How to Use a Variable to Specify Column Name in Ggplot

How to use a variable to specify column name in ggplot

You can use aes_string:

f <- function( column ) {
    ...
    ggplot( rates.by.groups, aes_string(x="name", y="rate", colour= column,
                                        group=column ) )
}

as long as you pass the column to the function as a string (f("majr") rather than f(majr)). Also note that we changed the other columns, "name" and "rate", to be strings.

If for whatever reason you'd rather not use aes_string, you could change it to (the somewhat more cumbersome):

    ggplot( rates.by.groups, aes(x=name, y=rate, colour= get(column),
                                        group=get(column) ) )

Pass/loop over column names to data.table and ggplot as variables

try to use get(ZZZ) in loop body, instead of ZZZ

Refering a column by its name in ggplot in a loop

We can use aes_string to pass strings

l1 <- vector("list", length(var.names))
for(v in seq_along(var.names)){
      variable <- var.names[v]
      l1[[v]] <- ggplot(df, aes_string(x = variable)) + 
                  geom_histogram() +
                  facet_wrap(~id)
 }

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Or another option in the dev version should be to convert the string to symbol (rlang::sym) and evaluate (!!) within the aes

for(v in seq_along(var.names)){
      variable <- rlang::sym(var.names[v])
      l1[[v]] <- ggplot(df, aes(x = !!variable)) +
                   geom_histogram() +
                    facet_wrap(~id)
 }

The plots stored in the list can be saved in a .pdf file

library(gridExtra)
l2 <- map(l1, ggplotGrob)
ggsave(marrangeGrob(grobs = l2, nrow = 1, ncol = 1), file = 'plots.pdf')

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If we need to overlay the three plots in a single page, use gather to convert to 'long' format

library(tidyr)
library(dplyr)
gather(df, key, val, var.names) %>% 
    ggplot(., aes(x = val, fill = key)) +
    geom_histogram() + 
    facet_wrap(~id)

-output

ggplot2 Variable Name with Spaces and tidyeval Syntax

Because it's quoted text, instead of enquo, use rlang::sym

xVariable <- "Month"
yVariable <- "High Temperature"
fun <- function(dat, xvar, yvar) {
  xvar <- rlang::sym(xvar)
  yvar <- rlang::sym(yvar)
  p1 <-dat %>%
    ggplot(aes(x = !!xvar, y = !!yvar)) +
    geom_point()
  return(p1)
  
}


fun(weather, xVariable, yVariable)

Variable name as argument in function - ggplot R

If you call plot_var_aantal with a string like "people" you need to evalute vari as a symbol on the righthand side with !!sym(vari) and on the lefthand side you need to put it into a glue specification "{vari}". The following code should work:

plot_var_aantal<-function(vari){
  eval(substitute(vari), MASTERDATA)
  MASTERDATA%>%
    group_by(COMPANY)%>%
    summarize(AMOUNT_COMP = (sum(AMOUNT, na.rm=TRUE)),
              Type=Type,
              "{vari}" := !!sym(vari)) %>% # changed this line 
    filter(!is.na(Type)) %>%
    ggplot(aes(!! sym(vari),AMOUNT_COMP ), na.rm = TRUE) + # changed this line
    geom_point()+
    facet_wrap(~Type,nrow=4)
  
}

However, without seeing your data it is hard to figure out what COMP_VAR1 = COMP_VAR1 is doing in your dplyr::summarise call. You are not using an aggregating function (like mean or paste(..., collapse = ",")) so the whole summarise is probably not summarising but returning data in the original length. Similarly the line "{vari}" := !!sym(vari) doesn't seem to make sense (although the non-standard evaluation when vari is a string, is correct).

R pass variable column indices to ggplot2

You can use the aes_string in stead of aes to pass string in stead of using objects, i.e.:

myplot = function(df, x_string, y_string) {
   ggplot(df, aes_string(x = x_string, y = y_string)) + geom_point()
 }
myplot(df, "A", "B")
myplot(df, "B", "A")

ggplot and dplyr and column name as string

You need to UQ (or !!) the name/symbol. For example

for(el in name_list){
  pdf(paste(el, '.pdf', sep =''))
  test <- my_df %>% group_by(UQ(as.name(el))) %>% summarize(count = n())
  print(ggplot(data = test, aes_string(x = el, y = 'count')) + geom_bar(stat='identity'))
  dev.off()
}

Use ggplot in an R function with three inputs: filename of dataframe, and two column variables of numeric data

df <- data.frame(
  "choco" = 1:5,
  "tea" = c(2, 4, 5, 8, 10),
  "coffee" = c(0.5, 2, 3, 1.5, 2.5),
  "sugar" = 16:20
)

test <- function(Data, ing1, ing2)  {
  if (ing1 %in% names(Data)  &  ing2 %in% names(Data)) {
    ggplot(Data, aes(x = Data[, ing1], y = Data[, ing2])) +
      geom_point()
  }
  else {
    print("Both ing1, and ing2 has to be columns of data frame")
  }
}
test(Data = df, ing1 = "choco", ing2 = "sugar")

Regards,
Grzegorz

Is it possible to make a column plot using ggplot in which the column fill is controlled by a third variable?

It looks like you have 3 X values that each appear 5, 10, or 15 times. Do you want the bars to be overlaid on top of one another, as they are now? If you add an alpha = 0.5 to the geom_col call you'll see the overlapping bars.

Alternatively, you might use dodging to show the bars next to one another instead of on top of one another.

ggplot(df, aes(x=x, y=y, fill=z, group = z)) + 
  geom_col(width=0.5, position=position_dodge()) +
  scale_fill_viridis_c(option="turbo", # added with ggplot 3.x in 2018
                     limits = c(0,10),
                     breaks=seq(0,10,2.5),
                     labels=c("0","2.5","5.0","7.5","10.0"))

Or you might plot the data in order of y so that the smaller bars appear on top, visibly:

ggplot(dplyr::arrange(df,y), aes(x=x, y=y, fill=z))+ 
  geom_col(width=0.5, position="identity") +
  scale_fill_viridis_c(option="turbo",
                     limits = c(0,10),
                     breaks=seq(0,10,2.5),
                     labels=c("0","2.5","5.0","7.5","10.0"))

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