added example data

.gitignore

@@ -6,3 +6,4 @@ inst/doc
 data-raw/*.csv
 node_modules
 docs
+data-raw/inputs/

R/data.R

@@ -58,3 +58,34 @@
 #'   }
 #' @source Wikipedia (\url{https://fr.wikipedia.org/wiki/Climat_de_Paris})
 "climate_paris"
+
+
+#' @title eco2mix data
+#'
+#' @description The dataset contains data about electricity consumption and production in France between 2012 and 2022.
+#'
+#' @format A data frame with 3,033 observations and 3 variables.
+#'
+#' @source Rte (Réseau et transport d'électricité) (\url{https://www.rte-france.com/eco2mix/} and \url{https://opendata.reseaux-energies.fr/})
+"eco2mix"
+
+
+#' @title Temperature data
+#'
+#' @description The dataset contains data about temperatures in France between 2018 and 2022.
+#'
+#' @format A data frame with 365 observations and 6 variables.
+#'
+#' @source Enedis (\url{https://data.enedis.fr/explore/dataset/donnees-de-temperature-et-de-pseudo-rayonnement/})
+"temperatures"
+
+
+#' @title Life expectancy  data
+#'
+#' @description The dataset contains data about life expectancy in 1972 and 2007 for 10 countries.
+#'
+#' @format A data frame with 10 observations and 4 variables.
+#'
+#' @source gapminder package (\url{https://jennybc.github.io/gapminder/} and \url{https://www.gapminder.org/data/})
+"life_expec"
+

data-raw/eco2mix.R

@@ -0,0 +1,131 @@
+#  ------------------------------------------------------------------------
+#
+# eCO2mix data
+# https://www.rte-france.com/eco2mix
+#
+#  ------------------------------------------------------------------------
+
+
+# Packages ----------------------------------------------------------------
+
+library(data.table)
+library(fasttime)
+
+
+complete <- function(data, vars, fill = list()) {
+  data <- data[do.call(CJ, c(
+    lapply(
+      X = mget(vars),
+      FUN = function(var) {
+        if (inherits(var, "factor")) {
+          if (anyNA(var)) {
+            factor(c(levels(var), NA_character_), levels = levels(var), ordered = is.ordered(var))
+          } else {
+            factor(levels(var), levels = levels(var), ordered = is.ordered(var))
+          }
+        } else {
+          unique(var)
+        }
+      }
+    ),
+    list(sorted = FALSE)
+  )), on = vars]
+  if (length(fill) > 0 && all(nzchar(names(fill)))) {
+    for (fillvar in names(fill)) {
+      data[is.na(get(fillvar)), (fillvar) := fill[[fillvar]]]
+    }
+  }
+  data[]
+}
+
+
+
+# Download data -----------------------------------------------------------
+
+# Source: https://odre.opendatasoft.com/explore/dataset/eco2mix-national-cons-def/
+# and https://odre.opendatasoft.com/explore/dataset/eco2mix-national-tr
+
+
+# Read & transform data ---------------------------------------------------
+
+# eco2mix <- fread(file = "data-raw/inputs/eco2mix-national-cons-def.csv")
+# eco2mix <- eco2mix[, c(5, 6, 9:17)]
+# setnames(eco2mix, c("datetime", "consumption", "fuel", "coal", "gas", "nuclear", "wind", "solar", "hydraulic", "pumping", "bioenergies"))
+
+eco2mix_tr <- fread(file = "data-raw/inputs/eco2mix-national-tr.csv")
+eco2mix_tr <- eco2mix_tr[, c(5, 6, 9:17)]
+setnames(eco2mix_tr, c("datetime", "consumption", "fuel", "coal", "gas", "nuclear", "wind", "solar", "hydraulic", "pumping", "bioenergies"))
+
+eco2mix <- copy(eco2mix_tr)
+# eco2mix <- rbind(eco2mix, eco2mix_tr)
+
+eco2mix <- eco2mix[!is.na(consumption)]
+eco2mix[, consumption := NULL]
+# eco2mix[, date := as.Date(format(datetime, format = "%Y-%m-%d"))]
+# eco2mix[, datetime := NULL]
+# setcolorder(eco2mix, "date")
+eco2mix <- eco2mix[minute(datetime) != 15]
+eco2mix <- eco2mix[minute(datetime) != 45]
+eco2mix <- eco2mix[datetime >= (max(datetime) - 24*60*60*7)]
+eco2mix <- melt(
+  data = eco2mix, 
+  id.vars = 1, 
+  variable.name = "source",
+  value.name = "production", 
+  na.rm = TRUE, 
+  variable.factor = FALSE
+)
+eco2mix <- eco2mix[, list(production = round(mean(production))), by = list(datetime, source)]
+eco2mix[, source := factor(
+  x = source,
+  levels = c("pumping", "wind", "solar", "nuclear", "hydraulic", "gas", "coal", "fuel", "bioenergies"),
+  ordered = TRUE
+)]
+eco2mix <- complete(eco2mix, c("datetime", "source"), list(production = 0))
+setorder(eco2mix, source, datetime)
+
+eco2mix[]
+
+
+# Use data ----------------------------------------------------------------
+
+setDF(eco2mix)
+usethis::use_data(eco2mix, internal = FALSE, overwrite = TRUE, compress = "xz")
+
+
+
+
+
+# Test example ------------------------------------------------------------
+
+apex(eco2mix[source == "consumption"], aes(date, production), type = "line")
+
+# data("eco2mix", package = "apexcharter")
+apex(eco2mix, aes(datetime, production, fill = source), type = "area") %>% 
+  ax_chart(animations = list(enabled = FALSE), stacked = TRUE) %>% 
+  ax_stroke(width = 1) %>% 
+  ax_fill(opacity = 1, type = "solid") %>% 
+  ax_tooltip(x = list(format = "dd MMM, HH:mm")) %>% 
+  ax_yaxis(labels = list(formatter = format_num("~", suffix = "MW"))) %>% 
+  ax_colors_manual(
+    list(
+      "bioenergies" = "#156956",
+      "fuel" = "#80549f",
+      "coal" = "#a68832",
+      "solar" = "#d66b0d",
+      "gas" = "#f20809",
+      "wind" = "#72cbb7",
+      "hydraulic" = "#2672b0",
+      "nuclear" = "#e4a701",
+      "pumping" = "#0e4269"
+    )
+  ) %>% 
+  ax_labs(
+    title = "Electricity generation by sector in France",
+    subtitle = "Data from \u00e9CO\u2082mix"
+  )
+
+
+
+
+

