I have a dataframe in R with observations that I would like to convert to one vector. All the rows have the same columns (with some NAs present in certain columns). I know that I can extract them all individually, but I am wondering what the most succinct way to extract all of the values (in order) is, to then convert them to one vector. I would like to read out all the values of row 1 (column-1, column-2... column-n), followed by row 2, followed by row 3...etc.
Example with sample data:
Row 1: 1, 2, 3, 4, 5, NA, 1
Row 2: 2, 3, 4, 5, 6, 8, NA
Row 3: 7, 9, 2, 3, 5, 12, 14
Desired Vector: 1, 2, 3, 4, 5, NA, 1, 2, 3, 4, 5, 6, 8, NA, 7, 9, 2, 3, 5, 12, 14
To then remove NAs and receive:
1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 6, 8, 7, 9, 2, 3, 5, 12, 14
Given that I have numerous rows and columns, what is the most succinct way to do this, rather than individually extracting each row/column's values?
You can also do this:
df |>
#turn the rows into columns
t() |>
#combine the colums into one vector
Reduce(f = c) |>
#drop na
Filter(f = Negate(is.na))
# [1] 1 2 3 4 5 1 2 3 4 5 6 8 7 9 2 3 5 12 14
The df is from Mohamed Desouky.
You can also use apply with the MARGIN=2 argument and drop the NA first. Then combine the list into a sigle vector:
df |> apply(2, na.omit) |> Reduce(f = c)
# x y z x y z x y z x y z x y z y z x z
# 1 2 7 2 3 9 3 4 2 4 5 3 5 6 5 8 12 1 14