How to specify a column name in ddply via character variable?

Question

I have a tibble/dataframe with

sample_id     condition     state
---------------------------------
sample1       case          val1
sample1       case          val2
sample1       case          val3
sample2       control       val1
sample2       control       val2
sample2       control       val3

The dataframe is generated within a for loop for different states. Hence, every dataframe has a different name for the state column.

I want to group the data by sample_id and calculate the median of the state column such that every unique sample_id has a single median value. The output should be like below...

sample_id     condition     state
---------------------------------
sample1       case          median
sample2       control       median

I am trying the command below; it is working if give the name of the column, but I am not able to pass the name via the state character variable. I tried ensym(state) and !!ensym(state) , but they all are throwing errors.

ddply(dat_state, .(sample_id), summarize,  condition=unique(condition), state_exp=median(ensym(state)))

Answer 1

As camille notes above, this is easier in dplyr. Basic syntax (not yet addressing your question):

my_df %>% 
  group_by(sample_id, condition) %>% 
  summarize(state = median(state))

Note that syntax will give you values for every unique sample_id - condition pair. Which isn't an issue in your example, since every sample_id has the same condition , but just something to be aware of.

On to your question... It's not quite clear to me how you're planning to pass the state name to your calculation. But a couple ways you can handle this. One is to use dplyr's "rename" function:

x <- "Massachusetts"
my_df %>% 
  rename(state = x) %>% 
  group_by(sample_id, condition) %>% 
  summarize(state = median(state))

The (probably more proper) way to do this is to write a function using dplyr's "tidyeval" syntax:

myfunc <- function(df, state_name) {
  df %>% 
    group_by(sample_id, condition) %>% 
    summarize(state = median({{state_name}}))
}

myfunc(my_df, Massachusetts) # Note: Unquoted state name

Answer 2

Thank you all for putting effort into answering my question. With your suggestions, I have found the solution. Below is the code to what I was trying to achieve by grouping sample_id and condition and passing state through a variable.

state_mark <- c("pPCLg2", "STAT1", "STAT5", "AKT")

for(state in state_mark){
    dat_state <- dat_clust_stim[,c("sample_id", "condition", state)]

    # I had to use !!ensym() to convert a character to a symbol.
    dat_med <- group_by(dat_state, sample_id, condition) %>% 
               summarise(med = median(!!ensym(state)))

    dat_med <- ungroup(dat_med)
    x <- dat_med[dat_med$condition == "case", "med"]
    y <- dat_med[dat_med$condition == "control", "med"]
    t_test <- t.test(x$med, y$med)
}