How to find the longest sequence of non-NA rows in R? - r

Question

I have an ordered dataframe with many variables, and am looking to extract the data from all columns associated with the longest sequence of non-NA rows for one particular column. Is there an easy way to do this? I have tried the na.contiguous() function but my data is not formatted as a time series.
My intuition is to create a running counter which determines whether a row has NA or not, and then will determine the count for the number of consecutive rows without an NA. I would then put this in an if statement to keep restarting every time an NA is encountered, outputting a dataframe with the lengths of every sequence of non-NAs, which I could use to find the longest such sequence. This seems very inefficient so I'm wondering if there is a better way!

Answer 1

If I understand this phrase correctly:
[I] am looking to extract the data from all columns associated with the longest sequence of non-NA rows for one particular column
You have a column of interest, call it WANT, and are looking to isolate all columns from the single row of data with the highest consecutive non-NA values in WANT.
Example data
df <- data.frame(A = LETTERS[1:10],
B = LETTERS[1:10],
C = LETTERS[1:10],
WANT = LETTERS[1:10],
E = LETTERS[1:10])
set.seed(123)
df[sample(1:nrow(df), 2), 4] <- NA
# A B C WANT E
#1 A A A A A
#2 B B B B B
#3 C C C <NA> C
#4 D D D D D
#5 E E E E E
#6 F F F F F
#7 G G G G G
#8 H H H H H
#9 I I I I I # want to isolate this row (#9) since most non-NA in WANT
#10 J J J <NA> J
Here you would want all I values as it is the row with the longest running non-NA values in WANT.
If my interpretation of your question is correct, we can extend the excellent answer found here to your situation. This creates a data frame with a running tally of consecutive non-NA values for each column.
The benefit of using this is that it will count consecutive non-NA runs across all columns (of any type, ie character, numeric), then you can index on whatever column you want using which.max()
# from #jay.sf at https://stackoverflow.com/questions/61841400/count-consecutive-non-na-items
res <- as.data.frame(lapply(lapply(df, is.na), function(x) {
r <- rle(x)
s <- sapply(r$lengths, seq_len)
s[r$values] <- lapply(s[r$values], `*`, 0)
unlist(s)
}))
# index using which.max()
want_data <- df[which.max(res$WANT), ]
#> want_data
# A B C WANT E
#9 I I I I I
If this isn't correct, please edit your question for clarity.