An introduction to the R-package PxWebApiData is given below. Six calls to the main function, ApiData, are demonstrated. First, two calls for reading data sets are shown. The third call captures meta data. However, in practise, one may look at the meta data first. Then three more examples and some background is given.
The dataset below has three variables, Region, ContentsCode and Tid. The variables can be used as input parameters. Here two of the parameters are specified by variable id’s and one parameter is specified by indices. Negative values are used to specify reversed indices. Thus, we here obtain the two first and the two last years in the data.
A list of two data frames is returned; the label version and the id version.
ApiData("http://data.ssb.no/api/v0/en/table/04861",
Region = c("1103", "0301"), ContentsCode = "Bosatte", Tid = c(1, 2, -2, -1))$`04861: Area and population of urban settlements, by region, contents and year`
region contents year value
1 Oslo municipality Number of residents 2000 504348
2 Oslo municipality Number of residents 2002 508134
3 Oslo municipality Number of residents 2021 693195
4 Oslo municipality Number of residents 2022 696712
5 Stavanger Number of residents 2000 106804
6 Stavanger Number of residents 2002 108271
7 Stavanger Number of residents 2021 138375
8 Stavanger Number of residents 2022 138778
$dataset
Region ContentsCode Tid value
1 0301 Bosatte 2000 504348
2 0301 Bosatte 2002 508134
3 0301 Bosatte 2021 693195
4 0301 Bosatte 2022 696712
5 1103 Bosatte 2000 106804
6 1103 Bosatte 2002 108271
7 1103 Bosatte 2021 138375
8 1103 Bosatte 2022 138778To return a single dataset with only labels use the function ApiData1. The function Apidata2 returns only id’s. To return a dataset with both labels and id’s in one dataframe use ApiData12.
ApiData12("http://data.ssb.no/api/v0/en/table/04861",
Region = c("1103", "0301"), ContentsCode = "Bosatte", Tid = c(1, 2, -2, -1)) region contents year Region ContentsCode Tid value
1 Oslo municipality Number of residents 2000 0301 Bosatte 2000 504348
2 Oslo municipality Number of residents 2002 0301 Bosatte 2002 508134
3 Oslo municipality Number of residents 2021 0301 Bosatte 2021 693195
4 Oslo municipality Number of residents 2022 0301 Bosatte 2022 696712
5 Stavanger Number of residents 2000 1103 Bosatte 2000 106804
6 Stavanger Number of residents 2002 1103 Bosatte 2002 108271
7 Stavanger Number of residents 2021 1103 Bosatte 2021 138375
8 Stavanger Number of residents 2022 1103 Bosatte 2022 138778All possible values is obtained by TRUE and corresponds to filter "all": "*" in the api query. Elimination of a variable is obtained by FALSE. An imaginary value corresponds to filter "top" in the api query.
x <- ApiData("http://data.ssb.no/api/v0/en/table/04861",
Region = FALSE, ContentsCode = TRUE, Tid = 3i)To show either label version or id version
x[[1]] contents year value
1 Area of urban settlements (km²) 2020 2218.08
2 Area of urban settlements (km²) 2021 2233.47
3 Area of urban settlements (km²) 2022 2250.94
4 Number of residents 2020 4416981.00
5 Number of residents 2021 4443243.00
6 Number of residents 2022 4485236.00x[[2]] ContentsCode Tid value
1 Areal 2020 2218.08
2 Areal 2021 2233.47
3 Areal 2022 2250.94
4 Bosatte 2020 4416981.00
5 Bosatte 2021 4443243.00
6 Bosatte 2022 4485236.00comment list additional dataset information: Title, latest update and source.
comment(x) label
"04861: Area and population of urban settlements, by contents and year"
source
"Statistics Norway"
updated
"2022-12-14T07:00:00Z" Meta information about the data set can be obtained by returnMetaFrames = TRUE.
ApiData("http://data.ssb.no/api/v0/en/table/04861", returnMetaFrames = TRUE)$Region
values valueTexts
1 3001 Halden
2 3002 Moss
3 3003 Sarpsborg
4 3004 Fredrikstad
5 3005 Drammen
6 3006 Kongsberg
7 3007 Ringerike
8 3011 Hvaler
9 3012 Aremark
10 3013 Marker
11 3014 Indre Østfold
12 3015 Skiptvet
13 3016 Rakkestad
14 3017 Råde
15 3018 Våler (Viken)
16 3019 Vestby
17 3020 Nordre Follo
18 3021 Ås
19 3022 Frogn
20 3023 Nesodden
21 3024 Bærum
22 3025 Asker
[ reached 'max' / getOption("max.print") -- omitted 799 rows ]
$ContentsCode
values valueTexts
1 Areal Area of urban settlements (km²)
2 Bosatte Number of residents
$Tid
values valueTexts
1 2000 2000
2 2002 2002
3 2003 2003
4 2004 2004
5 2005 2005
6 2006 2006
7 2007 2007
8 2008 2008
9 2009 2009
10 2011 2011
11 2012 2012
12 2013 2013
13 2014 2014
14 2015 2015
15 2016 2016
16 2017 2017
17 2018 2018
18 2019 2019
19 2020 2020
20 2021 2021
21 2022 2022
attr(,"text")
Region ContentsCode Tid
"region" "contents" "year"
attr(,"elimination")
Region ContentsCode Tid
TRUE FALSE FALSE
attr(,"time")
Region ContentsCode Tid
FALSE FALSE TRUE PxWebApi offers two more filters for groupings, agg: and vs:. You can see these filters in the code “API Query for this table” when you have made a table in PxWeb.
agg: is used for readymade aggregation groupings.