data-raw/life_expectancy.R

@@ -0,0 +1,65 @@
+
+
+# Package -----------------------------------------------------------------
+
+library(data.table)
+library(gapminder)
+
+
+
+# Data --------------------------------------------------------------------
+
+life_expec <- as.data.table(gapminder::gapminder)
+life_expec <- life_expec[year %in% c(1972, 2007), list(country, year, lifeExp)]
+
+# life_expec <- life_expec[country %in% sample(unique(country), 10)]
+life_expec <- life_expec[country %in% c("Botswana", "Ghana", "Iran", "Liberia", "Malaysia", "Mexico", 
+                                        "Nigeria", "Pakistan", "Philippines", "Zambia")]
+life_expec <- dcast(life_expec, country ~ year, value.var = "lifeExp")
+life_expec[, type := fifelse(`1972` > `2007`, "decreased", "increased")]
+
+
+
+# Use data ----------------------------------------------------------------
+
+setDF(life_expec)
+usethis::use_data(life_expec, internal = FALSE, overwrite = TRUE, compress = "xz")
+
+
+
+
+
+# Test example ------------------------------------------------------------
+
+
+pkgload::load_all()
+
+apex(life_expec, aes(country, x = `1972`, xend = `2007`), type = "dumbbell") %>% 
+  ax_plotOptions(
+    bar = bar_opts(
+      dumbbellColors = list(list("#3d85c6", "#fb6003"))
+    )
+  ) %>% 
+  ax_colors("#BABABA") %>% 
+  ax_labs(
+    title = "Life expectancy : 1972 vs. 2007",
+    subtitle = "Data from Gapminder dataset",
+    x = "Life expectancy at birth, in years"
+  )
+
+
+
+apex(life_expec, aes(country, x = `1972`, xend = `2007`, group = type), type = "dumbbell") %>% 
+  ax_xaxis(type = "category", categories = unique(life_expec$country)) %>%
+  ax_plotOptions(
+    bar = bar_opts(
+      dumbbellColors = list(list("#3d85c6", "#fb6003"), list("#3d85c6", "#fb6003"))
+    )
+  ) %>% 
+  ax_colors(c("#3d85c6", "#fb6003")) %>% 
+  ax_labs(
+    title = "Life expectancy : 1972 vs. 2007",
+    subtitle = "Data from Gapminder dataset",
+    x = "Life expectancy at birth, in years"
+  )
+

