statgl presentation

library(statgl)

  • Query and visualize data from Statbank Greenland

  • An implementation of my workflow + experimentation with packages

    • Explorative analysis of statbank. Heavy use of table ID’s, and querying tidy tables.

    • Used to be only ggplot2 themes

    • Used to be (a little) controversial

  • Not a strict implementation of the API

    • See pxweb, PxWebApiData or httr.

statgl_search()

Explore contents of Statbank:

statgl_search()
# A tibble: 21 × 4
   id    text                    type  path 
   <chr> <chr>                   <chr> <chr>
 1 ES    Businesses              l     /ES  
 2 KR    Criminal offenses       l     /KR  
 3 UD    Education               l     /UD  
 4 EN    Energy                  l     /EN  
 5 FI    Fisheries and catch     l     /FI  
 6 IE    Foreign trade           l     /IE  
 7 GD    Greenlanders in Denmark l     /GD  
 8 SU    Health                  l     /SU  
 9 BO    Housing                 l     /BO  
10 IN    Income                  l     /IN  
# ℹ 11 more rows

statgl_search: Query()

Use search query to search for table:

statgl_search("population")
# A tibble: 71 × 6
   id        title                                   type  path  score published
   <chr>     <chr>                                   <chr> <chr> <dbl> <chr>    
 1 BEXCALCS  Population Accounts, stock 1981 -       t     /BE/… 0.894 2023-02-…
 2 BEXCALCRS Regional Population Accounts, stock 19… t     /BE/… 0.742 2023-02-…
 3 SOXOU04   Economically disadvantaged adults by t… t     /SO/… 0.308 2022-12-…
 4 SUXA3     Abortions by districts and mean popula… t     /SU/… 0.293 2023-06-…
 5 SOXOU01   Economically disadvantaged by age and … t     /SO/… 0.264 2022-12-…
 6 SOXOU02   Economically disadvantaged by district… t     /SO/… 0.264 2022-12-…
 7 BEXSAT1   Population and population growth 1901-… t     /BE/… 0.258 2023-02-…
 8 BEXCALC2  Population Accounts (consolidated) 198… t     /BE/… 0.249 2023-02-…
 9 SUXA2     Abortions by age and mean population, … t     /SU/… 0.246 2023-06-…
10 SOXOU03   Economically disadvantaged children an… t     /SO/… 0.220 2022-12-…
# ℹ 61 more rows

statgl_search(): Advanced query

Supports things like wildcard (*) and fuzzy (~) searches:

statgl_search("pop* jan*")
# A tibble: 136 × 6
   id        title                                   type  path  score published
   <chr>     <chr>                                   <chr> <chr> <dbl> <chr>    
 1 BOXPERS   Number of persons per dwelling by dist… t     /BO/… 0.816 2015-07-…
 2 BEXSTA    Population January 1st 1977-2023        t     /BE/… 0.408 2023-02-…
 3 BEXSTAYY  Population January 1st, fixed residenc… t     /BE/… 0.408 2023-02-…
 4 BEXSTB    Population in Municipalities January 1… t     /BE/… 0.408 2023-02-…
 5 BEXSTC    Population in Districts and Municipali… t     /BE/… 0.408 2023-02-…
 6 BEXSTD    Population in Localities January 1st 1… t     /BE/… 0.408 2023-02-…
 7 BEXSTDt   Population seniority in Localities Jan… t     /BE/… 0.408 2023-02-…
 8 BEXSTNUK  Population In Nuuk January 1st by city… t     /BE/… 0.408 2023-02-…
 9 BEXST6NUK Populaion in Nuuk by Citizenship Janua… t     /BE/… 0.408 2023-02-…
10 BEXST2A   Population in  municipalities(2018) Ja… t     /BE/… 0.408 2017-10-…
# ℹ 126 more rows

