docs/articles/nsoApi.md
In bowerth/nsoApi: functions for connecting to various APIs
title: "nsoApi"
author: "Bo Werth"
date: "2016-09-01"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{Vignette Title}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
Providers
Some of the APIs require authentication:
|cou |provider |label |access |
|:---|:--------|:------------------------------|:--------|
|USA |BEA |Bureau of Economic Analysis |register |
|NLD |CBS |Statistics Netherlands |free |
|DEU |GENESIS |Destatis |paid |
|GBR |ONS |Office for National Statistics |register |
|NOR |SSB |Statistics Norway |free |
|AUT |STATAT |Statistics Austria |free |
|CAN |WDS |Statistics Canada |IP |
Setup
Create an R script containing a list with your keys or just modify the the example script and save it with gpg encryption at inst/apiKey.R.gpg.
apiKey <- list(
BEA = list(
userid = "29UG8ZKT-JN9R5N2Q")
,
GENESIS = list(
kennung = "8XXHKY78",
passwort = "3QYYTQ89")
,
ONS = list(
apikey = "k647uahw")
)
To prevent compromising the API keys, it is suggested to encrypt the file. If you are on Windows, you will need to install GnuPG first. The nsoApiGPG function allows to specify a directory to an executable using the gpg parameter.
file.apiKey.enc <- system.file("apiKey.R.gpg", package = "nsoApi")
nsoApi::nsoApiGPG(file = file.apiKey.enc,
gpg = NULL,
passphrase = Sys.getenv("NSOAPIGPG"),
keep = FALSE
)
## [1] TRUE
BEA Bureau of Economic Analysis
api.param <- list(
DATASETNAME = "GDPbyIndustry",
METHOD = "GETPARAMETERVALUES",
RESULTFORMAT = "JSON",
USERID = apiKey$BEA$userid,
PARAMETERNAME = "TABLEID"
)
tablelist <- beaAPI(api.param = api.param, curl = curl)
tablelist$BEAAPI$Request$RequestParam
## ParameterName ParameterValue
## 1 USERID 7023E825-15FF-488D-B8D9-D70E6F67D439
## 2 PARAMETERNAME TABLEID
## 3 DATASETNAME GDPBYINDUSTRY
## 4 RESULTFORMAT JSON
## 5 METHOD GETPARAMETERVALUES
Show first 5 tables
|Key |Desc |
|:---|:-------------------------------------------------------------------------|
|1 |Value Added by Industry (A) (Q) |
|5 |Value Added by Industry as a Percentage of Gross Domestic Product (A) (Q) |
|6 |Components of Value Added by Industry (A) |
|7 |Components of Value Added by Industry as a Percentage of Value Added (A) |
|8 |Chain-Type Quantity Indexes for Value Added by Industry (A) (Q) |
api.param <- list(
DATASETNAME = "GDPBYINDUSTRY",
FREQUENCY = "A",
INDUSTRY = "11",
METHOD = "GETDATA",
RESULTFORMAT = "JSON",
USERID = apiKey$BEA$userid,
TABLEID = "1",
YEAR = paste(as.character(c(2008:2015)), collapse = ",")
)
datalist <- beaAPI(api.param = api.param, curl = curl)
knitr::kable(datalist$BEAAPI$Results$Data)
|TableID |Frequency |Year |Quarter |Industry |IndustrYDescription |DataValue |NoteRef |
|:-------|:---------|:----|:-------|:--------|:-------------------------------------------|:---------|:-------|
|1 |A |2008 |2008 |11 |Agriculture, forestry, fishing, and hunting |154.5 |1 |
|1 |A |2009 |2009 |11 |Agriculture, forestry, fishing, and hunting |137.7 |1 |
|1 |A |2010 |2010 |11 |Agriculture, forestry, fishing, and hunting |160.2 |1 |
|1 |A |2011 |2011 |11 |Agriculture, forestry, fishing, and hunting |197.2 |1 |
|1 |A |2012 |2012 |11 |Agriculture, forestry, fishing, and hunting |185.8 |1 |
|1 |A |2013 |2013 |11 |Agriculture, forestry, fishing, and hunting |225.4 |1 |
|1 |A |2014 |2014 |11 |Agriculture, forestry, fishing, and hunting |215.4 |1 |
|1 |A |2015 |2015 |11 |Agriculture, forestry, fishing, and hunting |196.0 |1 |
