使用dcast函数时出现'Aggregate function missing'错误的解决及重复试验数据重塑需求

Hey there! I see where the issue is with your dcast call—let's get your data into that desired format where each treatment combination has one row with both repetition values side by side.

What Went Wrong #

Your original dcast formula grouped only by material + airspeed + classifier_speed and tried to aggregate over variable (which is just "fine_fraction" for all rows). Since you didn't specify how to handle multiple values per group, it defaulted to counting them with length—that's why you got counts instead of the actual parameter values.

The Fix: Include Repetitions in the Reshape #

You need to tell dcast to split the output columns based on your rep variable. Here's how to do it, either directly from your raw data (no need for melt first!) or adjusting your existing workflow:

Option 1: Direct Reshape from Raw Data (Simpler)

Skip the melt step entirely—dcast can handle this directly with your original dataset:

# Reshape to get one row per treatment, columns for each repetition
cast_result <- dcast(duplo_selection,
                     material + airspeed + classifier_speed ~ rep,
                     value.var = "fine_fraction")

Option 2: Adjust Your Existing Melt + Cast Workflow

If you want to keep using your melted data, just update the dcast formula to use rep as the column split variable instead of variable:

# Your original melt step is fine
melt1 <- melt(duplo_selection,
              id.vars = c("material", "airspeed", "classifier_speed", "rep"),
              measure.vars = c("fine_fraction"))

# Update dcast to split by rep
cast_result <- dcast(melt1,
                     material + airspeed + classifier_speed ~ rep,
                     value.var = "value")

Rename Columns to Match Your Desired Format #

If you want the column names to be explicitly like "Parameter of interest from repetition 1" instead of the rep codes (like L17, L19), you can rename them manually. For example, if your rep values are 1 and 2:

colnames(cast_result)[4:5] <- c("Parameter of interest from repetition 1",
                                "Parameter of interest from repetition 2")

Or if you're using the code-based reps from your example, you could map them to clearer names:

# Example mapping for your sample rep codes
name_mapping <- c("L17" = "Repetition 1", "L19" = "Repetition 2",
                  "L16" = "Repetition 1", "L22" = "Repetition 2",
                  "L18" = "Repetition 1", "L21" = "Repetition 2")
colnames(cast_result) <- ifelse(colnames(cast_result) %in% names(name_mapping),
                                name_mapping[colnames(cast_result)],
                                colnames(cast_result))

What You'll Get #

Running either option will give you a data frame where each row is a unique combination of material, airspeed, and classifier_speed, with separate columns holding the fine_fraction value from each repetition—exactly what you were aiming for!

内容的提问来源于stack exchange，提问作者Marjanne