data-raw/temperature.R

@@ -0,0 +1,63 @@
+#  ------------------------------------------------------------------------
+#
+# temperature data for France
+# https://data.enedis.fr/explore/dataset/donnees-de-temperature-et-de-pseudo-rayonnement
+#
+#  ------------------------------------------------------------------------
+
+
+# Packages ----------------------------------------------------------------
+
+library(data.table)
+library(fasttime)
+
+
+# Data --------------------------------------------------------------------
+
+temperatures <- fread(file = "data-raw/inputs/donnees-de-temperature-et-de-pseudo-rayonnement.csv")
+temperatures <- temperatures[, c(6, 7, 8, 2)]
+setnames(temperatures, c("year", "month", "day", "temperature"))
+temperatures <- temperatures[year > 2017]
+temperatures <- temperatures[, list(temperature = round(mean(temperature, na.rm = TRUE), 1)), by = c("year", "month", "day")]
+temperatures <- dcast(data = temperatures, formula = month + day ~ year, value.var = "temperature")
+temperatures <- temperatures[!(month == 2 & day == 29)]
+
+temperatures[, low := do.call(pmin, c(as.list(.SD), na.rm = TRUE)), .SDcols = as.character(2018:2021)]
+temperatures[, high := do.call(pmax, c(as.list(.SD), na.rm = TRUE)), .SDcols = as.character(2018:2021)]
+temperatures[, average := rowMeans(.SD, na.rm = TRUE), .SDcols = as.character(2018:2021)]
+temperatures[, (as.character(2018:2021)) := NULL]
+# setnames(temperatures, "2022", "temperature")
+
+temperatures[, date := as.Date("2022-01-01") + (seq_len(.N) - 1)]
+temperatures[, (c("month", "day")) := NULL]
+setcolorder(temperatures, "date")
+
+temperatures[]
+
+
+# Save --------------------------------------------------------------------
+
+setDF(temperatures)
+usethis::use_data(temperatures, internal = FALSE, overwrite = TRUE, compress = "xz")
+
+
+
+# Test example ------------------------------------------------------------
+
+
+pkgload::load_all()
+
+apex(temperatures, aes(x = date, ymin = low, ymax = high), type = "rangeArea", serie_name = "Low/High (2018-2021)") %>% 
+  add_line(aes(date, `2023`)) %>% 
+  ax_chart(animations = list(enabled = FALSE)) %>% 
+  ax_yaxis(tickAmount = 7, labels = list(formatter = format_num("~", suffix = "°C"))) %>% 
+  ax_colors(c("#8485854D", "#FF0000")) %>%
+  ax_stroke(width = c(1, 2)) %>% 
+  ax_fill(opacity = 1, type = "solid") %>% 
+  ax_labs(
+    title = "Temperatures in 2023 with range from 2018 to 2021",
+    subtitle = "Data from ENEDIS"
+  )
+
+
+

man/eco2mix.Rd

@@ -0,0 +1,19 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/data.R
+\docType{data}
+\name{eco2mix}
+\alias{eco2mix}
+\title{eco2mix data}
+\format{
+A data frame with 3,033 observations and 3 variables.
+}
+\source{
+Rte (Réseau et transport d'électricité) (\url{https://www.rte-france.com/eco2mix/} and \url{https://opendata.reseaux-energies.fr/})
+}
+\usage{
+eco2mix
+}
+\description{
+The dataset contains data about electricity consumption and production in France between 2012 and 2022.
+}
+\keyword{datasets}

man/life_expec.Rd

@@ -0,0 +1,19 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/data.R
+\docType{data}
+\name{life_expec}
+\alias{life_expec}
+\title{Life expectancy  data}
+\format{
+A data frame with 10 observations and 4 variables.
+}
+\source{
+gapminder package (\url{https://jennybc.github.io/gapminder/} and \url{https://www.gapminder.org/data/})
+}
+\usage{
+life_expec
+}
+\description{
+The dataset contains data about life expectancy in 1972 and 2007 for 10 countries.
+}
+\keyword{datasets}

man/temperatures.Rd

@@ -0,0 +1,19 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/data.R
+\docType{data}
+\name{temperatures}
+\alias{temperatures}
+\title{Temperature data}
+\format{
+A data frame with 365 observations and 6 variables.
+}
+\source{
+Enedis (\url{https://data.enedis.fr/explore/dataset/donnees-de-temperature-et-de-pseudo-rayonnement/})
+}
+\usage{
+temperatures
+}
+\description{
+The dataset contains data about temperatures in France between 2018 and 2022.
+}
+\keyword{datasets}