diff --git a/inst/compareScenarios/preprocessing.Rmd b/inst/compareScenarios/preprocessing.R
similarity index 95%
rename from inst/compareScenarios/preprocessing.Rmd
rename to inst/compareScenarios/preprocessing.R
index 58dc4f8..4b1730c 100644
--- a/inst/compareScenarios/preprocessing.Rmd
+++ b/inst/compareScenarios/preprocessing.R
@@ -1,11 +1,4 @@
-```{r load additional libraries}
-
-library(ggplot2)
-library(dplyr)
-
-```
-
-```{r reference models for historical}
+# reference models for historical ----
 
 # Sometimes it is necessary to choose a single model for the historical data,
 # e.g., calculating per capita variables. These reference models are defined here.
@@ -15,12 +8,9 @@ histRefModel <- c(
   "GDP|PPP pCap" = "James_IMF"
 )
 
-options(mip.histRefModel = histRefModel) # nolint
-
-```
+options(mip.histRefModel = histRefModel)
 
-
-```{r load custom plotting function}
+# load custom plotting function ----
 
 showLinePlotsByVariable <- function(
     data, vars, xVar, scales = "free_y",
@@ -109,9 +99,8 @@ showLinePlotsByVariable <- function(
   return(invisible(NULL))
 }
 
-```
+# calculate pCap variables ----
 
-```{r calcuate pCap variables}
 # For all variables in following table, add a new variable to data with the name
 # "OldName pCap". Calculate its value by OldValue * conversionFactor and set its unit to newUnit.
 # The new variable "OldName pCap" will be available in the plot sections.
@@ -172,6 +161,3 @@ dataPCap
 data %>%
   bind_rows(dataPCap) ->
 data
-```
-
-