CBS Statistics Netherlands
First, we define the API URI and the dataset ID
api <- "http://opendata.cbs.nl/ODataApi/OData/"
DSD <- "82572ENG" # Input-Output: "83068ENG"
CBS Metadata
Next, we return the members of a dimension
scheme <- "SectorBranchesSIC2008"
## print query
cbsODataAPI(api=api, DSD=DSD, scheme=scheme, query=TRUE)
[1] "http://opendata.cbs.nl/ODataApi/OData/82572ENG/SectorBranchesSIC2008"
cbs_dimension <- cbsODataAPI(api=api, DSD=DSD, scheme=scheme, query=FALSE)
knitr::kable(cbs_dimension[1:n_table, 1:2])
|Key |Title |
|:------|:-----------------------------------|
|300025 |A-U All economic activities |
|301000 |A Agriculture, forestry and fishing |
|301100 |01 Agriculture |
|304300 |02 Forestry and logging |
|305000 |03 Fishing and aquaculture |
CBS Data
Finally, we return a dataset
scheme <- "TypedDataSet"
# print query
cbsODataAPI(api=api, DSD=DSD, scheme=scheme, query=TRUE)
[1] "http://opendata.cbs.nl/ODataApi/OData/82572ENG/TypedDataSet"
cbs_data <- cbsODataAPI(api=api, DSD=DSD, scheme=scheme, query=FALSE)
knitr::kable(cbs_data[1:n_table, 1:6])
| ID|SectorBranchesSIC2008 |Periods | OutputBasicPrices_1| IntermediateConsumption_2| GrossValueAddedBasicPrices_3|
|--:|:---------------------|:--------|-------------------:|-------------------------:|----------------------------:|
| 0|300025 |1995JJ00 | 587866| 292992| 294874|
| 1|300025 |1996JJ00 | 624009| 316394| 307615|
| 2|300025 |1997JJ00 | 671992| 343515| 328477|
| 3|300025 |1998JJ00 | 714756| 364847| 349909|
| 4|300025 |1999JJ00 | 762732| 390927| 371805|
CBS Tables
List existing tables in CBS API. This takes 1-2 minutes to complete
cbs_tables <- nsoApi::cbsODataTables()
knitr::kable(cbs_tables[1:n_table, ])
|Identifier |Title |Frequency |Period |
|:----------|:--------------------------------------------------------------------------|:---------|:-------------|
|82010NED |Zeggenschap bedrijven in Nederland; banen en lonen, bedrijfsgrootte |Perjaar |2008 t/m 2011 |
|82011NED |Zeggenschap bedrijven in Nederland; banen en lonen, bedrijfstak (SBI 2008) |Perjaar |2008 t/m 2011 |
|81179ned |Zeggenschap bedrijven in Nederland; banen en lonen (SBI'93) 2006-2008 |Stopgezet |2006-2008 |
|81251ned |Banen werknemers en afstand woon-werk; woon- en werkregio's |Perjaar |2006 - 2014 |
|80339ned |Banen van werknemers; bedrijfsgrootte en economische activiteit, 2006-2009 |Stopgezet |2006 - 2009 |
Destatis GENESIS
Genesis Metadata
api.param.datenexport <- list(
method = "DatenExport",
kennung = apiKey$GENESIS$kennung,
passwort = apiKey$GENESIS$passwort,
namen = "81000BJ002",
bereich = "oeffentlich",
format = "csv",
werte = "false",
metadaten = "false",
zusatz = "true",
startjahr = "2013",
endjahr = "2014",
zeitscheiben = "",
regionalschluessel = "",
sachmerkmal = "",
sachschluessel = "",
stand = "01.01.2001",
sprache = "de"
)
## retrieve metadata
xml_list_datenexport_meta <- genesisAPI(api.param = api.param.datenexport,
service = "ExportService",
curl = curl)
meta_df <- genesisXMLtoDF(xml.list = xml_list_datenexport_meta,
meta = TRUE)
knitr::kable(meta_df)
|code |label |
|:------|:----------------------------------------------|
|JAHR |Jahr |
|DINSG |Deutschland insgesamt |
|BWS001 |Bruttowertschöpfung |
|VGRPB5 |Preisbasis (jeweilige Preise / preisbereinigt) |
|WZ08G2 |WZ2008: Wirtschaftsbereiche der VGR |
|code |label |
|:---------|:--------------------------------------------------|
|DG |Deutschland |
|VGRJPM |in jeweiligen Preisen (Mrd. EUR) |
