tiltToyData
The goal of tiltToyData is to provide toy datasets for TILT.
Installation
You can install the development version of tiltToyData like so:
# install.packages("devtools")
devtools::install_github("2DegreesInvesting/tiltToyData")Example
library(tiltToyData)
library(readr)
options(readr.show_col_types = FALSE)
toy_files()
#> [1] "emissions_profile_any_companies.csv.gz"
#> [2] "emissions_profile_products.csv.gz"
#> [3] "emissions_profile_products_ecoinvent.csv.gz"
#> [4] "emissions_profile_upstream_products.csv.gz"
#> [5] "emissions_profile_upstream_products_ecoinvent.csv.gz"
#> [6] "sector_profile_any_scenarios.csv.gz"
#> [7] "sector_profile_companies.csv.gz"
#> [8] "sector_profile_upstream_companies.csv.gz"
#> [9] "sector_profile_upstream_products.csv.gz"
read_csv(toy_emissions_profile_products())
#> # A tibble: 5 × 7
#> co2_footprint tilt_sector tilt_subsector unit isic_4digit
#> <dbl> <chr> <chr> <chr> <chr>
#> 1 176. Industry Other unit '2560'
#> 2 58.1 Industry Other unit '2560'
#> 3 4.95 Steel & Metals Steel kg '2870'
#> 4 12.5 Agriculture Agriculture kg '1780'
#> 5 2.07 Industry Other kg '2679'
#> # ℹ 2 more variables: activity_uuid_product_uuid <chr>, ei_activity_name <chr>
toy_files() |>
lapply(\(x) read_csv(toy_path(x))) |>
setNames(toy_files())
#> $emissions_profile_any_companies.csv.gz
#> # A tibble: 76 × 7
#> activity_uuid_product_uuid clustered companies_id country ei_activity_name
#> <chr> <chr> <chr> <chr> <chr>
#> 1 76269c17-78d6-420b-991a-aa38… tent soot_asianp… germany market for shed…
#> 2 76269c17-78d6-420b-991a-aa38… table hi… frightening… spain market for shed…
#> 3 76269c17-78d6-420b-991a-aa38… surface … hyperbrutal… germany market for deep…
#> 4 76269c17-78d6-420b-991a-aa38… surface … hyperbrutal… germany market for deep…
#> 5 76269c17-78d6-420b-991a-aa38… tent flexible_do… austria market for shed…
#> 6 76269c17-78d6-420b-991a-aa38… tent paramilitar… germany market for shed…
#> 7 76269c17-78d6-420b-991a-aa38… open spa… level_meado… france market for shed…
#> 8 bf94b5a7-b7a2-46d1-bb95-84bc… tent heartrendin… germany market for shed…
#> 9 76269c17-78d6-420b-991a-aa38… tent traumatopho… germany market for shed…
#> 10 76269c17-78d6-420b-991a-aa38… tent preliterary… germany market for shed…
#> # ℹ 66 more rows
#> # ℹ 2 more variables: main_activity <chr>, unit <chr>
#>
#> $emissions_profile_products.csv.gz
#> # A tibble: 5 × 7
#> co2_footprint tilt_sector tilt_subsector unit isic_4digit
#> <dbl> <chr> <chr> <chr> <chr>
#> 1 176. Industry Other unit '2560'
#> 2 58.1 Industry Other unit '2560'
#> 3 4.95 Steel & Metals Steel kg '2870'
#> 4 12.5 Agriculture Agriculture kg '1780'
#> 5 2.07 Industry Other kg '2679'
#> # ℹ 2 more variables: activity_uuid_product_uuid <chr>, ei_activity_name <chr>
#>
#> $emissions_profile_products_ecoinvent.csv.gz
#> # A tibble: 18 × 8
#> activity_uuid_product_uuid co2_footprint ei_activity_name ei_geography
#> <chr> <dbl> <chr> <chr>
#> 1 833caa78-30df-4374-900f-7f88ab44… 14.1 iron-nickel-chr… RER
#> 2 bf94b5a7-b7a2-46d1-bb95-84bc560b… 0.419 market for deep… GLO
#> 3 bf94b5a7-b7a2-46d1-bb95-84bc560b… 481. market for shed… GLO
#> 4 833caa78-30df-4374-900f-7f88ab44… 9.47 iron-nickel-chr… RER
#> 5 bf94b5a7-b7a2-46d1-bb95-84bc560b… 0.648 market for deep… GLO
#> 6 bf94b5a7-b7a2-46d1-bb95-84bc560b… 276. market for shed… GLO
