diff --git a/R-package/R/xgb.plot.importance.R b/R-package/R/xgb.plot.importance.R
index 2c02d5a42..07220375d 100644
--- a/R-package/R/xgb.plot.importance.R
+++ b/R-package/R/xgb.plot.importance.R
@@ -87,7 +87,13 @@ xgb.plot.importance <- function(importance_matrix = NULL, top_n = NULL, measure
   }
 
   # also aggregate, just in case when the values were not yet summed up by feature
-  importance_matrix <- importance_matrix[, Importance := sum(get(measure)), by = Feature]
+  importance_matrix <- importance_matrix[
+    , lapply(.SD, sum)
+    , .SDcols = setdiff(names(importance_matrix), "Feature")
+    , by = Feature
+  ][
+    , Importance := get(measure)
+  ]
 
   # make sure it's ordered
   importance_matrix <- importance_matrix[order(-abs(Importance))]
diff --git a/R-package/tests/testthat/test_helpers.R b/R-package/tests/testthat/test_helpers.R
index 04e034ce1..de6a099fc 100644
--- a/R-package/tests/testthat/test_helpers.R
+++ b/R-package/tests/testthat/test_helpers.R
@@ -382,6 +382,9 @@ test_that("xgb.importance works with GLM model", {
   expect_equal(colnames(imp2plot), c("Feature", "Weight", "Importance"))
   xgb.ggplot.importance(importance.GLM)
 
+  # check that the input is not modified in-place
+  expect_false("Importance" %in% names(importance.GLM))
+
   # for multiclass
   imp.GLM <- xgb.importance(model = mbst.GLM)
   expect_equal(dim(imp.GLM), c(12, 3))
@@ -400,6 +403,16 @@ test_that("xgb.model.dt.tree and xgb.importance work with a single split model",
   expect_equal(imp$Gain, 1)
 })
 
+test_that("xgb.plot.importance de-duplicates features", {
+  importances <- data.table(
+    Feature = c("col1", "col2", "col2"),
+    Gain = c(0.4, 0.3, 0.3)
+  )
+  imp2plot <- xgb.plot.importance(importances)
+  expect_equal(nrow(imp2plot), 2L)
+  expect_equal(imp2plot$Feature, c("col2", "col1"))
+})
+
 test_that("xgb.plot.tree works with and without feature names", {
   .skip_if_vcd_not_available()
   expect_silent(xgb.plot.tree(feature_names = feature.names, model = bst.Tree))