fixed #2

Author: usrbinr

R/data.R

@@ -4,7 +4,7 @@
 #' It provides insights into the transactions that have occurred, including order dates, delivery dates, customer and store information,
 #' as well as product details.
 #'
-#' @format A data frame with 12 columns:
+#' @format A data frame with 17 columns:
 #' \describe{
 #'   \item{order_key}{\code{double} Unique identifier for each order.}
 #'   \item{line_number}{\code{double} Line number within the order (for multi-line orders).}
@@ -19,8 +19,12 @@
 #'   \item{unit_cost}{\code{double} The cost per unit of the product.}
 #'   \item{currency_code}{\code{character} The currency code used for the transaction (e.g., USD, EUR).}
 #'   \item{exchange_rate}{\code{double} The exchange rate applied to the currency, if applicable.}
+#'   \item{revenue}{\code{double} A product's unit_price multiplied by quantity.}
+#'   \item{cogs}{\code{double} A product's unit_cost multiplied by quantity.}
+#'   \item{margin}{\code{double} A product's revenue minus cogs.}
+#'   \item{unit_margin}{\code{double} A product unit_price minus unit_cost.}
 #' }
-#' @source Contonso dataset
+#' @source https://github.com/sql-bi/Contoso-Data-Generator-V2-Data/releases/tag/ready-to-use-data
 "sales"
 
 

README.qmd

@@ -34,7 +34,7 @@ The package comes with the following datasets:
   - Contains detailed line items for each order, including product key, quantity, and price for each item in the order.
 
 
-  You can either load the datasets directly or use the function `create_contoso_duckdb()` to create a DuckDB  that contains the following tables:
+  You can either load the datasets directly or use the function `create_contoso_duckdb()` to create a DuckDB database that contains the following tables:
 
  The Contoso dataset is a fictional set of data created by Microsoft. It is commonly used for educational and demonstration purposes to showcase various features of data analysis, business intelligence tools, and data processing techniques
 

data-raw/sales.R

@@ -5,7 +5,13 @@ fpaR::create_data_raw()
 
 dir <- "data-raw"
 
-sales <- readr::read_csv(file.path(dir,"sales.csv"),name_repair = janitor::make_clean_names,show_col_types = FALSE)
+sales <- readr::read_csv(file.path(dir,"sales.csv"),name_repair = janitor::make_clean_names,show_col_types = FALSE) |>
+    dplyr::mutate(
+        revenue=quantity*unit_price
+        ,cogs=quantity*unit_cost
+        ,margin=revenue-cogs
+        ,unit_margin=unit_price-unit_cost
+    )
 
 
 usethis::use_data(sales, overwrite = TRUE)