|VGRPKM |preisbereinigt, Kettenindex (2010=100) |
|WZ08-A |Land- und Forstwirtschaft, Fischerei |
|WZ08-B-18 |Produzierendes Gewerbe ohne Baugewerbe |
|WZ08-C |Verarbeitendes Gewerbe |
|WZ08-F |Baugewerbe |
|WZ08-G-01 |Handel, Verkehr, Gastgewerbe |
|WZ08-J |Information und Kommunikation |
|WZ08-K |Erbringung von Finanz- und Versicherungsleistungen |
|WZ08-L |Grundstücks- und Wohnungswesen |
|WZ08-M-02 |Unternehmensdienstleister |
|WZ08-O-03 |Öffentliche Dienstleister, Erziehung, Gesundheit |
|WZ08-R-02 |Sonstige Dienstleister |
Genesis Data
api.param.datenexport <- list(
method = "DatenExport",
kennung = apiKey$GENESIS$kennung,
passwort = apiKey$GENESIS$passwort,
namen = "81000BJ002",
bereich = "oeffentlich",
format = "csv",
werte = "true",
metadaten = "false",
zusatz = "false",
startjahr = "2013",
endjahr = "2014",
zeitscheiben = "",
regionalschluessel = "",
sachmerkmal = "",
sachschluessel = "",
stand = "01.01.2001",
sprache = "de"
)
## retrieve data
xml_list_datenexport <- genesisAPI(api.param = api.param.datenexport,
service = "ExportService",
curl = curl)
## convert to data frame
data_df <- genesisXMLtoDF(xml.list = xml_list_datenexport)
knitr::kable(data_df[1:n_table,])
|VGRPB5 |WZ08G2 |DINSG | ZI-WERT|UNIT | WERT|
|:------|:---------|:-----|-------:|:------|-------:|
|VGRJPM |WZ08-A |DG | 2013|BWS001 | 24.005|
|VGRJPM |WZ08-B-18 |DG | 2013|BWS001 | 654.188|
|VGRJPM |WZ08-C |DG | 2013|BWS001 | 572.186|
|VGRJPM |WZ08-F |DG | 2013|BWS001 | 113.247|
|VGRJPM |WZ08-G-01 |DG | 2013|BWS001 | 395.395|
Genesis Tables
genesis_tables <- nsoApi::genesisTables(
namefilter = 11, # for testing - takes a few minutes to complete
## namefilter = c(11:14, 2, 3, 41:49, 5:9),
fields = c("code", "beschriftungstext"),
kennung = apiKey$GENESIS$kennung,
passwort = apiKey$GENESIS$passwort
)
"11*" filter: 4 entries
genesis_tables$beschriftungstext <- gsub("\n", " ", genesis_tables$beschriftungstext)
knitr::kable(genesis_tables)
|code |beschriftungstext |
|:----------|:-----------------------------------------------------------------------------|
|11111BJ001 |Feststellung des Gebietsstands, Gebietsflche, Deutschland insgesamt, Stichtag |
|11111KJ001 |Feststellung des Gebietsstands, Gebietsflche, Kreise, Stichtag |
|11111LJ001 |Feststellung des Gebietsstands, Gebietsflche, Bundeslnder, Stichtag |
|NA |NA |
ONS UK Office for National Statistics
ONS Data
api.param <- list(context = "Census",
geog = "2011WARDH",
totals = "false",
apikey = "xPuqnMzZ01")
ons_data <- onsCsvData(api.param = api.param, dataset = "QS208EW")
knitr::kable(ons_data[1:n_table, 1:7])
|geographic_id | total_all_categories_religion| christian| buddhist| hindu| jewish| muslim|
|:-------------|-----------------------------:|---------:|--------:|------:|------:|-------:|
|K04000001 | 56075912| 33243175| 247743| 816633| 263346| 2706066|
|E92000001 | 53012456| 31479876| 238626| 806199| 261282| 2660116|
|W92000004 | 3063456| 1763299| 9117| 10434| 2064| 45950|
|E12000001 | 2596886| 1753334| 6316| 7772| 4503| 46764|
|E12000002 | 7052177| 4742860| 20695| 38259| 30417| 356458|
ONS Tables
ons_tables <- onsAPI(method = "contexts", api.key = apiKey$ONS$apikey)
knitr::kable(ons_tables)
| contextId|contextName |
|---------:|:--------------|
| 1|Census |
| 2|Socio-Economic |
| 3|Economic |
| 4|Social |
ons_collections <- onsAPI(method = "collections", context = "Economic", api.key = apiKey$ONS$apikey)
titles <- sapply(ons_collections$name[, 1], function(x) x[1, 2])
titles <- iconv(titles, "latin1", "ASCII", sub="")
