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So I have a list, say:
L1 <- list(1:10, 5:14, 10:19)
Now I am trying to get the output of the list as dataframe such that my output looks:
1. 1 2 3 4 5 6 7 8 9 10
2. 5 6 7 8 9 10 11 12 13 14
3. 10 11 12 13 14 15 16 17 18 19
I am using
as.data.frame(L1, row.names = TRUE)
and
list_vect2df(L1)
But none of them are giving the required output
839
data. frame() can be used to convert a list to R DataFrame or create a data frame from a list. If you want the elements in the list column-wise, then use cbind otherwise you can use rbind. Also learned to use different third-party packages to create DataFrame from a list.
frame() function in R Programming Language is used to convert an object to data frame. These objects can be Vectors, Lists, Matrices, and Factors. Parameters: object: Vector, Matrix, factor, or data frame.
To convert R List to Numeric value, use the combination of the unlist() function and as. numeric() function. The unlist() function in R produces a vector that contains all the atomic components.
In this article, we will discuss how to convert a large list to a dataframe in the R Programming Language. First, create a large list. Then use the Map function on the list and convert it to dataframe using the as.data.frame function in R.
However, because there are things, you can do with a dataframe that you cannot do with a list, it is helpful to be able to convert from one to the other to get the added flexibility. Why Convert A List To A Data Frame? When dealing with data structures, it is often necessary to switch between different types.
Data <- list (A = seq ( 1, 4 ), B = c ( "A", "D", "G", "L" ), C = c ( "Best", "List", "Dataframe", "Rstats" )) We can also display our list (and the vectors) like this: In the two code chunks above, we used the list () function together with two functions to first create the list called Data. Here we used c and seq in R to generate vectors.
When you create a dataframe from a list or nested list you have to change the structure of the list into that of a dataframe. However, the elements of the list need to match to avoid producing errors when creating the resulting data frame. As you can see the as.data-xpx.frame () function has produced a dataframe from the list ...
You can unlist and use matrix, then converting to data.frame. It seems to be faster for this case.
as.data.frame(matrix(unlist(L1),nrow=length(L1),byrow=TRUE)
microbenchmark::microbenchmark(
a= map_dfr(L1, ~as.data.frame(t(.x))),
b= do.call(rbind, lapply(L1, function(x) as.data.frame(t(x)))),
c= as.data.frame(t(as.data.frame(L1))),
d= data.table::transpose(as.data.frame(L1)),
e= as.data.frame(matrix(unlist(L1),nrow=length(L1),byrow=TRUE)),
times = 100,unit = "relative")
# Unit: relative
# expr min lq mean median uq max neval
# a 9.146545 8.548656 8.859087 8.859051 9.449237 7.265274 100
# b 13.879833 11.523000 11.433790 10.924726 10.797251 24.012107 100
# c 12.719835 10.635809 10.442108 10.229913 10.259789 7.020377 100
# d 10.439881 9.143530 9.205734 8.859026 9.176125 6.624454 100
# e 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 100
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