Join multiple tables dynamically - r

Question

The problem
Hi all,
I am trying to join a few dataframes together dynamically. For me that means that I have a dataframe that I start with df_A, to which I want to join multiple other dataframesdf_B1, df_B2,df_B3, etc..
df_A contains a column for each of the df_B... tables to join against. Column_join_B1, Column_join_B2, Column_join_B3, etc. (Although in reality these have obscure names). These names are also in a vector df_A_join_names.
df_B1, df_B2, df_B3, etc.. are stored in a list df_B, which I understand is good practice to do :). This is also how I access them in my loop.
Each of these has two columns. One with the value to join against df_A The other with information.
I even tried renaming the first column to match the column in df_A before the join, but to no avail.
What I am trying
left_join() does not allow me simply use by = c(df_A_join_names[1], "Column_join_A") so I have to use setNames, but I cannot get this to work.
Below a function which I want to iterate in a loop:
my_join <- function(df_a, df_b, a_name, b_name){
df_joined <- left_join(df_a, df_b,
by = setNames(b_name, a_name))
return(df_joined)
}
I want to use this function in a loop to join all my df_B... dataframes against df_A.
for (i in 1: length(df_A_join_names)){
df_A <- my_join(df_a = df_A,
df_b = df_B[i],
a_name = as.character(df_A_join_names[i]),
b_name = "Column_join_A"
)
}
Running this I get:
Error in UseMethod("tbl_vars") :
no applicable method for 'tbl_vars' applied to an object of class "list"
Some stuff to play with
#Making df_A
A_a <- seq(1,10, by = 1)
Column_join_B1 <- seq(11,20, by = 1)
Column_join_B2 <- seq(21,30, by = 1)
df_A <- data.frame(cbind(A_a, Column_join_B1, Column_join_B2) )
#Making df_B
Column_join_A <- seq(11,20, by = 1)
B_a <- LETTERS[1:10]
df_B1 <- data.frame(Column_join_A, B_a )
Column_join_A <- seq(21,30, by = 1)
B_b <- LETTERS[11:20]
df_B2 <- data.frame(Column_join_A, B_b)
# In my own code I make this using a loop. maybe not the prettiest.
df_B <- list()
df_B[[1]] <- df_B1
df_B[[2]] <- df_B2
df_A_join_names <- c("Column_join_B1", "Column_join_B2")
References
I'm trying to apply this:
Dplyr join on by=(a = b), where a and b are variables containing strings?
I'm curious to hear what you guys think!

Answer 1

There's no need for building a specific function, you can simply use SetNames within left_join function:
df_B_join_name <- "Column_join_A"
for (i in 1: length(df_A_join_names)){
df_A <- left_join(df_A, df_B[[i]], by=c(setNames(nm = df_A_join_names[i], df_B_join_name)))
}

Answer 2

You were very close! The only thing you might need to change is the way you reference the data frame under list df_B. df_B[1] will still be a list, df_B[[1]] will return a data frame. I ran the code below and it worked for me.
for (i in 1: length(df_A_join_names)){
df_A <- my_join(df_a = df_A,
df_b = df_B[[i]],
a_name = as.character(df_A_join_names[i]),
b_name = "Column_join_A"
)
}

Answer 3

First, manage to rename the first column in df_B to match the column in df_A. So df_B will look like this:
# [[1]]
# Column_join_B1 B_a
# 1 11 A
# 2 12 B
# . . .
# . . .
# . . .
#
# [[2]]
# Column_join_B2 B_b
# 1 21 K
# 2 22 L
# . . .
# . . .
# . . .
Next, use Reduce() in base or reduce() in purrr to iterate the manipulation of left_join. You even don't need to use the for loop.
Reduce(left_join, df_B, init = df_A)
# A_a Column_join_B1 Column_join_B2 B_a B_b
# 1 1 11 21 A K
# 2 2 12 22 B L
# 3 3 13 23 C M
# 4 4 14 24 D N
# 5 5 15 25 E O
# 6 6 16 26 F P
# 7 7 17 27 G Q
# 8 8 18 28 H R
# 9 9 19 29 I S
# 10 10 20 30 J T