ons_collections_df <- data.frame(ID = ons_collections$id, Title = titles)
knitr::kable(ons_collections_df[1:n_table, ])
|ID |Title |
|:--------|:-------------------------------------------------------|
|A02Level |Labour Force Survey Summary Levels (Explorable Dataset) |
|A02Rate |Labour Force Survey Summary Rates (Explorable Dataset) |
|ABS |Annual Business Survey |
|ABS1 |Annual Business Survey |
|ASHE07E |Earnings by place of work |
STATAT Statistics Austria
STATAT Data
dataset <- "OGD_vgr001_VGRJahresR_1"
statat_data <- statatAPI(dataset = dataset)
## Warning: attributes are not identical across measure variables; they will
## be dropped
knitr::kable(statat_data[1:n_table, ])
|date |C_VGRW04_0 |variable | value|
|:--------|:----------|:-----------|-------:|
|A10-1976 |VGRW04-1 |F_ISIS_4575 | 41853.8|
|A10-1976 |VGRW04-2 |F_ISIS_4575 | 14974.9|
|A10-1976 |VGRW04-3 |F_ISIS_4575 | 16556.6|
|A10-1976 |VGRW04-4 |F_ISIS_4575 | 17803.1|
|A10-1976 |VGRW04-5 |F_ISIS_4575 | -150.7|
baseURL <- "http://data.statistik.gv.at/web/catalog.jsp"
dataset_title <-
baseURL %>%
RCurl::getURL() %>%
XML::htmlParse(baseURL) %>%
XML::readHTMLTable() %>%
lapply(function(x) x[["Title"]]) %>%
unlist %>%
stringr::str_replace(pattern = "\\n.+", replacement = "")
## latin1 encoded - containing umlaute!!
dataset_id <-
baseURL %>%
RCurl::getURL() %>%
stringr::str_match_all("meta.jsp[?]dataset=.+[\"\"]") %>% # only dataset ID
unlist() %>%
stringr::str_replace(pattern = "meta.jsp[?]dataset=", replacement = "") %>%
stringr::str_replace(pattern = "\"", replacement = "")
df <- data.frame(ID = dataset_id, Title = dataset_title)
knitr::kable(df[1:n_table, ])
|ID |Title |
|:------------------------|:--------------------------------------------------------------------------------------------|
|OGD_touextsai_Tour_HKL_1 |Nächtigungsstatistik ab November 1973 - Nächtigungen nach Herkunftsländern und Bundesländern |
|OGD_touextsai_Tour_UA_1 |Nächtigungsstatistik ab November 1973 - Nächtigungen nach Unterkunftsarten und Bundesländern |
|OGD_vpi10_VPI_2010_1 |Verbraucherpreisindex Basis 2010 |
|OGD_vpi05_VPI_2005_1 |Verbraucherpreisindex Basis 2005 |
|OGD_vpi15_VPI_2015_1 |Verbraucherpreisindex Basis 2015 |
bowerth/nsoApi documentation built on June 17, 2019, 4:55 a.m.
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title: "nsoApi" author: "Bo Werth" date: "2016-09-01" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Vignette Title} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8}
Providers
Some of the APIs require authentication:
|cou |provider |label |access | |:---|:--------|:------------------------------|:--------| |USA |BEA |Bureau of Economic Analysis |register | |NLD |CBS |Statistics Netherlands |free | |DEU |GENESIS |Destatis |paid | |GBR |ONS |Office for National Statistics |register | |NOR |SSB |Statistics Norway |free | |AUT |STATAT |Statistics Austria |free | |CAN |WDS |Statistics Canada |IP |
Setup
Create an R script containing a list with your keys or just modify the the example script and save it with gpg encryption at inst/apiKey.R.gpg.
apiKey <- list(
BEA = list(
userid = "29UG8ZKT-JN9R5N2Q")
,
GENESIS = list(
kennung = "8XXHKY78",
passwort = "3QYYTQ89")
,
ONS = list(
apikey = "k647uahw")
)
To prevent compromising the API keys, it is suggested to encrypt the file. If you are on Windows, you will need to install GnuPG first. The nsoApiGPG function allows to specify a directory to an executable using the gpg parameter.
