converting dataframe columns from matrix to vector

Question

I'm trying to combine a few dataframes. In the process of doing so, I noticed that one dataframe contains matrices rather than vectors. Here's a basic example:

df3 <- structure(list(v5 = structure(c(NA, 0), .Dim = c(2L, 1L), .Dimnames = list( c("206", "207"), "ecbi1")), v6 = structure(c(NA, 0), .Dim = c(2L, 1L), .Dimnames = list(c("206", "207"), "ecbi2"))), .Names = c("v5", "v6"), row.names = 206:207, class = "data.frame") # get class class(df3[,1]) # [1] "matrix"

I want the columns in df3 to be vectors, not matrices.

bramtayl · Accepted Answer · 2015-12-07 16:34:54Z

3

Just apply as.vector

df3[] = lapply(df3, as.vector)

answered Dec 7, 2015 at 16:34

bramtayl

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David Arenburg Over a year ago

See? You don't always have to library(dplyr/tidyr) and then spread %>% gather %>% mutate %>% another_irrelevant_function...

MichaelChirico · Accepted Answer · 2015-12-07 16:42:06Z

I think most important is to figure out how you managed to get matrix-type columns in the first place and understand whether this was a desired behavior or a side effect of a mistake somewhere earlier.

Given where you are, you can just use c to undo a given column:

df3$v5 <- c(df3$v5)

Or if this is a problem with all columns:

df3[ ] <- lapply(df3, c)

(lapply returns a list of vectors, and when we pass a list via assignment to a data.frame, it interprets each list element as a column; df3[ ] returns all columns of df3. We could also do df3 <- lapply(df3, c), but using [ ] is more robust -- if we make a mistake and somehow return the wrong number of columns, an error will be thrown, where as simply using df3 would have simply overwritten our data.frame silently in case of such an error)

Lastly, if only some columns are matrix-type, we can replace only those columns like so:

mat.cols <- sapply(df3, is.matrix) df3[ , mat.cols] <- lapply(df3[ , mat.cols], c)

As pertains to the relation between this approach and that using as.vector, from ?c:

c is sometimes used for its side effect of removing attributes except names, for example to turn an array into a vector. as.vector is a more intuitive way to do this, but also drops names.

So given that the names don't mean much in this context, c is simply a more concise approach, but the end result is practically identical.

Rich Scriven · Accepted Answer · 2015-12-07 18:42:23Z

1

Use this.

df3[,1] = as.vector(df3[,1])

The same procedure can be applied generally to the rest of the columns.

edited Dec 7, 2015 at 18:42

Rich Scriven

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answered Dec 7, 2015 at 16:40

AlxRd

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1 Comment

MichaelChirico Over a year ago

@bramtayl's solution is exactly a better version of this.

akrun · Accepted Answer · 2015-12-07 18:11:20Z

0

We can use do.call

do.call(data.frame, df3)

answered Dec 7, 2015 at 18:11

akrun

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