I want to merge duplicate rows in a table. It should sum together all metrics in rows if the dimensions are the same.

|    date    | page   | users | sessions |
| ---------- | ------ | ----- | -------- |
| 2024-05-01 | a.html | 20    | 22       |
| 2024-05-01 | b.html | 14    | 16       |
| 2024-05-01 | a.html | 2     | 3        |

Result:

|    date    | page   | users | sessions |
| ---------- | ------ | ----- | -------- |
| 2024-05-01 | a.html | 22    | 25       |
| 2024-05-01 | b.html | 14    | 16       |

Here is a lengthy code that does exactly what I need:

if ("page" %in% colnames(data)) {
  if ("segment" %in% colnames(data)) {
    data <- aggregate(. ~ date + page + segment, data, sum)
  } else {
    data <- aggregate(. ~ date + page, data, sum)
  }
} else if ("campaign" %in% colnames(data)) {
  if ("channelGrouping" %in% colnames(data)) {
    data <- aggregate(. ~ date + campaign + channelGrouping, data, sum)
  } else {
    data <- aggregate(. ~ date + campaign, data, sum)
  }
} else if ("channelGrouping" %in% colnames(data)) {
  data <- aggregate(. ~ date + channelGrouping, data, sum)
} else {
  data <- aggregate(. ~ date, data, sum)
}
# ... other similar lines of code here
data <- data[order(data$date), ]

I want to simplify that so it uses a dynamic list of dimensions so I don’t need to use a lot of IF conditions.

Changing:

data <- aggregate(. ~ date + page, data, sum)

To:

data <- aggregate(. ~ insert_dynamic_dimensions_list, data, sum)

But the aggregating line shows a wrapup error:

columns = c("date")
if ("page" %in% colnames(data)) columns <- c(columns, "page")
if ("campaign" %in% colnames(data)) columns <- c(columns, "campaign")
if ("channelGrouping" %in% colnames(data)) columns <- c(columns, "channelGrouping")
if ("segment" %in% colnames(data)) columns <- c(columns, "segment")
data <- aggregate(. ~ .[columns], data, sum) ### <== This throws aggregating error
data <- data[order(data$date), ]