file.apiKey.enc <- system.file("apiKey.R.gpg", package = "nsoApi")
nsoApi::nsoApiGPG(file = file.apiKey.enc,
gpg = NULL,
passphrase = Sys.getenv("NSOAPIGPG"),
keep = FALSE
)
## [1] TRUE
BEA Bureau of Economic Analysis
api.param <- list(
DATASETNAME = "GDPbyIndustry",
METHOD = "GETPARAMETERVALUES",
RESULTFORMAT = "JSON",
USERID = apiKey$BEA$userid,
PARAMETERNAME = "TABLEID"
)
tablelist <- beaAPI(api.param = api.param, curl = curl)
tablelist$BEAAPI$Request$RequestParam
## ParameterName ParameterValue
## 1 USERID 7023E825-15FF-488D-B8D9-D70E6F67D439
## 2 PARAMETERNAME TABLEID
## 3 DATASETNAME GDPBYINDUSTRY
## 4 RESULTFORMAT JSON
## 5 METHOD GETPARAMETERVALUES
Show first 5 tables
|Key |Desc | |:---|:-------------------------------------------------------------------------| |1 |Value Added by Industry (A) (Q) | |5 |Value Added by Industry as a Percentage of Gross Domestic Product (A) (Q) | |6 |Components of Value Added by Industry (A) | |7 |Components of Value Added by Industry as a Percentage of Value Added (A) | |8 |Chain-Type Quantity Indexes for Value Added by Industry (A) (Q) |
api.param <- list(
DATASETNAME = "GDPBYINDUSTRY",
FREQUENCY = "A",
INDUSTRY = "11",
METHOD = "GETDATA",
RESULTFORMAT = "JSON",
USERID = apiKey$BEA$userid,
TABLEID = "1",
YEAR = paste(as.character(c(2008:2015)), collapse = ",")
)
datalist <- beaAPI(api.param = api.param, curl = curl)
knitr::kable(datalist$BEAAPI$Results$Data)
|TableID |Frequency |Year |Quarter |Industry |IndustrYDescription |DataValue |NoteRef | |:-------|:---------|:----|:-------|:--------|:-------------------------------------------|:---------|:-------| |1 |A |2008 |2008 |11 |Agriculture, forestry, fishing, and hunting |154.5 |1 | |1 |A |2009 |2009 |11 |Agriculture, forestry, fishing, and hunting |137.7 |1 | |1 |A |2010 |2010 |11 |Agriculture, forestry, fishing, and hunting |160.2 |1 | |1 |A |2011 |2011 |11 |Agriculture, forestry, fishing, and hunting |197.2 |1 | |1 |A |2012 |2012 |11 |Agriculture, forestry, fishing, and hunting |185.8 |1 | |1 |A |2013 |2013 |11 |Agriculture, forestry, fishing, and hunting |225.4 |1 | |1 |A |2014 |2014 |11 |Agriculture, forestry, fishing, and hunting |215.4 |1 | |1 |A |2015 |2015 |11 |Agriculture, forestry, fishing, and hunting |196.0 |1 |
CBS Statistics Netherlands
First, we define the API URI and the dataset ID
api <- "http://opendata.cbs.nl/ODataApi/OData/"
DSD <- "82572ENG" # Input-Output: "83068ENG"
CBS Metadata
Next, we return the members of a dimension
scheme <- "SectorBranchesSIC2008"
## print query
cbsODataAPI(api=api, DSD=DSD, scheme=scheme, query=TRUE)
[1] "http://opendata.cbs.nl/ODataApi/OData/82572ENG/SectorBranchesSIC2008"
cbs_dimension <- cbsODataAPI(api=api, DSD=DSD, scheme=scheme, query=FALSE)
knitr::kable(cbs_dimension[1:n_table, 1:2])
|Key |Title | |:------|:-----------------------------------| |300025 |A-U All economic activities | |301000 |A Agriculture, forestry and fishing | |301100 |01 Agriculture | |304300 |02 Forestry and logging | |305000 |03 Fishing and aquaculture |
CBS Data
Finally, we return a dataset
scheme <- "TypedDataSet"
# print query
cbsODataAPI(api=api, DSD=DSD, scheme=scheme, query=TRUE)
[1] "http://opendata.cbs.nl/ODataApi/OData/82572ENG/TypedDataSet"
cbs_data <- cbsODataAPI(api=api, DSD=DSD, scheme=scheme, query=FALSE)
knitr::kable(cbs_data[1:n_table, 1:6])