Apache Lucene

statgl_search(): Other parameters

Specify language or API path:

statgl_search("befolk*", lang = "da", path = "UD")
# A tibble: 8 × 6
  id         title                                   type  path  score published
  <chr>      <chr>                                   <chr> <chr> <dbl> <chr>    
1 UDXISCPROD Befolkningens højst fuldførte uddannel… t     /UD4… 0.289 2023-08-…
2 UDXISCPROE Befolkningens højst fuldførte uddannel… t     /UD4… 0.289 2023-08-…
3 UDXISCPROF Befolkningens højst fuldførte uddannel… t     /UD4… 0.289 2023-08-…
4 UDXISCPROG Befolkningens højst fuldførte uddannel… t     /UD4… 0.289 2023-08-…
5 UDXISCPROH Befolkningens højst fuldførte uddannel… t     /UD4… 0.289 2023-09-…
6 UDXISCPROA Befolkningens uddannelse efter bopæl o… t     /UD9… 0.289 2017-08-…
7 UDXISCPROB Befolkningens uddannelse efter alder 2… t     /UD9… 0.289 2017-08-…
8 UDXISCPROC Befolkningens uddannelse efter alder o… t     /UD9… 0.289 2017-08-…

statgl_search(): Path diving

Folder shorthand shortcut:

statgl_search(path = "BE0120")
# A tibble: 10 × 5
   id         text                                           type  path  updated
   <chr>      <chr>                                          <chr> <chr> <chr>  
 1 BEXSTA     Population January 1st 1977-2023               t     /BE/… 2023-0…
 2 BEXSTAYY   Population January 1st, fixed residence type … t     /BE/… 2023-0…
 3 BEXSTB     Population in Municipalities January 1st 1977… t     /BE/… 2023-0…
 4 BEXSTC     Population in Districts and Municipalities Ja… t     /BE/… 2023-0…
 5 BEXSTD     Population in Localities January 1st 1977-2023 t     /BE/… 2023-0…
 6 BEXSTDt    Population seniority in Localities January 1s… t     /BE/… 2023-0…
 7 BEXSTE     Marital Status by January 1st 1977-2023        t     /BE/… 2023-0…
 8 BEXSTFSGRL Persons born in Greenland by year of birth an… t     /BE/… 2023-0…
 9 BEXSTNUK   Population In Nuuk January 1st by citydistric… t     /BE/… 2023-0…
10 BEXXKIRK   Church of Denmark, members 2012 - 2023         t     /BE/… 2023-0…

statgl_search: Other APIs

Can explore other pxweb APIs:

statgl_search(api_url = "bank.stat.gl", path = "GSmicro")
# A tibble: 4 × 4
  id    text          type  path       
  <chr> <chr>         <chr> <chr>      
1 UD    Education     l     /GSmicro/UD
2 SU    Health        l     /GSmicro/SU
3 AR    Labour market l     /GSmicro/AR
4 BE    Population    l     /GSmicro/BE

statgl_search(): Other APIs

Including other statistical offices:

statgl_search(api_url = "statbank.hagstova.fo", path = "H2", lang = "fo")
# A tibble: 20 × 4
   id    text                           type  path   
   <chr> <chr>                          <chr> <chr>  
 1 UO    Umhvørvi og orka               l     /H2/UO 
 2 IB    Íbúgvar og val                 l     /H2/IB 
 3 AM    Arbeiði og lønir               l     /H2/AM 
 4 IP    Inntøkur og prísir             l     /H2/IP 
 5 UV    Undirvísing                    l     /H2/UV 
 6 MM    Mentan og átrúnaður            l     /H2/MM 
 7 AL    Almannamál                     l     /H2/AL 
 8 HM    Heilsumál                      l     /H2/HM 
 9 RL    Rættur og løgregla             l     /H2/RL 
10 SS    Samferðsla og samskifti        l     /H2/SS 
11 VV    Vinna og veiða                 l     /H2/VV 
12 UH    Uttanlandshandil               l     /H2/UH 
13 VB    Vinnubúskapur                  l     /H2/VB 
14 PF    Peninga- og fíggjarviðurskifti l     /H2/PF 
15 LK    Lands- og kommunubúskapur      l     /H2/LK 
16 TB    Tjóðarbúskapur                 l     /H2/TB 
17 KB    Konjunkturbarometrið           l     /H2/KB 
18 MT    Manntal 2011                   l     /H2/MT 
19 SDG   Heimsmálini                    l     /H2/SDG
20 DEV   Hagtøl undir menning           l     /H2/DEV

statgl_url()

statgl_url()