#> 7 833caa78-30df-4374-900f-7f88ab44… 13.6 iron-nickel-chr… RER
#> 8 76269c17-78d6-420b-991a-aa38c51b… 0.405 market for deep… GLO
#> 9 76269c17-78d6-420b-991a-aa38c51b… 447. market for shed… GLO
#> 10 833caa78-30df-4374-900f-7f88ab44… 14.7 iron-nickel-chr… RER
#> 11 833caa78-30df-4374-900f-7f88ab44… 0.390 market for deep… GLO
#> 12 bf94b5a7-b7a2-46d1-bb95-84bc560b… 442. market for shed… GLO
#> 13 76269c17-78d6-420b-991a-aa38c51b… 14.1 iron-nickel-chr… RER
#> 14 76269c17-78d6-420b-991a-aa38c51b… 0.884 market for deep… GLO
#> 15 76269c17-78d6-420b-991a-aa38c51b… 321. market for shed… GLO
#> 16 833caa78-30df-4374-900f-7f88ab44… 12.7 iron-nickel-chr… RER
#> 17 76269c17-78d6-420b-991a-aa38c51b… 0.675 market for deep… GLO
#> 18 bf94b5a7-b7a2-46d1-bb95-84bc560b… 435. market for shed… GLO
#> # ℹ 4 more variables: isic_4digit <chr>, tilt_sector <chr>,
#> # tilt_subsector <chr>, unit <chr>
#>
#> $emissions_profile_upstream_products.csv.gz
#> # A tibble: 33 × 7
#> input_co2_footprint input_tilt_sector input_tilt_subsector input_unit
#> <dbl> <chr> <chr> <chr>
#> 1 7.07e+0 Inudstry Other kg
#> 2 3.99e+1 Inudstry Other kwh
#> 3 5.12e-1 Inudstry Other kg
#> 4 1.24e+0 Inudstry Other kg
#> 5 2.12e+1 Inudstry Other kwh
#> 6 1.24e-9 Inudstry Other kg
#> 7 7 e-9 Inudstry Other kg
#> 8 1.04e+0 Inudstry Other kg
#> 9 1.12e+0 Inudstry Other kg
#> 10 3.51e+0 Inudstry Other kg
#> # ℹ 23 more rows
#> # ℹ 3 more variables: input_isic_4digit <chr>,
#> # input_activity_uuid_product_uuid <chr>, activity_uuid_product_uuid <chr>
#>
#> $emissions_profile_upstream_products_ecoinvent.csv.gz
#> # A tibble: 96 × 9
#> activity_uuid_product_uuid ei_geography input_activity_uuid_produ…¹
#> <chr> <chr> <chr>
#> 1 bf94b5a7-b7a2-46d1-bb95-84bc560b12fb RER bdc93cd8-00b4-5b3e-993e-b7…
#> 2 bf94b5a7-b7a2-46d1-bb95-84bc560b12fb RER fdb1f848-173f-5fe1-96a2-58…
#> 3 76269c17-78d6-420b-991a-aa38c51b45b7 RER 95fcd1bb-4dc6-516a-a3b2-30…
#> 4 bf94b5a7-b7a2-46d1-bb95-84bc560b12fb RER daef2f9a-4108-52ae-90a7-fe…
#> 5 bf94b5a7-b7a2-46d1-bb95-84bc560b12fb RER 3b190359-a32e-5294-af63-98…
#> 6 833caa78-30df-4374-900f-7f88ab44075b RER 2c92cdcd-29df-53ba-a209-77…
#> 7 bf94b5a7-b7a2-46d1-bb95-84bc560b12fb RER 9392c694-12a6-5cd7-a421-d4…
#> 8 bf94b5a7-b7a2-46d1-bb95-84bc560b12fb RER c18c6cc9-4a26-5c47-9ea9-86…
#> 9 bf94b5a7-b7a2-46d1-bb95-84bc560b12fb RER c4ec0b1e-2a3b-5700-871c-2a…
#> 10 833caa78-30df-4374-900f-7f88ab44075b RER 7361f7fb-5cf2-598c-823a-a4…
#> # ℹ 86 more rows
#> # ℹ abbreviated name: ¹input_activity_uuid_product_uuid
#> # ℹ 6 more variables: input_co2_footprint <dbl>, input_isic_4digit <chr>,
#> # input_reference_product_name <chr>, input_tilt_sector <chr>,
#> # input_tilt_subsector <chr>, input_unit <chr>
#>
#> $sector_profile_any_scenarios.csv.gz
#> # A tibble: 388 × 8
#> scenario region sector subsector year value reductions type
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr>
#> 1 1.5c rps world power <NA> 2030 5359. 0.58 ipr
#> 2 1.5c rps world power <NA> 2050 -807. 1.06 ipr
#> 3 1.5c rps world buildings <NA> 2030 2454. 0.18 ipr
#> 4 1.5c rps world buildings <NA> 2050 61.3 0.98 ipr
#> 5 1.5c rps world industry iron and steel 2030 1872. 0.23 ipr
#> 6 1.5c rps world industry iron and steel 2050 88.3 0.96 ipr
#> 7 1.5c rps world industry non-metallic minerals 2030 2641. 0.13 ipr