| ID|SectorBranchesSIC2008 |Periods | OutputBasicPrices_1| IntermediateConsumption_2| GrossValueAddedBasicPrices_3| |--:|:---------------------|:--------|-------------------:|-------------------------:|----------------------------:| | 0|300025 |1995JJ00 | 587866| 292992| 294874| | 1|300025 |1996JJ00 | 624009| 316394| 307615| | 2|300025 |1997JJ00 | 671992| 343515| 328477| | 3|300025 |1998JJ00 | 714756| 364847| 349909| | 4|300025 |1999JJ00 | 762732| 390927| 371805|
CBS Tables
List existing tables in CBS API. This takes 1-2 minutes to complete
cbs_tables <- nsoApi::cbsODataTables()
knitr::kable(cbs_tables[1:n_table, ])
|Identifier |Title |Frequency |Period | |:----------|:--------------------------------------------------------------------------|:---------|:-------------| |82010NED |Zeggenschap bedrijven in Nederland; banen en lonen, bedrijfsgrootte |Perjaar |2008 t/m 2011 | |82011NED |Zeggenschap bedrijven in Nederland; banen en lonen, bedrijfstak (SBI 2008) |Perjaar |2008 t/m 2011 | |81179ned |Zeggenschap bedrijven in Nederland; banen en lonen (SBI'93) 2006-2008 |Stopgezet |2006-2008 | |81251ned |Banen werknemers en afstand woon-werk; woon- en werkregio's |Perjaar |2006 - 2014 | |80339ned |Banen van werknemers; bedrijfsgrootte en economische activiteit, 2006-2009 |Stopgezet |2006 - 2009 |
Destatis GENESIS
Genesis Metadata
api.param.datenexport <- list(
method = "DatenExport",
kennung = apiKey$GENESIS$kennung,
passwort = apiKey$GENESIS$passwort,
namen = "81000BJ002",
bereich = "oeffentlich",
format = "csv",
werte = "false",
metadaten = "false",
zusatz = "true",
startjahr = "2013",
endjahr = "2014",
zeitscheiben = "",
regionalschluessel = "",
sachmerkmal = "",
sachschluessel = "",
stand = "01.01.2001",
sprache = "de"
)
## retrieve metadata
xml_list_datenexport_meta <- genesisAPI(api.param = api.param.datenexport,
service = "ExportService",
curl = curl)
meta_df <- genesisXMLtoDF(xml.list = xml_list_datenexport_meta,
meta = TRUE)
knitr::kable(meta_df)
|code |label | |:------|:----------------------------------------------| |JAHR |Jahr | |DINSG |Deutschland insgesamt | |BWS001 |Bruttowertschöpfung | |VGRPB5 |Preisbasis (jeweilige Preise / preisbereinigt) | |WZ08G2 |WZ2008: Wirtschaftsbereiche der VGR |
|code |label | |:---------|:--------------------------------------------------| |DG |Deutschland | |VGRJPM |in jeweiligen Preisen (Mrd. EUR) | |VGRPKM |preisbereinigt, Kettenindex (2010=100) | |WZ08-A |Land- und Forstwirtschaft, Fischerei | |WZ08-B-18 |Produzierendes Gewerbe ohne Baugewerbe | |WZ08-C |Verarbeitendes Gewerbe | |WZ08-F |Baugewerbe | |WZ08-G-01 |Handel, Verkehr, Gastgewerbe | |WZ08-J |Information und Kommunikation | |WZ08-K |Erbringung von Finanz- und Versicherungsleistungen | |WZ08-L |Grundstücks- und Wohnungswesen | |WZ08-M-02 |Unternehmensdienstleister | |WZ08-O-03 |Öffentliche Dienstleister, Erziehung, Gesundheit | |WZ08-R-02 |Sonstige Dienstleister |
Genesis Data
api.param.datenexport <- list(
method = "DatenExport",
kennung = apiKey$GENESIS$kennung,
passwort = apiKey$GENESIS$passwort,
namen = "81000BJ002",
bereich = "oeffentlich",
format = "csv",
werte = "true",
metadaten = "false",
zusatz = "false",
startjahr = "2013",
endjahr = "2014",
zeitscheiben = "",
regionalschluessel = "",
sachmerkmal = "",
sachschluessel = "",
stand = "01.01.2001",
