Takeout orders from an Indian restaurant. A dataset containing the total quantity of each dish ordered, as well as the dish's price and status as vegetarian or meat.
name_and_quant.RdTakeout orders from an Indian restaurant.
A dataset containing the total quantity of each dish ordered, as well as the dish's price and status as vegetarian or meat.
Format
A dataframe with 238 rows and 5 variables:
- Item.Name
Name of the dish
- Total.Quantity
Number of times the dish was ordered
- Product.Price
Price of the dish
- Prop.of.Total
Proportion of all orders
- Meat.Veg
Whether the dish is vegetarian (Veg) or not (Meat)
Examples
pillar::glimpse(name_and_quant)
#> Rows: 238
#> Columns: 5
#> $ Item.Name <chr> "Aloo Chaat", "Aloo Gobi", "Aloo Methi", "Baingan Hari …
#> $ Total.Quantity <int> 316, 620, 44, 199, 45, 18, 23, 109, 73, 247, 524, 211, …
#> $ Product.Price <dbl> 4.950000, 5.950000, 5.950000, 5.950000, 12.950000, 12.9…
#> $ Prop.of.Total <dbl> 0.0034275921, 0.0067250225, 0.0004772597, 0.0021585153,…
#> $ Meat.Veg <chr> "Veg", "Veg", "Veg", "Veg", "Meat", "Meat", "Meat", "Me…
name_and_quant |> dplyr::group_by(Meat.Veg) |>
dplyr::summarise(Num.Dishes.Sold = sum(Total.Quantity),
Total.Revenue = sum(Total.Quantity * Product.Price))
#> # A tibble: 2 × 3
#> Meat.Veg Num.Dishes.Sold Total.Revenue
#> <chr> <int> <dbl>
#> 1 Meat 23916 210574.
#> 2 Veg 68277 230660.