This example shows the use of aggregation in age groups and aggregated timeseries for the new Norwegian municipality structure from 2020. Also note the url where /en is replaced by /no. That returns labels in Norwegian instead of in English.
ApiData("http://data.ssb.no/api/v0/no/table/07459",
Region = list("agg:KommSummer", c("K-3001", "K-3002")),
Tid = 4i,
Alder = list("agg:TodeltGrupperingB", c("H17", "H18")),
Kjonn = TRUE)$`07459: Befolkning, etter region, kjønn, alder, statistikkvariabel og år`
region kjønn alder statistikkvariabel år value
1 Halden Menn 0-17 år Personer 2020 3197
2 Halden Menn 0-17 år Personer 2021 3148
3 Halden Menn 0-17 år Personer 2022 3127
4 Halden Menn 0-17 år Personer 2023 3080
5 Halden Menn 18 år eller eldre Personer 2020 12609
6 Halden Menn 18 år eller eldre Personer 2021 12674
7 Halden Menn 18 år eller eldre Personer 2022 12754
[ reached 'max' / getOption("max.print") -- omitted 25 rows ]
$dataset
Region Kjonn Alder ContentsCode Tid value
1 K-3001 1 H17 Personer1 2020 3197
2 K-3001 1 H17 Personer1 2021 3148
3 K-3001 1 H17 Personer1 2022 3127
4 K-3001 1 H17 Personer1 2023 3080
5 K-3001 1 H18 Personer1 2020 12609
6 K-3001 1 H18 Personer1 2021 12674
7 K-3001 1 H18 Personer1 2022 12754
[ reached 'max' / getOption("max.print") -- omitted 25 rows ]There are two limitations in the PxWebApi using these filters.
agg: and vs: can only take single elements as input. Filter "all":"*" eg. TRUE, does not work with agg: and vs:.The other filter vs:, specify the grouping value sets, which is a part of the value pool. As it is only possible to give single elements as input, it is easier to query the value pool. This means that vs: is redundant.
In this example Region is the value pool and Fylker (counties) is the value set. As vs:Fylker is redundant, both will return the same:
Region = list("vs:Fylker",c("01","02"))
Region = list(c("01","02"))In PxWebApi the original query is formulated as JSON. Using the parameter returnApiQuery is useful for debugging.
ApiData("http://data.ssb.no/api/v0/en/table/04861", returnApiQuery = TRUE){
"query": [
{
"code": "Region",
"selection": {
"filter": "item",
"values": ["3001", "2399", "9999"]
}
},
{
"code": "ContentsCode",
"selection": {
"filter": "item",
"values": ["Areal", "Bosatte"]
}
},
{
"code": "Tid",
"selection": {
"filter": "item",
"values": ["2000", "2021", "2022"]
}
}
],
"response": {
"format": "json-stat2"
}
} To convert an original JSON API query to a PxWebApiData query there is also a simple webpage PxWebApiData call creator.
Statistics Norway also provides an API with readymade datasets, available by http GET. The data is most easily retrieved with the GetApiData function, which is the same as using the parameter getDataByGET = TRUE in the ApiData function. This dataset is from Statistics Norway’s Economic trends forecasts.
x <- GetApiData("https://data.ssb.no/api/v0/dataset/934516.json?lang=en")
x[[1]] year contents value
1 2023 Gross domestic product 1.6
2 2023 GDP Mainland Norway 1.3
3 2023 Employed persons 0.6
4 2023 Unemployment rate (level) 3.6
5 2023 Wages per standard man-year 5.0
6 2023 Consumer price index (CPI) 5.0
7 2023 CPI-ATE 5.4
8 2023 Housing prices -2.8
9 2023 Money market rate (level) 3.5
10 2023 Import-weighted NOK exchange rate (44 countries) 7.5
11 2024 Gross domestic product 1.8
12 2024 GDP Mainland Norway 1.6
13 2024 Employed persons 0.1
14 2024 Unemployment rate (level) 3.8
15 2024 Wages per standard man-year 4.5
[ reached 'max' / getOption("max.print") -- omitted 25 rows ]comment(x) label
"12880: Main economic indicators. Accounts and forecasts, by year and contents"
source
"Statistics Norway"
updated
"2023-03-10T07:00:00Z" Eurostat REST API offers JSON-stat version 2. It is possible to use this package to obtain data from Eurostat by using GetApiData or the similar functions with 1, 2 or 12 at the end
This example shows HICP total index, latest two periods for EU and Norway. See Eurostat for more.