Lookup url of specific table ID:

statgl_url("BEXSTNUK")
[1] "https://bank.stat.gl:443/api/v1/en/Greenland/BE/BE01/BE0120/BEXSTNUK.PX"


In other languages:

statgl_url("BEXSTNUK", lang = "kl")
[1] "https://bank.stat.gl:443/api/v1/kl/Greenland/BE/BE01/BE0120/BEXSTNUK.PX"

statgl_url(): Other languages

Shorthand for translated table:

statgl_url("BEDSTNUK")
[1] "https://bank.stat.gl:443/api/v1/da/Greenland/BE/BE01/BE0120/BEXSTNUK.PX"


lang parameter will always translate:

statgl_url("BEDSTNUK", lang = "kl")
[1] "https://bank.stat.gl:443/api/v1/kl/Greenland/BE/BE01/BE0120/BEXSTNUK.PX"

statgl_url(): Other API’s

Works with other API’s too:

statgl_url(
  "land_oyfj", lang = "fo",
  api_url = "statbank.hagstova.fo/api/v1/en/H2/"
)
[1] "statbank.hagstova.fo/api/v1/fo/H2/UO/UO01/land_oyfj.px"

statgl_meta()

statgl_meta()

I would like your feedback on this:

statgl_meta("BEDSTNUK")
$title
[1] "Nuuks befolkning efter alder, bydel, fødested, køn og tid"

$url
[1] "https://bank.stat.gl:443/api/v1/da/Greenland/BE/BE01/BE0120/BEXSTNUK.PX"

$variables
# A tibble: 5 × 6
  code           text     elimination time  values      valueTexts 
  <chr>          <chr>    <lgl>       <lgl> <list>      <list>     
1 age            alder    TRUE        NA    <chr [100]> <chr [100]>
2 citydistrict   bydel    TRUE        NA    <chr [6]>   <chr [6]>  
3 gender         køn      TRUE        NA    <chr [3]>   <chr [3]>  
4 place of birth fødested TRUE        NA    <chr [3]>   <chr [3]>  
5 time           tid      NA          TRUE  <chr [30]>  <chr [30]>

statgl_meta(): Return

Do you expect something closer to:

statgl_meta("BEDSTNUK") %>% pluck(3) %>% pull(values, code)
$age
  [1] "0"  "1"  "2"  "3"  "4"  "5"  "6"  "7"  "8"  "9"  "10" "11" "12" "13" "14"
 [16] "15" "16" "17" "18" "19" "20" "21" "22" "23" "24" "25" "26" "27" "28" "29"
 [31] "30" "31" "32" "33" "34" "35" "36" "37" "38" "39" "40" "41" "42" "43" "44"
 [46] "45" "46" "47" "48" "49" "50" "51" "52" "53" "54" "55" "56" "57" "58" "59"
 [61] "60" "61" "62" "63" "64" "65" "66" "67" "68" "69" "70" "71" "72" "73" "74"
 [76] "75" "76" "77" "78" "79" "80" "81" "82" "83" "84" "85" "86" "87" "88" "89"
 [91] "90" "91" "92" "93" "94" "95" "96" "97" "98" "99"

$citydistrict
[1] "N" "1" "2" "3" "4" "9"

$gender
[1] "T" "M" "K"

$`place of birth`
[1] "T" "N" "S"

$time
 [1] "1994" "1995" "1996" "1997" "1998" "1999" "2000" "2001" "2002" "2003"
[11] "2004" "2005" "2006" "2007" "2008" "2009" "2010" "2011" "2012" "2013"
[21] "2014" "2015" "2016" "2017" "2018" "2019" "2020" "2021" "2022" "2023"

statgl_meta(): metadata?

