cbind a dataframe with an empty dataframe - cbind.fill?
RDataframeCbindR Problem Overview
I think I'm looking for an analog of rbind.fill (in Hadley's plyr package) for cbind. I looked, but there is no cbind.fill.
What I want to do is the following:
#set these just for this example
one_option <- TRUE
diff_option <- TRUE
return_df <- data.frame()
if (one_option) {
#do a bunch of calculations, produce a data.frame, for simplicity the following small_df
small_df <- data.frame(a=1, b=2)
return_df <- cbind(return_df,small_df)
}
if (diff_option) {
#do a bunch of calculations, produce a data.frame, for simplicity the following small2_df
small2_df <- data.frame(l="hi there", m=44)
return_df <- cbind(return_df,small2_df)
}
return_df
Understandably, this produces an error:
Error in data.frame(..., check.names = FALSE) :
arguments imply differing number of rows: 0, 1
My current fix is to replace the line return_df <- data.frame() with return_df <- data.frame(dummy=1) and then the code works. I then just remove dummy from the return_df at the end. After adding the dummy and running the above code, I get
dummy a b l m
1 1 1 2 hi there 44
I then just need to get rid of the dummy, e.g.:
> return_df[,2:ncol(return_df)]
a b l m
1 1 2 hi there 44
I'm sure I'm missing an easier way to do this.
edit: I guess I'm not looking for a cbind.fill because that would mean that an NA value would be created after the cbind, which is not what I want.
R Solutions
Solution 1 - R
Here's a cbind fill:
cbind.fill <- function(...){
nm <- list(...)
nm <- lapply(nm, as.matrix)
n <- max(sapply(nm, nrow))
do.call(cbind, lapply(nm, function (x)
rbind(x, matrix(, n-nrow(x), ncol(x)))))
}
Let's try it:
x<-matrix(1:10,5,2)
y<-matrix(1:16, 4,4)
z<-matrix(1:12, 2,6)
cbind.fill(x,y)
cbind.fill(x,y,z)
cbind.fill(mtcars, mtcars[1:10,])
I think I stole this from somewhere.
EDIT STOLE FROM HERE: LINK
Solution 2 - R
While, I think Tyler's solution is direct and the best here, I just provide the other way, using rbind.fill() that we already have.
require(plyr) # requires plyr for rbind.fill()
cbind.fill <- function(...) {
transpoted <- lapply(list(...),t)
transpoted_dataframe <- lapply(transpoted, as.data.frame)
return (data.frame(t(rbind.fill(transpoted_dataframe))))
}
Solution 3 - R
Using rowr::cbind.fill
rowr::cbind.fill(df1,df2,fill = NA)
A B
1 1 1
2 2 2
3 3 3
4 4 4
5 5 5
6 NA 6
Solution 4 - R
cbind.na from the qpcR package can do that.
install.packages("qpcR")
library(qpcR)
qpcR:::cbind.na(1, 1:7)
Solution 5 - R
When a and b are data frames, following should work just fine:
ab <- merge(a, b, by="row.names", all=TRUE)[,-1]
or another possibility:
rows <- unique(c(rownames(a), rownames(b)))
ab <- cbind(a[rows ,], b[rows ,])
Solution 6 - R
I suggest a modification of Tyler's answer. My function allows cbind-ing of data.frames and/or matrices with vectors without loosing column names as it happens in Tyler's solution
cbind.fill <- function(...){
nm <- list(...)
dfdetect <- grepl("data.frame|matrix", unlist(lapply(nm, function(cl) paste(class(cl), collapse = " ") )))
# first cbind vectors together
vec <- data.frame(nm[!dfdetect])
n <- max(sapply(nm[dfdetect], nrow))
vec <- data.frame(lapply(vec, function(x) rep(x, n)))
if (nrow(vec) > 0) nm <- c(nm[dfdetect], list(vec))
nm <- lapply(nm, as.data.frame)
do.call(cbind, lapply(nm, function (df1)
rbind(df1, as.data.frame(matrix(NA, ncol = ncol(df1), nrow = n-nrow(df1), dimnames = list(NULL, names(df1))))) ))
}
cbind.fill(data.frame(idx = numeric()), matrix(0, ncol = 2),
data.frame(qwe = 1:3, rty = letters[1:3]), type = "GOOD", mark = "K-5")
# idx V1 V2 qwe rty type mark
# 1 NA 0 0 1 a GOOD K-5
# 2 NA NA NA 2 b GOOD K-5
# 3 NA NA NA 3 c GOOD K-5
Solution 7 - R
I just find a trick that when we want to add columns into an empty dataframe, just rbind it at first time, than cbind it later.
newdf <- data.frame()
# add the first column
newdf <- rbind(newdf,data.frame("col1"=c("row1"=1,"row2"=2)))
# add the second column
newdf <- cbind(newdf,data.frame("col2"=c("row1"=3,"row2"=4)))
# add more columns
newdf <- cbind(newdf,data.frame("col3"=c("row1"=5,"row2"=6)))
# result
# col1 col2 col3
#row1 1 3 5
#row2 2 4 6
I don't know why, but it works for me.
Solution 8 - R
We could add id column then use merge:
df1 <- mtcars[1:5, 1:2]
# mpg cyl id
# Mazda RX4 21.0 6 1
# Mazda RX4 Wag 21.0 6 2
# Datsun 710 22.8 4 3
# Hornet 4 Drive 21.4 6 4
# Hornet Sportabout 18.7 8 5
df2 <- mtcars[6:7, 3:4]
# disp hp
# Valiant 225 105
# Duster 360 360 245
#Add id column then merge
df1$id <- seq(nrow(df1))
df2$id <- seq(nrow(df2))
merge(df1, df2, by = "id", all.x = TRUE, check.names = FALSE)
# id mpg cyl disp hp
# 1 1 21.0 6 225 105
# 2 2 21.0 6 360 245
# 3 3 22.8 4 NA NA
# 4 4 21.4 6 NA NA
# 5 5 18.7 8 NA NA
Solution 9 - R
We can use a list instead of data.frame and convert it to a data.frame at the end. For instance:
df = list()
df2 = data.frame(col1 = 1:3, col2 = c('a','b','c'))
df = as.data.frame(cbind(df, as.matrix(df2)))
df
# col1 col2
# 1 1 a
# 2 2 b
# 3 3 c
Solution 10 - R
To cbind.fill named lists, where the names overlap and you wish to cbind by names, Tyler's answer may be modified to the following:
cbind.fill <- function(...){
nm <- list(...)
nm <- lapply(nm, as.matrix)
names <- unique(do.call(c, lapply(nm, rownames)))
res <- matrix(nrow = length(names), ncol = length(nm))
rownames(res) <- names
for(i in 1:length(nm))
res[rownames(nm[[i]]),i] <- nm[[i]][,1]
res
}