Evolution of gas prices in Llinars del Vallès

Published

February 12, 2024

Use this R libraries:

library(httr2)
library(dplyr)
library(purrr)
library(tidyr)
library(stringr)
library(ggplot2)

theme_set(
  theme_bw() +
  theme(
    axis.title = element_blank()
  )
)

Define function to retrieve information:

get_gas <- function(filtro, args) {
  paste0(
    "https://sedeaplicaciones.minetur.gob.es",
    "/ServiciosRESTCarburantes/PreciosCarburantes/EstacionesTerrestresHist/",
    filtro, paste(args, collapse = "/")
  ) %>%
    request() %>%
    req_perform() %>%
    resp_body_json() %>%
    .[["ListaEESSPrecio"]] %>%
    map(\(x) as_tibble(list_flatten(x))) %>%
    bind_rows() %>%
    janitor::clean_names()
}

Retrieve yesterday’s gas prices in catalan provinces:

prov <- c("08", "43", "17", "25")

gCat <- map(prov, \(x) get_gas(
  filtro = "FiltroProvincia/",
  args = c(format(Sys.Date() - 1, "%d-%m-%Y"), x)
)) %>%
  bind_rows() %>%
  mutate(precio = as.numeric(gsub(",", ".", precio_gasolina_95_e5)))

Summary of gas stations and price statistics per province:¹

gCat %>%
  summarise(
    n = n(),
    mean = mean(precio, na.rm = TRUE) %>% round(3),
    median = median(precio, na.rm = TRUE) %>% round(3),
    sd = sd(precio, na.rm = TRUE) %>% round(3),
    .by = provincia
  )

# A tibble: 4 × 5
  provincia     n  mean median    sd
  <chr>     <int> <dbl>  <dbl> <dbl>
1 BARCELONA   799  1.48   1.51 0.116
2 TARRAGONA   235  1.48   1.53 0.114
3 GIRONA      263  1.49   1.53 0.094
4 LLEIDA      184  1.43   1.48 0.107

Prices from the largest providers in Catalonia, 2025:

gCat %>%
  filter(rotulo %in% (
    summarise(gCat, .by = rotulo, n = n()) %>%
      arrange(n) %>% pull(rotulo) %>% tail(10)
  )) %>%
  drop_na() %>%
  select(rotulo, precio) %>%
  ggplot(aes(rotulo, precio)) +
  geom_boxplot() +
  labs(
    title = "Gas prices in Catalonia, 2025",
    subtitle = "Euros per litre of gas 95 E5 (10 largest providers)"
  )

Narrow down geographical scope: Consider municipalities nearby Llinars del Vallès

muns <- gCat %>% 
  summarise(n = n(), m = round(mean(precio), 3), .by = c(municipio, id_municipio)) %>% 
  filter(str_detect(municipio, 
    "Llinars|Cardedeu|Vilamajor|Palautordera|Sant Celoni"
  ))

knitr::kable(muns, caption = "Average price and station count per municipality")

Average price and station count per municipality
municipio	id_municipio	n	m
Cardedeu	908	4	1.544
Llinars del Vallès	973	3	1.579
Sant Antoni de Vilamajor	1060	1	1.529
Sant Celoni	1065	4	1.524
Santa Maria de Palautordera	1123	3	1.517

Retrieve daily prices for Gasolina 95 - E5 at all locations within scope. Define request parameters:

# api end point
fil <- "FiltroMunicipioProducto/"

t <- Sys.time()
# parameters
anys <- 1/12
mun <- set_names(muns$id_municipio, muns$municipio)
prod <- set_names("01", "gas95-e5")
date <- format(Sys.Date() - 1:(anys*365), "%d-%m-%Y")
params <- expand_grid(date, mun, prod)

gas <- apply(params, 1, \(x) mutate(get_gas(filtro = fil, args = x), date = as.Date(x[1]))) %>% 
  bind_rows() %>%
  mutate(precio = as.numeric(gsub(",", ".", precio_producto)))
t <- Sys.time() - t

Evolution of average price per municipality:

summarise(gas, .by = c(municipio, date), price = mean(precio), desv = sd(precio)) %>% 
  ggplot(aes(x = date, y = price, colour = municipio)) +
  geom_line() +
  labs(colour = "Municipality", title = "Gas prive evolution, last 30 days")

Footnotes

Considering 95 gas - E5↩︎