Amounts of trash collected by each of the 4 trash wheels in Baltimore's harbor, marked by date. Includes total weight and volume, then estimates of counts of items by type. Values may be NA if counts of an item were not available for a trash wheel.
Format
A data frame with 1313 rows and 12 variables:
- name
Factor. Name of trash wheel.
- dumpster
Numeric. Dumpster number within the trash wheel.
- date
Date of counting.
- weight_tons
Numeric. Total weight of trash collected in tons.
- volume_cubic_yards
Numeric. Total volume of trash collected in cubic yards.
- plastic_bottles
Numeric. Estimated number of plastic bottles collected.
- polystyrene
Numeric. Estimated number of pieces of polystyrene collected.
- cigarette_butts
Numeric. Estimated number of cigarette butts collected.
- glass_bottles
Numeric. Estimated number of glass bottles collected.
- plastic_bags
Numeric. Estimated number of plastic bags collected.
- wrappers
Numeric. Estimated number of wrappers collected.
- sports_balls
Numeric. Estimated number of sports balls collected.
Source
Waterfront Partnership of Baltimore. (2026). Trash Interception. Mr. Trash Wheel. https://www.mrtrashwheel.com/trash-interception
Examples
head(trashwheel)
#> # A tibble: 6 × 12
#> name dumpster date weight_tons volume_cubic_yards plastic_bottles
#> <fct> <dbl> <date> <dbl> <dbl> <dbl>
#> 1 Mr. Trash … 1 2014-05-16 4.31 18 1450
#> 2 Mr. Trash … 2 2014-05-16 2.74 13 1120
#> 3 Mr. Trash … 3 2014-05-16 3.45 15 2450
#> 4 Mr. Trash … 4 2014-05-17 3.1 15 2380
#> 5 Mr. Trash … 5 2014-05-17 4.06 18 980
#> 6 Mr. Trash … 6 2014-05-20 2.71 13 1430
#> # ℹ 6 more variables: polystyrene <dbl>, cigarette_butts <dbl>,
#> # glass_bottles <dbl>, plastic_bags <dbl>, wrappers <dbl>, sports_balls <dbl>