# Creating multiple graphs based upon the column names

A solution using `tidyeval` approach. We will need `ggplot2 v3.0.0` (remember to restart your R session)

``````install.packages("ggplot2", dependencies = TRUE)
``````
• First we build a function that takes column and group names as inputs. Note the use of `rlang::sym`, `rlang::quo_name` & `!!`.

• Then create 2 name vectors for `x-` & `y-` values so that we can loop through them simultaneously using `purrr::map2`.

``````library(rlang)
library(tidyverse)

df <- structure(list(ID = structure(1:6, .Label = c("101","102","103","118","119","120"), class = "factor"),
Group = structure(c(1L,1L,1L,2L,2L,2L), .Label = c("C8","TC"), class = "factor"),
Wave = structure(c(1L, 2L, 3L, 4L, 1L, 2L), .Label = c("A","B","C","D"), class = "factor"),
Yr = structure(c(1L, 2L, 1L, 2L, 1L, 2L), .Label = c("3","5"), class = c("ordered", "factor")),
Age.Yr. = c(10.936,10.936, 9.311, 10.881, 10.683, 11.244),
Training..hr. = c(10.667,10.333, 10.667, 10.333, 10.333, 10.333),
X1BCSTCAT = c(-0.156,0.637,-1.133,0.637,2.189,1.229),
X1BCSTCR = c(0.484,0.192, -1.309, 0.912, 1.902, 0.484),
X1BCSTPR = c(-1.773,0.859, 0.859, 0.12, -1.111, 0.12),
X2BCSTCAT = c(1.006, -0.379,-1.902, 0.444, 2.074, 1.006),
X2BCSTCR = c(0.405, -0.457,-1.622, 1.368, 1.981, 0.168),
X2BCSTPR = c(-0.511, -0.036,2.189, -0.036, -0.894, 0.949),
X3BCSTCAT = c(1.18, -1.399,-1.399, 1.18, 1.18, 1.18),
X3BCSTCR = c(0.967, -1.622, -1.622,0.967, 0.967, 1.255),
X3BCSTPR = c(-1.282, -1.282, 1.539,1.539, 0.792, 0.792)),
row.names = c(1L, 2L, 3L, 4L, 5L,8L), class = "data.frame")

# define a function that accept strings as input
pair_plot <- function(x_var, y_var, group_var) {

# convert strings to symbols
x_var <- rlang::sym(x_var)
y_var <- rlang::sym(y_var)
group_var <- rlang::sym(group_var)

# unquote symbols using !!
ggplot(df, aes(x = !! x_var, y = !! y_var, shape = !! group_var, color = !! group_var)) +
geom_point() + geom_smooth(method = lm, aes(fill = !! group_var), fullrange = TRUE) +
labs(title = "BCSTCAT", x = rlang::quo_name(x_var), y = rlang::quo_name(y_var)) +
scale_color_manual(name = "Group", labels = c("C8", "TC"), values = c("blue", "red")) +
scale_shape_manual(name = "Group", labels = c("C8", "TC"), values = c(16, 17)) +
scale_fill_manual(name = "Group",  labels = c("C8", "TC"), values = c("light blue", "pink")) +
theme_bw()
}

# Test if the new function works
pair_plot("X1BCSTCAT", "X2BCSTCAT", "Group")
``````

``````# Create 2 parallel lists
list_x <- colnames(df)[-c(1:6, (ncol(df)-2):(ncol(df)))]
list_x
#> [1] "X1BCSTCAT" "X1BCSTCR"  "X1BCSTPR"  "X2BCSTCAT" "X2BCSTCR"  "X2BCSTPR"

list_y <- lead(colnames(df)[-(1:6)], 3)[1:length(list_x)]
list_y
#> [1] "X2BCSTCAT" "X2BCSTCR"  "X2BCSTPR"  "X3BCSTCAT" "X3BCSTCR"  "X3BCSTPR"

# Loop through 2 lists simultaneously
# Supply inputs to pair_plot function using purrr::map2
map2(list_x, list_y, ~ pair_plot(.x, .y, "Group"))
``````

Sample outputs:

``````#> [[1]]
``````

``````#>
#> [[2]]
``````

Created on 2018-05-24 by the reprex package (v0.2.0).