In angiebouche/ESM_262_Assignment_5: Analyze Emissions of Various Fuel Types in Business Sectors (2010-2016)

knitr::opts_chunk$set(echo = TRUE)

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library(tidyverse)
library(testthat)
library(dplyr)
library(devtools)
library(roxygen2)
library(Assignment5)
ghg <- read_csv("GHG.csv")

# devtools::document() this will update the documentation
# after running that code, it should open the help page when the functions are called

Summarize: Average natural gas emissions by year

ng_emissions = ghg %>% 
  filter(Fuel_Type == "Natural Gas") %>% 
  select(Total_CO2_Emissions) %>% 
  summarize(mean = (sum(Total_CO2_Emissions)/7))

Summarize: Add up total emisisons by year

annual_emissions = ghg %>% 
  group_by(Year) %>% 
  summarize(sum_col = sum(Total_CO2_Emissions)) %>%  
  arrange(-Year) %>% 
  head(10)

Array:

emissions_year = array(1:40, dim=c(5,4,2), #fill array with numbers 1-40 FAKE DATA
                dimnames = list(c('Transportation', 'Electricity_Generation', 'Residential', 'Commercial',  'Industrial'),
              c('Diesel', 'Gasoline', 'Coal', 'Natural Gas'),
              c(2010,2016))) # add column names
              emissions_year 

#each ton is taxed $1,000 - econ cost for emissions for each sector 
cost = apply(emissions_year, c(1), sum)*1000

Impact without coal

  less_emissions = ghg%>%
    dplyr::filter(Fuel_Type != "Coal") %>%
    dplyr::select(Total_CO2_Emissions) %>%
    dplyr::summarize((sum(Total_CO2_Emissions)/10*.1))

Possible Tests

usethis::use_test()

source("R/add_total_emissions_year.R")
test_that("Data from 2019 is not included", {
data(ghg)
ghg_2019 <- ghg %>% 
dplyr::filter(Year == 2019)
expect_false(add_total_emissions_year(ghg_em_year = ghg_2019) > 0)
})


source("R/average_ng.R")
test_that("Average natural gas emissions are numerical", {
data(ghg)
expect_is(average_ng(ghg_data = ghg), "numeric")
})


source("R/average_ng.R")
test_that("Test that the average natural gas emissions in 2016 were 165.85", {
data(ghg)
ghg_2016 <- ghg %>% 
dplyr::filter(Year == 2016)
expect_true(average_ng(ghg_data = ghg_2016) > 165)
})

angiebouche/ESM_262_Assignment_5 documentation built on June 14, 2019, 3:25 p.m.