Energy

Energy 
url <- paste0("https://bank.stat.gl/api/v1/", language, "/Greenland/EN/EN20/ENX1ACT.px")

ENX1ACT_raw <- 
  url |> 
  statgl_fetch(
    type      = 0,
    product   = px_all(),
    use       = 0,
    time      = px_top(5),
    .col_code = T
  ) |> 
  as_tibble()

ENX1ACT <- 
  ENX1ACT_raw |> 
  unite(combi, use, type, sep = " ") |> 
  mutate(product = product |> fct_inorder()) |> 
  spread(time, value)

ENX1ACT |> 
  select(-1) |> 
  rename(" " = 1) |> 
  statgl_table() |> 
  row_spec(1, bold = T) |> 
  add_footnote(ENX1ACT_raw[[1]][1], notation = "symbol")
2018 2019 2020 2021 2022
Total 8.885 8.998 8.827 9.258 10.002
Gas oil 5.266 5.086 5.463 6.035 6.494
Gasoline 730 820 815 856 843
Kerosene / Jet Fuel 817 850 468 561 764
Diesel Fuel Arctic 189 170 170 170 162
LPG 3 3 3 3 3
Aviation Gasoline 1 1 0 0 1
Fueloil 302 515 282 1 0
Wasteoil 9 9 9 9 9
Waste heat 98 110 103 102 88
Hydropower 1.469 1.434 1.513 1.521 1.639
* Actual energy consumption


See the table in our Statbank: ENX1ACT

url <- paste0("https://bank.stat.gl/api/v1/", language, "/Greenland/EN/EN20/ENX2CO2.px")

ENX2CO2_raw <- 
  url |> 
  statgl_fetch(
    type      = 0,
    gas       = px_all(),
    time      = px_top(5),
    .col_code = T
  ) |> 
  as_tibble()

ENX2CO2 <- 
  ENX2CO2_raw |> 
  spread(gas, value)

ENX2CO2 |> 
  select(-1) |> 
  rename(" " = 1) |> 
  statgl_table() |> 
  add_footnote(ENX2CO2[[1]][1], notation = "symbol")
Carbon dioxide (CO2) Methane (CH4) Nitrous oxide (N2O)
2018 540.255 50,9 8,68
2019 550.961 52,1 9,15
2020 532.904 52,0 8,39
2021 562.527 53,5 8,90
2022 609.204 56,1 10,00
* Actual emission


See the table in our Statbank: ENX2CO2

Climate 
url <- paste0("https://bank.stat.gl/api/v1/", language, "/Greenland/EN/EN30/ENX1MID.px")

ENX1MID_raw <- 
  url |> 
  statgl_fetch(
    measuring         = px_all(),
    time              = px_top(),
    "weather station" = 5,
    month             = px_all(),
    .col_code         = T
  ) |> 
  as_tibble()

ENX1MID <- 
  ENX1MID_raw |> 
  mutate(month = month |> fct_inorder(),
         measuring = measuring |> fct_inorder()) |> 
  spread(measuring, value) |> 
  unite(combi, `weather station`, time, sep = " ")
  
ENX1MID |> 
  select(-1) |> 
  rename(" " = 1) |> 
  statgl_table() |> 
  add_footnote(ENX1MID[[1]][1], notation = "symbol")
Average Maximum temperature Minimum temperature
January -4,0 2,6 -9,8
February -7,6 3,9 -14,8
March -6,2 7,3 -22,2
April -1,4 7,6 -11,8
May 1,6 12,3 -3,8
June 4,9 14,9 0,0
July 7,9 18,1 0,5
August 7,9 16,6 2,8
September 2,8 12,2 -2,3
October 0,8 7,8 -6,1
November -3,2 6,6 -11,2
December -1,9 12,2 -9,0
* Nuuk 2021


See the table in our Statbank: ENX1MID

Motor vehicles 
url <- paste0("https://bank.stat.gl/api/v1/", language, "/Greenland/EN/EN40/ENXMO1HI.px")

ENXMO1HI_raw <- 
  url |> 
  statgl_fetch(
    ownership = 1:2,
    category  = px_all(),
    time      = px_top(),
    .col_code = T
  ) |> 
  as_tibble()

ENXMO1HI <- 
  ENXMO1HI_raw |> 
  mutate_all(~replace(., is.na(.), 0)) |> 
  mutate(category = category |> fct_inorder()) |> 
  spread(ownership, value)

ENXMO1HI |> 
  select(-time) |> 
  rename(" " = 1) |> 
  statgl_table() |> 
  row_spec(1, bold = T) |> 
  add_footnote(ENXMO1HI[[2]][1], notation = "symbol")
Businesses Private households
Motor vehicles total 6.763 7.748
Taxis 175 0
Rental cars 0 0
Cars 2.250 4.299
Buser 108 0
Emergency vehicles total 216 0
  • Of which Fire-engines
216 0
  • Of which Ambulances
0 0
Vans and Trucks total 1.609 90
  • Of which Vans
1.161 90
  • Of which Trucks
448 0
Motorcycles 0 4
Construction machineries 1.186 0
Trailers 338 121
Snowmobiles 459 2.848
ATV and 4-wheeler 354 384
Other motor vehicles 68 2
* 2023