Output is better suited for statgl_fetch_px():

statgl_meta("BEDSTNUK", returnclass = "px_list")
$CHARSET
[1] "ANSI"

$`AXIS-VERSION`
[1] "2010"

$CODEPAGE
[1] "Windows-1252"

$LANGUAGE
[1] "en"

$LANGUAGES
[1] "en,da,kl"

$`CREATION-DATE`
[1] "20190124 09:00"

$DECIMALS
[1] "0"

$SHOWDECIMALS
[1] "0"

$MATRIX
[1] "BEXSTNUK"

$COPYRIGHT
[1] "YES"

$`SUBJECT-CODE`
[1] "BE"

$`SUBJECT-AREA`
[1] "Population"

$DESCRIPTION
[1] "Population In Nuuk January 1st by citydistrict 1994-2023 <em>[BEESTNUK]</em>"

$TITLE
[1] "Population in Nuuk by time"

$CONTENTS
[1] "Population in Nuuk"

$HEADING
[1] "time"

$`VALUES("time")`
[1] "1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023"

$`TIMEVAL("time")`
[1] "TLIST(A1),1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023"

$`CODES("time")`
[1] "1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023"

$`LAST-UPDATED`
[1] "20230210 09:00"

$UNITS
[1] "persons"

$CONTACT
[1] "Lars Pedersen, LARP@stat.gl"

$SOURCE
[1] "Statistics Greenland"

$NOTE
[1] "The Population Register contains information on all persons who have resided in Greenland after 1 January 1977. ##The purpose of the register is to be the basis for population statistics, and to supplement other personal information #with basic informati\r\non about each person, like address and family relations.The Population register is updated with information from CPR (Administrative Population Register) where the following information is retrieved: #name, gender, age, place of birth, citizenship, marit\r\nal status, reference to mother, father and spouse, address of residence and more.#According to §13 of the Act on Greenland Statistics, no person-related information is disclosed from the register, except for personal numbers, randomly drawn for surveys"

$LINK
[1] "www.stat.gl/bee202301/m1"

$`NEXT-UPDATE`
[1] "20240209 09:00"

$`SUBJECT-AREA[da]`
[1] "Befolkning"

$`DESCRIPTION[da]`
[1] "Befolkningen i Nuuks bydele pr 1. januar 1994-2023 <em>[BEDSTNUK]</em>"

$`TITLE[da]`
[1] "Nuuks befolkning efter tid"

$`CONTENTS[da]`
[1] "Nuuks befolkning"

$`HEADING[da]`
[1] "tid"

$`VALUES[da]("tid")`
[1] "1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023"

$`TIMEVAL[da]("tid")`
[1] "TLIST(A1),1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023"

$`LAST-UPDATED[da]`
[1] "20230210 09:00"

$`UNITS[da]`
[1] "personer"

$`CONTACT[da]`
[1] "Lars Pedersen, LARP@stat.gl"

$`SOURCE[da]`
[1] "Grønlands Statistik"

$`NOTE[da]`
[1] "Befolkningsstatistikregistret indeholder oplysninger om alle personer, som har haft bopæl i Grønland efter 1. januar 1977.##Registrets formål er at danne grundlag for befolkningsstatistikken, samt supplere andre personhenførbare oplysninger #med basisopl\r\nysninger om personen, samt dennes adresse og familierelationer.#Befolkningsstatistikregistret opdateres med oplysninger fra CPR(Folkeregistrene) hvor følgende oplysninger hentes:#navn, køn, alder, fødested, statsborgerskab, civilstand, henvisning til mor\r\n, far samt ægtefælle, bopælsadresse og tilflytningsdato.##Jfr §13 i Lov om Grønlands Statistik, videregives ingen personhenførbare oplysninger fra registret, bortset fra personnumre, som efter Datatilsynets godkendelse er udtrukket til interviewundersøge\r\nlser"

$`LINK[da]`
[1] "www.stat.gl/bed202301/m1"

$`SUBJECT-AREA[kl]`
[1] "Innuttaasut"

$`DESCRIPTION[kl]`
[1] "Nuummi innuttaasut 1994-2023 <em>[BENSTNUK]</em>"

$`TITLE[kl]`
[1] "Nuummi innuttaasut kingorna piffissaq"

$`CONTENTS[kl]`
[1] "Nuummi innuttaasut"

$`HEADING[kl]`
[1] "piffissaq"

$`VALUES[kl]("piffissaq")`
[1] "1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023"

$`TIMEVAL[kl]("piffissaq")`
[1] "TLIST(A1),1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023"

$`LAST-UPDATED[kl]`
[1] "20230210 09:00"

