration which is seq(x) as well as the values containing the NAs which is x itself. From the output you want the y, and, because it is the whole (transposed) matrix, just row [2,].

d$X2 <- apply(d[-1], MARGIN=1, function(x) approx(seq(x), x, seq(x))$y)[2,]
d
#         Date         X1         X2         X3         X4         X5       X6
# 1 2020-02-10 0.04919382 0.04940968 0.04962555 0.04579872 0.03546890 0.048592
# 2 2020-05-20 0.04909930 0.04933630 0.04957330 0.04587720 0.04741000 0.052167
# 3 2020-08-12 0.04909930 0.04933630 0.04957330 0.04525272 0.03554400 0.045489
# 4 2020-10-18 0.04915135 0.04936232 0.04957330 0.04782200 0.03485484 0.024452

---

Data:

d <- structure(list(Date = structure(c(18302, 18402, 18486, 18553), class = "Date"), 
    X1 = c(0.04919382, 0.0490993, 0.0490993, 0.04915135), X3 = c(0.04962555, 
    0.0495733, 0.0495733, 0.0495733), X4 = c(0.04579872, 0.0458772, 
    0.04525272, 0.047822), X5 = c(0.0354689, 0.04741, 0.035544, 
    0.03485484), X6 = c(0.048592, 0.052167, 0.045489, 0.024452
    )), row.names = c(NA, -4L), class = "data.frame")