See the table in our Statbank: ENXMO1HI
Last updated: 17. april 2024
---
params:
  lang: "da"
output:
  statgl::statgl_report:
    code_download: true
    code_folding: hide
editor_options: 
  chunk_output_type: console
---

```{r setup, include=FALSE}

knitr::opts_chunk$set(
	echo    = TRUE,
	message = FALSE,
	warning = FALSE,
	class.output = "scroll-100"
)

library("tidyverse")
library("statgl")
library("kableExtra")
library("lubridate")
library("yaml")

language  <- params$lang
option    <- paste0("?lang=", language, "&select")
logo      <- paste0(getwd(),"/add/logo.gif")
txt       <- read_yaml(paste0(getwd(), "/add/txt.yml"), fileEncoding = "ISO-8859-1")
source    <- txt$source[language] %>% unlist()

xaringanExtra::use_clipboard()

```

```{css, echo = FALSE}

.accordion {
  background-color: #919900;
  color: white;
  cursor: pointer;
  padding: 18px;
  width: 100%;
  border: none;
  border-radius: 5px;
  text-align: left;
  outline: none;
  font-size: 15px;
  transition: 0.4s;
}

.active, .accordion:hover {
  background-color: #f97242;
}

.accordion:after {
  content: '\002B';
  color: #777;
  font-weight: bold;
  float: right;
  margin-left: 5px;
}

.active:after {
  content: "\2212";
}

.panel {
  padding: 0px 5px 0px 5px;
  background-color: white;
  max-height: 0;
  overflow: hidden;
  transition: max-height 0.2s ease-out;
}

details {
  width: 100%;
}

details > summary {
  padding: 4px 12px;
  width: 100%;
  background-color: #007f99;
  border: solid;
  border-color: white;
  border-radius: 5px;
  cursor: pointer;
  font-size: 15px;
  color: white;
}

details[open] > summary {
  background-color: #faa41a;
}


.title {
  color: #1b5463;
  font-size: 36px;
}


.personer {
  box-shadow: 3px 3px 4px black;
  background: #004459;
  padding-right: 15px;
  padding-left: 16px;
  padding-top: 0.1px;
  padding-bottom: 1px;
  font-size: 11px;
  color: white;
  vertical-align: middle;
}

.økonomi {
  box-shadow: 3px 3px 4px black;
  background: #007F99;
  padding-right: 15px;
  padding-left: 16px;
  padding-top: 1px;
  padding-bottom: 0.1px;
  font-size: 11px;
  color: white;
  vertical-align: middle;
}

.tværgående {
  box-shadow: 3px 3px 4px black;
  background: #faa41a;
  padding-right: 15px;
  padding-left: 16px;
  padding-top: 0.1px;
  padding-bottom: 1px;
  font-size: 11px;
  color: white;
  vertical-align: middle;
}

.container {
  width: inherit;
}

.scroll-100 {
  max-height: 100;
  overflow-y: auto;
  background-color: inherit;
}


pre {
  max-height: 300px;
  overflow-y: auto;
}

pre[class] {
  max-height: 300px;
}

```

<br>
<br>

<center>

--- 

# [`r txt$EN$title[language]`]{.title}

---

</center>

<details> <summary> `r txt$EN$sub1[language]` </summary>
<br>
<button class="accordion"> `r '*Tabel 1:* {statgl_meta(glue::glue("https://bank.stat.gl/api/v1/{language}/Greenland/EN/EN20/ENX1ACT.px")) |> pluck("title")}' |> glue::glue() ` </button> <div class="panel">

```{r ENX1ACT}

url <- paste0("https://bank.stat.gl/api/v1/", language, "/Greenland/EN/EN20/ENX1ACT.px")

ENX1ACT_raw <- 
  url |> 
  statgl_fetch(
    type      = 0,
    product   = px_all(),
    use       = 0,
    time      = px_top(5),
    .col_code = T
  ) |> 
  as_tibble()

ENX1ACT <- 
  ENX1ACT_raw |> 
  unite(combi, use, type, sep = " ") |> 
  mutate(product = product |> fct_inorder()) |> 
  spread(time, value)

ENX1ACT |> 
  select(-1) |> 
  rename(" " = 1) |> 
  statgl_table() |> 
  row_spec(1, bold = T) |> 
  add_footnote(ENX1ACT_raw[[1]][1], notation = "symbol")


```
<br>
[![](`r logo`){width=40}`r paste(source, "ENX1ACT")`](`r paste0("https://bank.stat.gl:443/sq/3c547ef9-5c8b-47a5-91b9-259c5f0ad146", option)`){target="_blank"}
</div> 