$`UNITS[kl]`
[1] "inuit amerlassusaat"

$`CONTACT[kl]`
[1] "Lars Pedersen, LARP@stat.gl"

$`SOURCE[kl]`
[1] "Naatsorsueqqissaartarfik"

$`NOTE[kl]`
[1] "Innuttaasunut nalunaarsuisarfik 1.januaari 1977 kingorna Kalaallit Nunaanni najugaqarsimasunut tamanut paasissutissanik imaqarpoq.#Innuttaasut pillugit kisitsisitigut paasissutissaliorsinnaaneq nalunaarsuisarfiup siunertaraa, taamaatullu inunnut tunngasu\r\nnut paasissutissanut allanut tapertaalluni.#Inuup paasissutissaanik tunngaviusunik, kiisali najugaanut ilaqutariinnermilu inissisimaneranut tunngasut.#Innuttaasunut kisitsisitigut paasissutissat nalunaarsuisarfiat paasissutissanit CPR-iminngaanneersunik \r\n(Inunnut nalunaarsuisarfiit) nutarterneqartarpoq tassani paasissutissat pineqartut aaneqarnerisigut:#Ateq, suiaassuseq, ukiut, inunngorfik, innuttaassuseq, aappaqarneq, anaanaasumut, ataataasumut aapparisamullu innersuunneqarneq, najukkami adresse aammal\r\nu qanga nuussimanermut ulloq.##Naatsorsueqqissaartarfik pillugu inatsimmi §13 malillugu inuit ataasiakkaat pillugit paasissutissat nalunaarsuiffinniittut allanut ingerlateqqinneqaqqusaanngillat,taamaallaat inuit normui Datatilsynemit immikkut akuersisoqa\r\nrtillugu apersuinissamut atugassat ingerlateqqinneqarsinnaapput.”"

$`LINK[kl]`
[1] "www.stat.gl/ben202301/m1"

statgl_fetch()

statgl_fetch()

Data querying used to look like this:

statgl_url("BEXSTNUK") %>% 
  pxweb::pxweb_get_data(list()) %>% 
  as_tibble()


And this:

statgl_url("BEXSTNUK") %>% 
  statgl_fetch()

statgl_fetch(): Use table ID

If API is Statbank Greenland and not URL:

statgl_fetch("BEDSTNUK")
# A tibble: 30 × 2
   tid   value
   <chr> <int>
 1 1994  12483
 2 1995  12723
 3 1996  12882
 4 1997  12909
 5 1998  13024
 6 1999  13169
 7 2000  13445
 8 2001  13649
 9 2002  13884
10 2003  13884
# ℹ 20 more rows

statgl_fetch(): Fetch helpers

px_top()

statgl_fetch("BEDSTNUK", time = px_top(1))
# A tibble: 1 × 2
  tid   value
  <chr> <int>
1 2023  19604

px_all()

statgl_fetch("BEDSTNUK", time = px_top(1), age = px_all("*0"))
# A tibble: 10 × 3
   alder tid   value
   <chr> <chr> <int>
 1 0     2023    249
 2 10    2023    237
 3 20    2023    234
 4 30    2023    416
 5 40    2023    313
 6 50    2023    242
 7 60    2023    260
 8 70    2023    100
 9 80    2023     25
10 90    2023      4

statgl_fetch(): Elimination

Some values are not shown by default (elimination variables)

statgl_fetch("BEXBAF4B", time = px_top())
# A tibble: 1 × 2
  time  value
  <chr> <int>
1 2022  18325

statgl_fetch(): Elimination

.eliminate_rest can be used to show these quickly:

statgl_fetch("BEXBAF4B", time = px_top(), .eliminate_rest = FALSE)
# A tibble: 38,416 × 6
   origin     `place of birth` gender distination            time  value
   <chr>      <chr>            <chr>  <chr>                  <chr> <int>
 1 Nanortalik Greenland        Men    Nanortalik             2022    114
 2 Nanortalik Greenland        Men    Aappilattoq (NAN)      2022      1
 3 Nanortalik Greenland        Men    Narsaq Kujalleq        2022      5
 4 Nanortalik Greenland        Men    Tasiusaq (NAN)         2022      3
 5 Nanortalik Greenland        Men    Illorpaat              2022      0
 6 Nanortalik Greenland        Men    Ammassivik             2022      1
 7 Nanortalik Greenland        Men    Alluitsup Paa          2022      5
 8 Nanortalik Greenland        Men    Andre lokaliteter(NAN) 2022      0
 9 Nanortalik Greenland        Men    Qaqortoq               2022     29
10 Nanortalik Greenland        Men    Saarloq                2022      1
# ℹ 38,406 more rows

