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My question is I have a dataframe m as below
y1 =c( rep("A",5),rep("B",5))
y2 = rep(c(1:5),2)
y3 = y2
y3[c(2,7,9)]=NA
m = data.frame(y1,y2,y3)
y1 y2 y3
1 A 1 1
2 A 2 <NA>
3 A 3 3
4 A 4 4
5 A 5 5
6 B 1 1
7 B 2 <NA>
8 B 3 3
9 B 4 <NA>
10 B 5 5
I want to fill in the NA based on the closest non-NA value "in front of" this NA. My output should look like this:
y1 y2 y3 y4
1 A 1 1 1
2 A 2 <NA> 1
3 A 3 3 3
4 A 4 4 4
5 A 5 5 5
6 B 1 1 1
7 B 2 <NA> 1
8 B 3 3 3
9 B 4 <NA> 3
10 B 5 5 5
Any idea about how to use dplyr to achieve this goal?
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How to fill NA values with previous values in an R data frame column? How to fill NA values with previous values in an R data frame column? To fill NA values with next and previous values, we can use na.locf function of zoo package with fromLast = TRUE.
In R this is usually solved using the na.locf (Last Observation Carried Forward) function from the zoo package. See also here: Fill in NA based on the last non-NA value for each group in R. Using dplyr window-functions to make trailing values.
We can do that based on the zoo add-on package. Let’s install and load the package to RStudio: The zoo R package contains the na.locf function, which is a generic function for replacing each NA with the most recent non-NA value prior to it.
To fill NA values with next and previous values, we can use na.locf function of zoo package with fromLast = TRUE. This is the situation of a column as shown below −
This may have been answered before, but I don't know if it's been answered in a dplyr context. zoo::na.locf() is your friend:
m %>% group_by(y1) %>% mutate(y4=zoo::na.locf(y3))
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