<button class="accordion"> `r '*Tabel 2:* {statgl_meta(glue::glue("https://bank.stat.gl/api/v1/{language}/Greenland/EN/EN20/ENX2CO2.px")) |> pluck("title")}' |> glue::glue() ` </button> <div class="panel">

```{r ENX2CO2}

url <- paste0("https://bank.stat.gl/api/v1/", language, "/Greenland/EN/EN20/ENX2CO2.px")

ENX2CO2_raw <- 
  url |> 
  statgl_fetch(
    type      = 0,
    gas       = px_all(),
    time      = px_top(5),
    .col_code = T
  ) |> 
  as_tibble()

ENX2CO2 <- 
  ENX2CO2_raw |> 
  spread(gas, value)

ENX2CO2 |> 
  select(-1) |> 
  rename(" " = 1) |> 
  statgl_table() |> 
  add_footnote(ENX2CO2[[1]][1], notation = "symbol")


```
<br>
[![](`r logo`){width=40}`r paste(source, "ENX2CO2")`](`r paste0("https://bank.stat.gl:443/sq/3c547ef9-5c8b-47a5-91b9-259c5f0ad146", option)`){target="_blank"}
</div> 


</details>


<details> <summary> `r txt$EN$sub2[language]` </summary>
<br>
<button class="accordion"> `r '*Tabel 3:* {statgl_meta(glue::glue("https://bank.stat.gl/api/v1/{language}/Greenland/EN/EN30/ENX1MID.px")) |> pluck("title")}' |> glue::glue() ` </button> <div class="panel">

```{r ENX1MID}

url <- paste0("https://bank.stat.gl/api/v1/", language, "/Greenland/EN/EN30/ENX1MID.px")

ENX1MID_raw <- 
  url |> 
  statgl_fetch(
    measuring         = px_all(),
    time              = px_top(),
    "weather station" = 5,
    month             = px_all(),
    .col_code         = T
  ) |> 
  as_tibble()

ENX1MID <- 
  ENX1MID_raw |> 
  mutate(month = month |> fct_inorder(),
         measuring = measuring |> fct_inorder()) |> 
  spread(measuring, value) |> 
  unite(combi, `weather station`, time, sep = " ")
  
ENX1MID |> 
  select(-1) |> 
  rename(" " = 1) |> 
  statgl_table() |> 
  add_footnote(ENX1MID[[1]][1], notation = "symbol")

```
<br>
[![](`r logo`){width=40}`r paste(source, "ENX1MID")`](`r paste0("https://bank.stat.gl:443/sq/3b0791b8-47e2-4183-b6d4-ed9a330e78ea", option)`){target="_blank"}
</div> 


</details>


<details> <summary> `r txt$EN$sub3[language]` </summary>
<br>
<button class="accordion"> `r '*Tabel 4:* {statgl_meta(glue::glue("https://bank.stat.gl/api/v1/{language}/Greenland/EN/EN40/ENXMO1HI.px")) |> pluck("title")}' |> glue::glue() ` </button> <div class="panel">
```{r ENXMO1HI}

url <- paste0("https://bank.stat.gl/api/v1/", language, "/Greenland/EN/EN40/ENXMO1HI.px")

ENXMO1HI_raw <- 
  url |> 
  statgl_fetch(
    ownership = 1:2,
    category  = px_all(),
    time      = px_top(),
    .col_code = T
  ) |> 
  as_tibble()

ENXMO1HI <- 
  ENXMO1HI_raw |> 
  mutate_all(~replace(., is.na(.), 0)) |> 
  mutate(category = category |> fct_inorder()) |> 
  spread(ownership, value)

ENXMO1HI |> 
  select(-time) |> 
  rename(" " = 1) |> 
  statgl_table() |> 
  row_spec(1, bold = T) |> 
  add_footnote(ENXMO1HI[[2]][1], notation = "symbol")

```
<br>
[![](`r logo`){width=40}`r paste(source, "ENXMO1HI")`](`r paste0("https://bank.stat.gl:443/sq/82109b9a-6f21-4b91-ab4e-2651718798d5", option)`){target="_blank"}
</div> 

</details>












<hr style="border:1px ridge lightgray"> </hr>
<center> <span style='color:#D3D3D3; font-size:90%;'> `r paste(txt$update[language], format(Sys.Date(), "%d. %B %Y"))` </span> </center>




<script>
var acc = document.getElementsByClassName("accordion");
var i;

for (i = 0; i < acc.length; i++) {
  acc[i].addEventListener("click", function() {
    this.classList.toggle("active");
    var panel = this.nextElementSibling;
    if (panel.style.maxHeight) {
      panel.style.maxHeight = null;
    } else {
      panel.style.maxHeight = panel.scrollHeight + "px";
    } 
  });
}
</script>




