Find the Index Position of the First Non-Na Value in an R Vector

Find the index position of the first non-NA value in an R vector?

Use a combination of is.na and which to find the non-NA index locations.

NonNAindex <- which(!is.na(z))
firstNonNA <- min(NonNAindex)

# set the next 3 observations to NA
is.na(z) <- seq(firstNonNA, length.out=3)

dplyr: Need help returning column index of first non-NA value in every row

You could use apply as well:

data.frame(                           
"X1"=c(100,rep(NA,8)),
"X2"=c(NA,10,rep(NA,7)),
"X3"=c(NA,NA,1000,1000,rep(NA,5)),
"X4"=c(rep(NA,4),25,50,10,40,50),
"FirstNonNaPosition"=c(1,2,3,3,4,4,4,4,4)
) %>%
  mutate(First_Non_NA_Pos = apply(., 1, function(x) which(!is.na(x))[1]))

   X1 X2   X3 X4 FirstNonNaPosition First_Non_NA_Pos
1 100 NA   NA NA                  1                1
2  NA 10   NA NA                  2                2
3  NA NA 1000 NA                  3                3
4  NA NA 1000 NA                  3                3
5  NA NA   NA 25                  4                4
6  NA NA   NA 50                  4                4
7  NA NA   NA 10                  4                4
8  NA NA   NA 40                  4                4
9  NA NA   NA 50                  4                4

Get index from last previous non-NA value

Using base R

y=1:length(x)
y[is.na(x)]=0
y=cummax(y)
y[!is.na(x)]=NA

y
[1] NA NA  2 NA NA  5  5 NA

squeeze to one_line from Henrik

replace(cummax(seq_along(x) * !is.na(x)), !is.na(x), NA)

Finding the first non NA value after a certain value by groups

foo = function(x, v = 5) {
    ind_v = which(x == v)[1]
    x[seq_along(x) <= ind_v] = NA
    ind_non_na = which(!is.na(x))[1]
    x[seq_along(x) > ind_non_na] = NA
    x[max(ind_non_na, ind_v, na.rm = TRUE)] = max(0, ind_non_na, na.rm = TRUE)
    return(x)
}

library(dplyr)
d %>%
    group_by(Group) %>%
    mutate(Index = foo(Value))

Get index and value of non-NA list element

1) Base R Assuming that the list L contains only scalars and NA's this returns a 2 column matrix with one row for each set of xy coordinates and an attribute recording which positions were omitted.

Omit the x= and y= if you don't want the column names. If you don't want the attribute recording the positions of the NA's append [,] to the end of the line. If you know that there is only one scalar you might want to wrap it in c(...) to produce a 2 element vector. If you prefer data frame output replace cbind with data.frame.

na.omit(cbind(x = seq_along(L), y = unlist(L)))

2) tidyverse or using the tidyverse

library(tibble)
library(tidyr)

drop_na(enframe(unlist(L)))

2a) which could alternately be written using pipes like this:

L %>% unlist %>% enframe %>% drop_na

Pick out the index of the first non-NA value preceding and succeeding an index in R?

If

index = 5
values=c(0.4, NA, 0.5, NA, NA, NA, 0.3 ,NA, NA, NA, 0.5, 0.3,0.5)

then the two values you are looking for are

max(which(!is.na(values))[which(!is.na(values))<index])
[1] 3

min(which(!is.na(values))[which(!is.na(values))>index])
[1] 7

dplyr::first() to choose first non NA value

Use na.omit, compare:

first(c(NA, 11, 22))
# [1] NA

first(na.omit(c(NA, 11, 22)))
# [1] 11

Using example data:

d %>%
  mutate(
    value = case_when(
      group == 2 & year ==2000 ~ NA_integer_,
      group == 3 & year ==2002 ~ NA_integer_,
      TRUE ~ value))%>%
  group_by(group) %>% 
  mutate(
    first = dplyr::first(na.omit(value)),
    last = dplyr::last(na.omit(value)))

# # A tibble: 9 x 5
# # Groups:   group [3]
#   group  year value first  last
#   <int> <dbl> <int> <int> <int>
# 1     1  2000     3     3     4
# 2     1  2001     8     3     4
# 3     1  2002     4     3     4
# 4     2  2000    NA     9     1
# 5     2  2001     9     9     1
# 6     2  2002     1     9     1
# 7     3  2000     5     5     9
# 8     3  2001     9     5     9
# 9     3  2002    NA     5     9

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