Setup

library(RCurl); library(knitr); library(jsonlite); library(tidyverse); library(magrittr)


gm_names <- c("biomass", "coal", "imports", "gas", "nuclear", "other", "hydro", "solar", "wind")

date_fixer <- function(v) {
  strptime(x = v, format = "%Y-%m-%dT%H:%MZ")
  }

genmix_api <- function(fromdate, todate){
fromdate <- as.Date(fromdate); todate <- as.Date(todate);

datelist <- seq.Date(fromdate, to = todate, by = "1 day")

gen_mix <- data.frame(matrix(nrow = 0, ncol = 4)) %>% 
  set_colnames(c("data.from", "data.to", "data.generationmix.fuel", "data.generationmix.perc"))

for (i in 1:length(datelist)){
  
if(fromdate < as.Date("2017-09-12")) {
  cat("\n\n", "Please select a from-date of 2017-09-12 or later", "\n\n"); break
  }
df_json <- RCurl::basicTextGatherer()

df_json$reset() # For caution

paste0("https://api.carbonintensity.org.uk/generation/", datelist[i], "T00:00Z/", datelist[i], "T23:59Z") %>%
RCurl::curlPerform(url = .,  writefunction = df_json$update)

data_response <- df_json$value() %>%  
  parse_json(simplifyVector = TRUE) %>% 
  as.data.frame()

data_response$info <- NULL

gen_mix  <- rbind(gen_mix, data_response)

} # close the loop

data.from <- gen_mix$data.from %>%
  date_fixer()

data.to <- gen_mix$data.to %>% 
  date_fixer()

gm_percentages <- gen_mix[[3]] %>% 
  as.data.frame() %>%
  t() %>% 
  set_colnames(gm_names)  %>% 
  as.data.frame() %>% 
  filter(biomass != "biomass")

 data.frame(data.from, data.to, gm_percentages) 


} # close the function

Pull

gm_data <- genmix_api(Sys.Date() - 30, todate = Sys.Date() - 1) 
gm_data %>% 
  head() %>% 
  kable(caption = "Generation Mix")
Generation Mix
data.from data.to biomass coal imports gas nuclear other hydro solar wind
2019-11-08 23:30:00 2019-11-09 00:00:00 7.6 1.4 13.0 34.0 24.1 0.4 0.9 0.0 18.6
2019-11-09 00:00:00 2019-11-09 00:30:00 7.7 1.5 12.0 33.1 24.5 0.4 1.0 0.0 19.8
2019-11-09 00:30:00 2019-11-09 01:00:00 7.6 1.4 11.9 33.9 24.2 0.4 0.9 0.0 19.7
2019-11-09 01:00:00 2019-11-09 01:30:00 7.7 1.4 11.8 33.6 24.4 0.4 1.0 0.0 19.7
2019-11-09 01:30:00 2019-11-09 02:00:00 7.8 1.5 12.1 32.4 24.9 0.4 1.0 0.0 19.9
2019-11-09 02:00:00 2019-11-09 02:30:00 7.9 1.5 11.9 31.0 24.9 0.4 1.0 0.0 21.4

Wrangle

gm_data_longer <- gm_data %>%
  pivot_longer(
    cols = 3:11,
    names_to = "gen_type",
    values_to = "mix"
    ) %>% 
  mutate(mix = mix %>% 
           as.character() %>% 
           as.numeric())

Plot

(Code generated using the esquisse package)

 gm_data_longer %<>%
  filter(data.from >= "2019-11-30 23:30:00" & data.from <= "2019-12-08 23:00:00") 

 ggplot(gm_data_longer) +
 aes(x = data.from, y = mix, fill = gen_type) +
 geom_area(size = 1L) +
 scale_fill_viridis_d(option = "viridis") +
 labs(
   x = "Date",
   y = "Mix %", 
   title = "Generation Mix UK", 
   subtitle = "Source: National Grid ESO - https://carbon-intensity.github.io"
   ) +
     theme_bw() +
 theme(legend.position = "bottom")

 ggplot(gm_data_longer) +
  aes(x = data.from, y = gen_type, fill = mix) +
  geom_tile(size = 1L) +
  scale_fill_distiller(palette = "RdYlGn") +
  labs(
    x = "Date", 
    y = "Mix", 
    title = "Generation Mix", 
    subtitle = "Weird Heatmap Thing!",
    fill = "Mix %"
    ) +
  theme_minimal() +
 theme(
   legend.position = "bottom", 
   legend.title = element_text(vjust = 0.5)
   )