--- a
+++ b/R/MergeIDPosition.R
@@ -0,0 +1,62 @@
+#' Merge Data Frames by Common Row Names with Additional Columns
+#'
+#' This function merges a list of data frames based on common row names. It adds an 'id' column to track the row order and a 'point_position' column calculated based on the maximum 'Count' value across all data frames. It filters data frames to include only common rows, sorts rows by the length of the 'Description' in descending order, and then merges them by rows.
+#'
+#' @param df_list A list of data frames, each with a 'Description' and 'Count' column and set row names.
+#' @return A single data frame merged from the list, with additional 'id' and 'point_position' columns.
+#' @importFrom dplyr arrange
+#' @examples
+#' df1 <- data.frame(Description = c("DataA", "DataB"), Count = c(10, 20), row.names = c("R1", "R2"))
+#' df2 <- data.frame(Description = c("DataC", "DataD"), Count = c(30, 40), row.names = c("R1", "R3"))
+#' df_list <- list(df1, df2)
+#' combined_df_test <- merge_id_position(df_list)
+#'
+#' @export
+merge_id_position <- function(df_list) {
+  # Find common row names across all data frames
+  common_row_names <- Reduce(intersect, lapply(df_list, row.names))
+
+  # Get the maximum value of the 'Count' column across all data frames
+  max_count <- max(sapply(df_list, function(df) max(as.numeric(df$Count), na.rm = TRUE)))
+
+  # Calculate the smallest multiple of 10 greater than the maximum count
+  ceiling_max_count <- ceiling(max_count / 10) * 10
+
+  # Initialize a list to store processed data frames
+  processed_dfs <- list()
+  number_of_dfs <- length(df_list)
+
+  # Process each data frame
+  for (i in seq_along(df_list)) {
+    # Filter for common rows
+    filtered_df <- df_list[[i]][common_row_names, , drop = FALSE]
+
+    # Sort 'Description' column by character length in descending order
+    filtered_df <- filtered_df %>% dplyr::arrange(desc(nchar(.data$Description)))
+
+    # Add 'id' column
+    filtered_df$id <- seq_len(nrow(filtered_df))
+
+    # Calculate 'point_position' value
+    point_position_value <- ceiling_max_count * i / number_of_dfs
+
+    # Add 'point_position' column
+    filtered_df$point_position <- point_position_value
+
+    # Append processed data frame to the list
+    processed_dfs[[i]] <- filtered_df
+  }
+
+  # Check if any data frames are empty after filtering
+  if (any(sapply(processed_dfs, nrow) == 0)) {
+    stop("One or more dataframes have no rows after filtering for common row names.")
+  }
+
+  # Merge data frames by rows
+  combined_df <- do.call(rbind, processed_dfs)
+
+  # Remove original row names and set new row names as NULL
+  rownames(combined_df) <- NULL
+
+  return(combined_df)
+}