urlEurostat <- paste0( # Here the long url is split into several lines using paste0
"https://ec.europa.eu/eurostat/api/dissemination/statistics/1.0/data/prc_hicp_mv12r",
"?format=JSON&lang=EN&lastTimePeriod=2&coicop=CP00&geo=NO&geo=EU")
urlEurostat[1] "https://ec.europa.eu/eurostat/api/dissemination/statistics/1.0/data/prc_hicp_mv12r?format=JSON&lang=EN&lastTimePeriod=2&coicop=CP00&geo=NO&geo=EU"GetApiData12(urlEurostat)No encoding supplied: defaulting to UTF-8. Time frequency Unit of measure
1 Monthly Moving 12 months average rate of change
2 Monthly Moving 12 months average rate of change
3 Monthly Moving 12 months average rate of change
4 Monthly Moving 12 months average rate of change
Classification of individual consumption by purpose (COICOP)
1 All-items HICP
2 All-items HICP
3 All-items HICP
4 All-items HICP
Geopolitical entity (reporting)
1 European Union (EU6-1958, EU9-1973, EU10-1981, EU12-1986, EU15-1995, EU25-2004, EU27-2007, EU28-2013, EU27-2020)
2 European Union (EU6-1958, EU9-1973, EU10-1981, EU12-1986, EU15-1995, EU25-2004, EU27-2007, EU28-2013, EU27-2020)
3 Norway
4 Norway
Time freq unit coicop geo time value
1 2023-01 M RCH_MV12MAVR CP00 EU 2023-01 9.5
2 2023-02 M RCH_MV12MAVR CP00 EU 2023-02 9.9
3 2023-01 M RCH_MV12MAVR CP00 NO 2023-01 6.6
4 2023-02 M RCH_MV12MAVR CP00 NO 2023-02 6.9We would like to extract the number of female R&D personel in the services sector of the Norwegian business life for the years 2019 and 2020.
Locate the relevant table at https://www.ssb.no that contains information on R&D personel. Having obtained the relevant table, table 07964, we create the link https://data.ssb.no/api/v0/no/table/07964/
Load the package.
library(PxWebApiData)variables <- ApiData("https://data.ssb.no/api/v0/no/table/07964/",
returnMetaFrames = TRUE)
names(variables)## [1] "NACE2007" "ContentsCode" "Tid"values <- ApiData("https://data.ssb.no/api/v0/no/table/07964/",
returnMetaData = TRUE)
values[[1]]$values## [1] "A-N" "A03" "B05-B09" "B06_B09.1" "C" "C10-C11"
## [7] "C13" "C14-C15" "C16" "C17" "C18" "C19-C20"
## [13] "C21" "C22" "C23" "C24" "C25" "C26"
## [19] "C26.3" "C26.5" "C27" "C28" "C29" "C30"
## [25] "C30.1" "C31" "C32" "C32.5" "C33" "D35"
## [31] "E36-E39" "F41-F43" "G-N" "G46" "H49-H53" "J58"
## [37] "J58.2" "J59-J60" "J61" "J62" "J63" "K64-K66"
## [43] "M70" "M71" "M72"
## [ reached getOption("max.print") -- omitted 2 entries ]values[[2]]$values## [1] "EnhetTot" "EnheterFoU" "FoUpersonale"
## [4] "KvinneligFoUpers" "FoUPersonaleUoHutd" "FoUPersonaleDoktor"
## [7] "FoUArsverk" "FoUArsverkPers" "FoUArsverkUtd"values[[3]]$values## [1] "2007" "2008" "2009" "2010" "2011" "2012" "2013" "2014" "2015" "2016"
## [11] "2017" "2018" "2019" "2020" "2021"mydata <- ApiData("https://data.ssb.no/api/v0/en/table/07964/",
Tid = c("2019", "2020"), # Define year to 2019 and 2020
NACE2007 = "G-N", # Define the services sector
ContentsCode = c("KvinneligFoUpers")) # Define women R&D personell
mydata <- mydata[[1]] # Extract the first list element, which contains full variable names.
head(mydata)## industry (SIC2007) contents year value
## 1 Services total Female R&D personnel 2019 4509
## 2 Services total Female R&D personnel 2020 4666comment(mydata)## label
## "07964: R&D personnel and R&D man-years in Business Enterprise sector, by industry (SIC2007), contents and year"
## source
## "Statistics Norway"
## updated
## "2023-02-16T07:00:00Z"PxWeb and it’s API, PxWebApi is used as output database (Statbank) by many statistical agencies in the Nordic countries and several others, i.e. Statistics Norway, Statistics Finland, Statistics Sweden. See list of installations.
For hints on using PxWebApi in general see PxWebApi User Guide.