Share of vehicle listings for combinations of grouping variables, computed across all listing years and inventory types. Includes six pairwise combinations (powertrain by vehicle type, powertrain by price bin, vehicle type by powertrain, vehicle type by price bin, price bin by powertrain, and price bin by vehicle type) plus three singular time trends for powertrain, vehicle type, and price bin individually.
Usage
data(percent_listings)Format
A tibble with 8 variables:
| Variable | Description |
listing_year | Year of the vehicle listing (2018–2024) |
inventory_type | Inventory type: "New" or "Used" |
group_var | Name of the grouping variable: "powertrain", "vehicle_type", or "price_bin" |
group_level | Level of the grouping variable (e.g., "Gasoline", "Car", "$30k-$40k") |
category_var | Name of the category variable: "powertrain", "vehicle_type", or "price_bin"; NA for singular time trends |
category_level | Level of the category variable; NA for singular time trends |
n | Number of listings in this group-category combination |
p | Proportion of listings within the group (sums to 1 within each listing year, inventory type, and group level) |
Source
Computed from vehicle listings data from Marketcheck.
Examples
data(percent_listings)
head(percent_listings)
#> # A tibble: 6 × 8
#> listing_year inventory_type group_var group_level category_var category_level
#> <dbl> <chr> <chr> <chr> <chr> <chr>
#> 1 2018 New powertrain Battery El… vehicle_type Minivan
#> 2 2025 New powertrain Battery El… vehicle_type Minivan
#> 3 2024 New powertrain Battery El… vehicle_type Minivan
#> 4 2024 New powertrain Battery El… vehicle_type SUV
#> 5 2025 New powertrain Battery El… vehicle_type SUV
#> 6 2023 New powertrain Battery El… vehicle_type SUV
#> # ℹ 2 more variables: n <int>, p <dbl>