How to set a loop to assign lots of variables - r

Question

I just started using R for a psych class, so please go easy on me. I watched a bunch of youtube videos on For loops, but none have answered my question. I have 4 data frames (A, B, C, D), each with 25 columns. I want to combine the nth column from each data frame together, and save them as an object, like so:
Q1 <- cbind(A[1], B[1], C[1], D[1])
Q2 <- cbind(A[2], B[2], C[2], D[2])
How can I set a loop to do this for all 25 so I don’t have to do it manually?
Thanks in advance
Each of my data frames looks like this (with column headings reflecting the letter of the data frame (i.e. B has QB1, QB2, etc.
QA1 QA2 QA3 QA4 QA5 QA6 QA7 QA8 QA9 QA10 QA11 QA12 QA13 QA14 QA15
1 1 2 2 0 0 2 0 1 0 0 0 0 0 0 0
2 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0
3 1 0 0 0 0 0 1 0 0 2 1 1 0 0 0
4 1 0 0 0 0 0 1 1 0 1 0 2 0 0 0

Answer 1

In order to do it in a for loop, you need to use assign() from baseR and eval_tidy(), sym() from rlang(). Basically, you will need to evaluate strings as variables.
Create simulation data
library(rlang)
nrows = 10
ncols = 25
df_names <- c("A","B","C","D")
for(df_name in df_names){
# assign value to a string as variable
assign(
df_name,
as.data.frame(
matrix(
data = sample(
c(0,1),
size = nrows * ncols,
replace = TRUE
),
ncol = 25
)
)
)
# rename columns
assign(
df_name,
setNames(eval_tidy(sym(df_name)),paste0("Q",df_name,1:ncols))
)
}
Show A
> head(A)
QA1 QA2 QA3 QA4 QA5 QA6 QA7 QA8 QA9 QA10 QA11 QA12 QA13 QA14 QA15 QA16 QA17 QA18 QA19 QA20 QA21 QA22 QA23 QA24 QA25
1 1 1 0 0 1 0 1 0 1 1 0 0 1 1 1 0 0 1 0 0 1 1 0 1 1
2 0 1 0 1 1 1 1 0 1 1 1 1 0 0 0 1 0 1 1 0 1 0 1 1 0
3 0 0 0 1 1 0 1 0 1 0 0 1 0 0 0 1 1 1 1 0 0 0 1 1 1
4 0 0 1 1 1 0 0 1 1 1 1 0 1 1 0 1 0 0 0 1 0 1 1 1 1
5 1 1 0 1 1 1 1 1 1 0 1 0 0 0 0 0 1 0 1 0 1 1 0 1 1
6 1 1 0 0 1 1 0 1 1 1 0 1 0 1 1 0 1 0 0 1 1 0 1 1 0
To answer your question:
This should create 25 variables from Q1 to Q25:
# assign dataframes from Q1 to Q25
for(i in 1:25){
new_df_name <- paste0("Q",i)
# initialize Qi with the same number of rows as A,B,C,D ...
assign(
new_df_name,
data.frame(tmp = matrix(NA,nrow = rows))
)
# loop A,B,C,D ... and bind them
for(df_name in df_names){
assign(
new_df_name,
cbind(
eval_tidy(sym(new_df_name)),
eval_tidy(sym(df_name))[,i,drop = FALSE]
)
)
}
# drop tmp to clean up
assign(
new_df_name,
eval_tidy(sym(new_df_name))[,-1]
)
}
Show result:
> Q25
QA25 QB25 QC25 QD25
1 1 0 1 1
2 0 1 0 0
3 1 1 0 0
4 1 0 1 1
5 1 1 0 0
6 0 1 1 1
7 1 0 0 0
8 0 0 0 1
9 1 1 1 0
10 0 0 1 1
The codes should be much easier if you save results in a list using map(). The major complexity is from assigning values to separate variables.

Answer 2

You can combine some dplyr verbs in a for loop to combine the columns from each data set and assign them to 25 new objects.
# merge data, gather, split by var numbers, assign each df to environment
for (i in 1:25) {
df <- cbind(q1,q2,q3,q4) %>% mutate(id=row_number()) %>%
gather(k,v,-id) %>%
mutate(num=sub('A|B|C|D','',k)) %>%
filter(num==i) %>% select(-num) %>% spread(k,v)
assign(paste0('df',i),df)
}
ls(pattern = 'df')
[1] "df1" "df10" "df11" "df12" "df13" "df14" "df15" "df16" "df17" "df18" "df19" "df2"
[13] "df20" "df21" "df22" "df23" "df24" "df25" "df3" "df4" "df5" "df6" "df7" "df8"
[25] "df9"
Code to create initial 4 toy data frames.
# create four toy data frames
q1 <- data.frame(matrix(runif(100),ncol=25))
q2 <- data.frame(matrix(runif(100),ncol=25))
q3 <- data.frame(matrix(runif(100),ncol=25))
q4 <- data.frame(matrix(runif(100),ncol=25))
# set var names for each toy data
names(q1) <- sub('X','A',names(q1))
names(q2) <- sub('X','B',names(q2))
names(q3) <- sub('X','C',names(q3))
names(q4) <- sub('X','D',names(q4))