statgl_fetch(): Elimination

.val_code shows underlying value codes:

statgl_fetch(
  "BEXBAF4B", time = px_top(), .eliminate_rest = FALSE, 
  .val_code = TRUE
)
# A tibble: 38,416 × 6
   origin     `place of birth` gender distination time  value
   <chr>      <chr>            <chr>  <chr>       <chr> <int>
 1 9550100NAN N                M      9550100NAN  2022    114
 2 9550100NAN N                M      9550102APL  2022      1
 3 9550100NAN N                M      9550103NKJ  2022      5
 4 9550100NAN N                M      9550104TAQ  2022      3
 5 9550100NAN N                M      9550105ILP  2022      0
 6 9550100NAN N                M      9550106AMS  2022      1
 7 9550100NAN N                M      9550108ALP  2022      5
 8 9550100NAN N                M      9550199X01  2022      0
 9 9550100NAN N                M      9550200QAQ  2022     29
10 9550100NAN N                M      9550201SAL  2022      1
# ℹ 38,406 more rows

statgl_fetch(): Elimination

.val_code accepts strings:

statgl_fetch(
  "BEXBAF4B", time = px_top(), .eliminate_rest = FALSE, 
  .val_code = c("origin", "distination")
)
# A tibble: 38,416 × 6
   origin     `place of birth` gender distination time  value
   <chr>      <chr>            <chr>  <chr>       <chr> <int>
 1 9550100NAN Greenland        Men    9550100NAN  2022    114
 2 9550100NAN Greenland        Men    9550102APL  2022      1
 3 9550100NAN Greenland        Men    9550103NKJ  2022      5
 4 9550100NAN Greenland        Men    9550104TAQ  2022      3
 5 9550100NAN Greenland        Men    9550105ILP  2022      0
 6 9550100NAN Greenland        Men    9550106AMS  2022      1
 7 9550100NAN Greenland        Men    9550108ALP  2022      5
 8 9550100NAN Greenland        Men    9550199X01  2022      0
 9 9550100NAN Greenland        Men    9550200QAQ  2022     29
10 9550100NAN Greenland        Men    9550201SAL  2022      1
# ℹ 38,406 more rows

Visuals

scale_color_statgl()

statgl_fetch("BEXSTNUK", citydistrict = c(1:4, 9)) %>% 
  ggplot(aes(as.numeric(time), value, color = citydistrict)) +
  geom_line(size = 2) +
  scale_color_statgl()

scale_fill_statgl()

statgl_fetch("BEXSTNUK", citydistrict = c(1:4, 9)) %>% 
  ggplot(aes(x = as.numeric(time), y = value, fill = citydistrict)) +
  geom_area() +
  scale_fill_statgl()

scale_fill_statgl(): Palettes

statgl_fetch("BEXSTNUK", citydistrict = c(1:4, 9)) %>% 
  ggplot(aes(x = as.numeric(time), y = value, fill = citydistrict)) +
  geom_area() +
  scale_fill_statgl(palette = "aurora")

scale_fill_statgl(): Reverse

statgl_fetch("BEXSTNUK", citydistrict = c(1:4, 9)) %>% 
  ggplot(aes(x = as.numeric(time), y = value, fill = citydistrict)) +
  geom_area() +
  scale_fill_statgl(palette = "aurora", reverse = TRUE)

theme_statgl()

statgl_fetch("BEXSTNUK", citydistrict = c(1:4, 9)) %>% 
  ggplot(aes(x = as.numeric(time), y = value, fill = citydistrict)) +
  geom_area() +
  scale_fill_statgl() +
  theme_statgl()

Other visuals

  • statgl_plot()

  • statgl_table()

  • statgl_report()

  • statgl_map()

thanks()