#> 8 1.5c rps world industry non-metallic minerals 2050 592. 0.8 ipr
#> 9 1.5c rps world industry chemicals 2030 1218. 0.12 ipr
#> 10 1.5c rps world industry chemicals 2050 102. 0.93 ipr
#> # ℹ 378 more rows
#>
#> $sector_profile_companies.csv.gz
#> # A tibble: 28 × 10
#> companies_id company_name clustered activity_uuid_produc…¹ isic_4digit
#> <chr> <chr> <chr> <chr> <chr>
#> 1 fleischerei-stiefs… fleischerei… steel 0faa7ecb-fef2-5117-89… '2410'
#> 2 fleischerei-stiefs… fleischerei… steel 0faa7ecb-fef2-5117-89… '2410'
#> 3 pecheries-basques_… pecheries-b… nitrogen 03fbf989-9a1a-5e3d-a5… '2029'
#> 4 pecheries-basques_… pecheries-b… nitrogen 03fbf989-9a1a-5e3d-a5… '2029'
#> 5 hoche-butter-gmbh_… hoche-butte… waste <NA> <NA>
#> 6 hoche-butter-gmbh_… hoche-butte… waste <NA> <NA>
#> 7 hoche-butter-gmbh_… hoche-butte… car <NA> <NA>
#> 8 hoche-butter-gmbh_… hoche-butte… car <NA> <NA>
#> 9 hoche-butter-gmbh_… hoche-butte… heater <NA> <NA>
#> 10 hoche-butter-gmbh_… hoche-butte… heater <NA> <NA>
#> # ℹ 18 more rows
#> # ℹ abbreviated name: ¹activity_uuid_product_uuid
#> # ℹ 5 more variables: tilt_sector <chr>, tilt_subsector <chr>, type <chr>,
#> # sector <chr>, subsector <chr>
#>
#> $sector_profile_upstream_companies.csv.gz
#> # A tibble: 8 × 6
#> companies_id clustered activity_uuid_produc…¹ ei_activity_name unit
#> <chr> <chr> <chr> <chr> <chr>
#> 1 fleischerei-stiefsohn… stove 0a242b09-772a-5edf-8e… cookstove produ… unit
#> 2 fleischerei-stiefsohn… oven be06d25c-73dc-55fb-96… microwave oven … unit
#> 3 pecheries-basques_fra… steel 977d997e-c257-5033-ba… market for stee… kg
#> 4 hoche-butter-gmbh_deu… aged che… ebb8475e-ff57-5e4e-93… cheese producti… kg
#> 5 vicquelin-espaces-ver… aged che… ebb8475e-ff57-5e4e-93… cheese producti… kg
#> 6 bst-procontrol-gmbh_0… cheese ebb8475e-ff57-5e4e-93… market for chee… kg
#> 7 leider-gmbh_000000050… cream 2f7b77a7-1556-5c1b-b0… market for seal… kg
#> 8 cheries-baqu_neu31654… rubber 2f7b77a7-1556-5c1b-b0… seal production… kg
#> # ℹ abbreviated name: ¹activity_uuid_product_uuid
#> # ℹ 1 more variable: tilt_sector <chr>
#>
#> $sector_profile_upstream_products.csv.gz
#> # A tibble: 74 × 10
#> activity_uuid_product_uuid input_activity_uuid_…¹ input_reference_prod…²
#> <chr> <chr> <chr>
#> 1 0a242b09-772a-5edf-8e82-9cb4ba… 5de8c337-dea9-5c1f-9d… biowaste
#> 2 0a242b09-772a-5edf-8e82-9cb4ba… 5de8c337-dea9-5c1f-9d… biowaste
#> 3 0a242b09-772a-5edf-8e82-9cb4ba… 1aeb18b9-8355-560f-82… chemical, inorganic
#> 4 0a242b09-772a-5edf-8e82-9cb4ba… 1aeb18b9-8355-560f-82… chemical, inorganic
#> 5 0a242b09-772a-5edf-8e82-9cb4ba… 22704506-7707-5ae7-99… chemical, organic
#> 6 0a242b09-772a-5edf-8e82-9cb4ba… 22704506-7707-5ae7-99… chemical, organic
#> 7 0a242b09-772a-5edf-8e82-9cb4ba… 92078219-1ed3-5215-9f… cow milk
#> 8 0a242b09-772a-5edf-8e82-9cb4ba… 92078219-1ed3-5215-9f… cow milk
#> 9 0a242b09-772a-5edf-8e82-9cb4ba… 9d483329-b09a-5513-b1… cream, from cow milk
#> 10 0a242b09-772a-5edf-8e82-9cb4ba… 9d483329-b09a-5513-b1… cream, from cow milk
#> # ℹ 64 more rows
#> # ℹ abbreviated names: ¹input_activity_uuid_product_uuid,
#> # ²input_reference_product_name
#> # ℹ 7 more variables: input_unit <chr>, input_isic_4digit <chr>,
#> # input_tilt_sector <chr>, input_tilt_subsector <chr>, type <chr>,
#> # sector <chr>, subsector <chr>