How to obtain a new table after filtering only one column in an existing table in R?

Question

I have a data frame having 20 columns. I need to filter / remove noise from one column. After filtering using convolve function I get a new vector of values. Many values in the original column become NA due to filtering process. The problem is that I need the whole table (for later analysis) with only those rows where the filtered column has values but I can't bind the filtered column to original table as the number of rows for both are different. Let me illustrate using the 'age' column in 'Orange' data set in R:

> head(Orange)
  Tree  age circumference
1    1  118            30
2    1  484            58
3    1  664            87
4    1 1004           115
5    1 1231           120
6    1 1372           142

Convolve filter used

smooth <- function (x, D, delta){
z <- exp(-abs(-D:D/delta))
r <- convolve (x, z, type='filter')/convolve(rep(1, length(x)),z,type='filter')
r <- head(tail(r, -D), -D)
r
}

Filtering the 'age' column

age2 <- smooth(Orange$age, 5,10)
data.frame(age2)

The number of rows for age column and age2 column are 35 and 15 respectively. The original dataset has 2 more columns and I like to work with them also. Now, I only need 15 rows of each column corresponding to the 15 rows of age2 column. The filter here removed first and last ten values from age column. How can I apply the filter in a way that I get truncated dataset with all columns and filtered rows?

Answer 1

You would need to figure out how the variables line up. If you can add NA's to age2 and then do Orange$age2 <- age2 followed by na.omit(Orange) you should have what you want. Or, equivalently, perhaps this is what you are looking for?

df <- tail(head(Orange, -10), -10)    # chop off the first and last 10 observations
df$age2 <- age2
df

   Tree  age circumference      age2
11    2 1004           156  915.1678
12    2 1231           172  876.1048
13    2 1372           203  841.3156
14    2 1582           203  911.0914
15    3  118            30  948.2045
16    3  484            51 1008.0198
17    3  664            75  955.0961
18    3 1004           108  915.1678
19    3 1231           115  876.1048
20    3 1372           139  841.3156
21    3 1582           140  911.0914
22    4  118            32  948.2045
23    4  484            62 1008.0198
24    4  664           112  955.0961
25    4 1004           167  915.1678

Edit: If you know the first and last x observations will be removed then the following works:

x <- 2
df <- tail(head(Orange, -x), -x)     # chop off the first and last x observations 
df$age2 <- age2