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Author: kalashsinghal

NAMESPACE

@@ -5,6 +5,9 @@ export(calculate_trs_descriptive_analysis_per_tr_benchmark)
 export(example_emission_ep_product_des_analysis)
 export(example_emission_product_co2_des_analysis)
 export(example_sector_ep_product_des_analysis)
+export(example_transition_risk_product_emission_cov)
+export(example_transition_risk_product_sector_cov)
+export(example_transition_risk_product_transition_risk_cov)
 export(example_transition_risk_product_trs_des_analysis)
 export(show_reduction_targets_for_tilt_subsectors_per_scenario_year)
 importFrom(dplyr,distinct)

R/example_data.R

@@ -12,6 +12,9 @@
 #' example_transition_risk_product_trs_des_analysis()
 #' example_emission_ep_product_des_analysis()
 #' example_sector_ep_product_des_analysis()
+#' example_transition_risk_product_emission_cov()
+#' example_transition_risk_product_sector_cov()
+#' example_transition_risk_product_transition_risk_cov()
 example_emission_product_co2_des_analysis <- function() {
   tribble(
   # styler: off
@@ -89,3 +92,61 @@ example_sector_ep_product_des_analysis <- function() {
     # styler: on
   )
 }
+
+#' @export
+#' @rdname example_emission_product_co2_des_analysis
+example_transition_risk_product_emission_cov <- function() {
+  tribble(
+    # styler: off
+    ~companies_id,    ~grouping_emission, ~cov_emission_rank,
+         "comp_1",                 "all",               10.0,
+         "comp_1",         "isic_4digit",               15.0,
+         "comp_1",      "tilt_subsector",               20.0,
+         "comp_1",                "unit",               25.0,
+         "comp_1",    "unit_isic_4digit",               30.0,
+         "comp_1", "unit_tilt_subsector",               35.0,
+         "comp_2",                 "all",               45.0,
+         "comp_2",         "isic_4digit",               50.0,
+         "comp_2",      "tilt_subsector",               55.0,
+         "comp_2",                "unit",               60.0,
+         "comp_2",    "unit_isic_4digit",               65.0,
+         "comp_2", "unit_tilt_subsector",               70.0
+    # styler: on
+  )
+}
+
+#' @export
+#' @rdname example_emission_product_co2_des_analysis
+example_transition_risk_product_sector_cov <- function() {
+  tribble(
+    # styler: off
+    ~companies_id,  ~scenario, ~year, ~cov_sector_target,
+         "comp_1", "1.5C RPS",  2030,               10.0,
+         "comp_1", "1.5C RPS",  2050,               15.0,
+         "comp_1",  "NZ 2050",  2030,               20.0,
+         "comp_1",  "NZ 2050",  2050,               25.0,
+         "comp_2", "1.5C RPS",  2030,               45.0,
+         "comp_2", "1.5C RPS",  2050,               50.0,
+         "comp_2",  "NZ 2050",  2030,               55.0,
+         "comp_2",  "NZ 2050",  2050,               60.0
+    # styler: on
+  )
+}
+
+#' @export
+#' @rdname example_emission_product_co2_des_analysis
+example_transition_risk_product_transition_risk_cov <- function() {
+  tribble(
+    # styler: off
+    ~companies_id,      ~grouping_transition_risk, ~cov_transition_risk,
+         "comp_1", "1.5C RPS_2030_tilt_subsector",                 10.0,
+         "comp_1", "1.5C RPS_2050_tilt_subsector",                 15.0,
+         "comp_1",  "NZ 2050_2030_tilt_subsector",                 20.0,
+         "comp_1",  "NZ 2050_2050_tilt_subsector",                 25.0,
+         "comp_2", "1.5C RPS_2030_tilt_subsector",                 45.0,
+         "comp_2", "1.5C RPS_2050_tilt_subsector",                 50.0,
+         "comp_2",  "NZ 2050_2030_tilt_subsector",                 55.0,
+         "comp_2",  "NZ 2050_2050_tilt_subsector",                 60.0
+    # styler: on
+  )
+}

man/example_emission_product_co2_des_analysis.Rd

@@ -12,7 +12,7 @@ knitr::opts_chunk$set(
 This article shows how to calculate the descriptive analysis on amount of 
 companies for emission and sector profile.
 
-```{r setup, warning=FALSE}
+```{r setup, warning=FALSE, echo = FALSE, message=FALSE}
 library(tiltDataAnalysis)
 library(dplyr)
 library(knitr)

vignettes/articles/descriptive-analysis-amount_of_companies.Rmd

@@ -12,7 +12,7 @@ knitr::opts_chunk$set(
 This article shows how to calculate the descriptive analysis of co2_footprint per
 benchmark using product-level output of Emissions profile indicator.
 
-```{r setup, warning=FALSE}
+```{r setup, warning=FALSE, echo = FALSE, message=FALSE}
 library(tiltDataAnalysis)
 library(tibble)
 

