I got help here yesterday to create a facet grid of multiple columns. This yielded a large grid containing 8*5 plots. The code creates a combination of plot for various Outcomes * Responses. For example (Outcome1 * Response1, Outcome1 * Response2, Outcome3 * Response1, Outcome2 * Response1 and so on).
I have pasted the code below.
plot1 <- ancestralmeansindex %>%
gather(var1, value1, bicepind:wcind) %>%
gather(var2, value2, mmois:mpfat) %>%
ggplot(aes(x = value1, y = value2)) +
geom_point(color='blue') +
geom_smooth(method = "lm", se = FALSE) +
facet_grid(var2 ~ var1, scales = "free", switch = "both",
labeller = as_labeller(c(mmois = "Water (gms)",
mkcal = "Caloric Intake",
mprot = "Protein (gms)",
mcarb = "Carb (gms)",
mtfat = "Total Fat (gms)",
msfat = "Saturated Fat (gms)",
mmfat = "Mono S.Fat (gms)",
mpfat = "Poly US.Fat (gms)",
bicepind = "Bicep",
tricepind = "Tricep",
subind = "Subscapular",
supind = "Suprailiac",
weightind = "Weight",
wcind = "Waist Circum"))) +
labs(title = "Regression Plot Matrix of Mean Dietary Values with Index Change 1", x = NULL, y = NULL) +
theme_bw() +
theme(strip.placement = "outside",
strip.background = element_blank())
ggsave("Regression Plot 1.pdf", width = 210, height = 297, units = "mm", plot1)
This gives a very neat grid of all the possible combinations mentioned in the code. However, the graph prints the plots in alphabetical order (as it is reflected in the labeller/data). I would like to change this order for both var2 and var1.
I read in the help that this problem can be solved by assigning factor levels and choosing a given order. For example, this solution Fixing the order of facets in ggplot
How do I assign factor levels to variables that have been converted to long form by dplyr? Can this be done? Is there another solution?
Edit1 I tried the solution below, but I am running into an error. Reproducible example below.
set.seed(1)
dat <- data.frame(
Outcome1 = sample(1:10),
Outcome2 = sample(11:20),
Outcome3 = sample(21:30),
Response1 = sample(31:40),
Response2 = sample(41:50),
Response3 = sample(51:60)
)
dat %>%
gather(var1, value1, Outcome1:Outcome3) %>%
mutate(var1, recode("Outcome1" = "Bicep",
"Outcome2" = "Tricep",
"Outcome3" = "Subscapular")) %>%
factor(var1, levels = c("Bicep",
"Tricep",
"Subscapular"))
gather(var2, value2, Response1:Response3) %>%
mutate(var2, recode("Response1" = "Water (gms)",
"Response2" = "Caloric Intake",
"Response3" = "Protein (gms)")) %>%
factor(var2, levels = c("Water (cms)",
"Caloric Intake",
"Protein (gms)")) %>%
ggplot(aes(x = value1, y = value2)) +
geom_point(color='blue') +
geom_smooth(method = "lm", se = FALSE) +
facet_grid(var2 ~ var1, scales = "free", switch = "both",
labeller = as_labeller(c(mmois = "Water (gms)",
mkcal = "Caloric Intake",
mprot = "Protein (gms)",
bicepind = "Bicep",
tricepind = "Tricep",
subind = "Subscapular"))) +
labs(title = "Regression Plot", x = NULL, y = NULL) +
theme_bw() +
theme(strip.placement = "outside",
strip.background = element_blank())
Error in factor(., var1, levels = c("Bicep", "Tricep", "Subscapular", :
object 'var1' not found
Error in gather(var2, value2, Response1:Response3) :
object 'var2' not found