vignettes/articles/descriptive-analysis-co2_footprint_per_benchmark.Rmd

@@ -0,0 +1,91 @@
+---
+title: "Descriptive analysis of coefficient of variation"
+---
+
+```{r, include = FALSE}
+knitr::opts_chunk$set(
+  collapse = TRUE,
+  comment = "#>"
+)
+```
+
+This article shows how to calculate the descriptive analysis of coefficient of 
+variation for emission profile, sector profile, and transition risk profile.
+
+```{r setup, echo = FALSE, message=FALSE}
+library(tiltDataAnalysis)
+library(dplyr)
+library(knitr)
+options(readr.show_col_types = FALSE)
+```
+
+### Example company-level output of transition risk profile for `cov_emission_rank`
+
+```{r}
+emission_product_example <- example_transition_risk_product_emission_cov()
+kable(emission_product_example)
+```
+
+### Average `cov_emission_rank` per company for emission profile benchmarks
+
+```{r}
+avg_cov_emission_rank_per_benchmark <- emission_product_example |>
+  select(all_of(c("companies_id", "grouping_emission", "cov_emission_rank"))) |>
+  distinct() |>
+  mutate(sum_cov_emission_rank = sum(.data$cov_emission_rank, na.rm = TRUE), .by = "grouping_emission") |>
+  mutate(distinct_companies_per_benchmark = n_distinct(.data$companies_id, na.rm = TRUE), .by = "grouping_emission") |>
+  mutate(avg_cov_emission_rank = sum_cov_emission_rank/distinct_companies_per_benchmark) |>
+  select(-all_of(c("sum_cov_emission_rank", "distinct_companies_per_benchmark", "cov_emission_rank", "companies_id"))) |>
+  distinct()
+  
+kable(avg_cov_emission_rank_per_benchmark)
+```
+
+### Example company-level output of transition risk profile for `cov_sector_target`
+
+```{r}
+sector_product_example <- example_transition_risk_product_sector_cov()
+kable(sector_product_example)
+```
+
+### Average `cov_sector_target` per company for sector profile benchmarks
+
+```{r}
+avg_cov_sector_target_per_benchmark <- sector_product_example |>
+  select(all_of(c("companies_id", "scenario", "year", "cov_sector_target"))) |>
+  mutate(grouping_sector = paste(.data$scenario, .data$year, sep = "_")) |>
+  select(-all_of(c("scenario", "year"))) |>
+  distinct() |>
+  mutate(sum_cov_sector_target = sum(.data$cov_sector_target, na.rm = TRUE), .by = "grouping_sector") |>
+  mutate(distinct_companies_per_benchmark = n_distinct(.data$companies_id, na.rm = TRUE), .by = "grouping_sector") |>
+  mutate(avg_cov_sector_target = sum_cov_sector_target/distinct_companies_per_benchmark) |>
+  select(-all_of(c("sum_cov_sector_target", "distinct_companies_per_benchmark", "cov_sector_target", "companies_id"))) |>
+  distinct()
+  
+kable(avg_cov_sector_target_per_benchmark)
+```
+
+### Example company-level output of transition risk profile for `cov_transition_risk`
+
+```{r}
+transition_risk_product_example <- example_transition_risk_product_transition_risk_cov()
+kable(transition_risk_product_example)
+```
+
+### Average `cov_transition_risk` per company for transition risk profile benchmarks (only for tilt_subsector)
+
+```{r}
+avg_cov_transition_risk_per_benchmark <- transition_risk_product_example |>
+  select(all_of(c("companies_id", "grouping_transition_risk", "cov_transition_risk"))) |>
+  distinct() |>
+  filter(grouping_transition_risk %in% c("1.5C RPS_2030_tilt_subsector", "1.5C RPS_2050_tilt_subsector",
+                                         "NZ 2050_2030_tilt_subsector", "NZ 2050_2050_tilt_subsector")) |>
+  mutate(sum_cov_transition_risk = sum(.data$cov_transition_risk, na.rm = TRUE), .by = "grouping_transition_risk") |>
+  mutate(distinct_companies_per_benchmark = n_distinct(.data$companies_id, na.rm = TRUE), .by = "grouping_transition_risk") |>
+  mutate(avg_cov_transition_risk = sum_cov_transition_risk/distinct_companies_per_benchmark) |>
+  select(-all_of(c("sum_cov_transition_risk", "distinct_companies_per_benchmark", "cov_transition_risk", "companies_id"))) |>
+  distinct()
+  
+kable(avg_cov_transition_risk_per_benchmark)
+```
+

vignettes/articles/descriptive-analysis-coefficient_of_variation.Rmd

@@ -12,7 +12,7 @@ knitr::opts_chunk$set(
 This article shows how to calculate the descriptive analysis of companies'
 employees.
 
-```{r setup, warning=FALSE}
+```{r setup, warning=FALSE, echo = FALSE, message=FALSE}
 library(tiltDataAnalysis)
 library(dplyr)
 library(knitr)

vignettes/articles/descriptive-analysis-employees.Rmd

@@ -12,7 +12,7 @@ knitr::opts_chunk$set(
 This article shows how to calculate the descriptive analysis of products for 
 emission and sector profile.
 
-```{r setup, warning=FALSE}
+```{r setup, warning=FALSE, echo = FALSE, message=FALSE}
 library(dplyr)
 library(tiltDataAnalysis)
 library(knitr)

vignettes/articles/descriptive-analysis-products.Rmd

@@ -13,7 +13,7 @@ This article shows how to calculate the descriptive analysis of transition risk
 scores for all `tilt_subsectors` per scenario-year-tilt_subsector benchmark 
 using product-level output of Transition risk profile indicator.
 
-```{r setup, warning=FALSE}
+```{r setup, warning=FALSE, echo = FALSE, message=FALSE}
 library(tiltDataAnalysis)
 options(readr.show_col_types = FALSE)
 options(width = 5000)

vignettes/articles/descriptive-analysis-transition_risk_score_per_scenario_year_tilt_subsector.Rmd

@@ -12,7 +12,7 @@ knitr::opts_chunk$set(
 This article outlines how to show reduction targets for all `tilt_subsectors` per
 scenario-year benchmark using product-level output of Sector profile indicator.
 
-```{r setup, warning=FALSE}
+```{r setup, warning=FALSE, echo = FALSE, message=FALSE}
 library(tiltDataAnalysis)
 options(readr.show_col_types = FALSE)
 ```