sprache = "de"
)
## retrieve data
xml_list_datenexport <- genesisAPI(api.param = api.param.datenexport,
service = "ExportService",
curl = curl)
## convert to data frame
data_df <- genesisXMLtoDF(xml.list = xml_list_datenexport)
knitr::kable(data_df[1:n_table,])
|VGRPB5 |WZ08G2 |DINSG | ZI-WERT|UNIT | WERT| |:------|:---------|:-----|-------:|:------|-------:| |VGRJPM |WZ08-A |DG | 2013|BWS001 | 24.005| |VGRJPM |WZ08-B-18 |DG | 2013|BWS001 | 654.188| |VGRJPM |WZ08-C |DG | 2013|BWS001 | 572.186| |VGRJPM |WZ08-F |DG | 2013|BWS001 | 113.247| |VGRJPM |WZ08-G-01 |DG | 2013|BWS001 | 395.395|
Genesis Tables
genesis_tables <- nsoApi::genesisTables(
namefilter = 11, # for testing - takes a few minutes to complete
## namefilter = c(11:14, 2, 3, 41:49, 5:9),
fields = c("code", "beschriftungstext"),
kennung = apiKey$GENESIS$kennung,
passwort = apiKey$GENESIS$passwort
)
"11*" filter: 4 entries
genesis_tables$beschriftungstext <- gsub("\n", " ", genesis_tables$beschriftungstext)
knitr::kable(genesis_tables)
|code |beschriftungstext | |:----------|:-----------------------------------------------------------------------------| |11111BJ001 |Feststellung des Gebietsstands, Gebietsflche, Deutschland insgesamt, Stichtag | |11111KJ001 |Feststellung des Gebietsstands, Gebietsflche, Kreise, Stichtag | |11111LJ001 |Feststellung des Gebietsstands, Gebietsflche, Bundeslnder, Stichtag | |NA |NA |
ONS UK Office for National Statistics
ONS Data
api.param <- list(context = "Census",
geog = "2011WARDH",
totals = "false",
apikey = "xPuqnMzZ01")
ons_data <- onsCsvData(api.param = api.param, dataset = "QS208EW")
knitr::kable(ons_data[1:n_table, 1:7])
|geographic_id | total_all_categories_religion| christian| buddhist| hindu| jewish| muslim| |:-------------|-----------------------------:|---------:|--------:|------:|------:|-------:| |K04000001 | 56075912| 33243175| 247743| 816633| 263346| 2706066| |E92000001 | 53012456| 31479876| 238626| 806199| 261282| 2660116| |W92000004 | 3063456| 1763299| 9117| 10434| 2064| 45950| |E12000001 | 2596886| 1753334| 6316| 7772| 4503| 46764| |E12000002 | 7052177| 4742860| 20695| 38259| 30417| 356458|
ONS Tables
ons_tables <- onsAPI(method = "contexts", api.key = apiKey$ONS$apikey)
knitr::kable(ons_tables)
| contextId|contextName | |---------:|:--------------| | 1|Census | | 2|Socio-Economic | | 3|Economic | | 4|Social |
ons_collections <- onsAPI(method = "collections", context = "Economic", api.key = apiKey$ONS$apikey)
titles <- sapply(ons_collections$name[, 1], function(x) x[1, 2])
titles <- iconv(titles, "latin1", "ASCII", sub="")
ons_collections_df <- data.frame(ID = ons_collections$id, Title = titles)
knitr::kable(ons_collections_df[1:n_table, ])
|ID |Title | |:--------|:-------------------------------------------------------| |A02Level |Labour Force Survey Summary Levels (Explorable Dataset) | |A02Rate |Labour Force Survey Summary Rates (Explorable Dataset) | |ABS |Annual Business Survey | |ABS1 |Annual Business Survey | |ASHE07E |Earnings by place of work |
STATAT Statistics Austria
STATAT Data
dataset <- "OGD_vgr001_VGRJahresR_1"
statat_data <- statatAPI(dataset = dataset)
## Warning: attributes are not identical across measure variables; they will
## be dropped
knitr::kable(statat_data[1:n_table, ])
|date |C_VGRW04_0 |variable | value| |:--------|:----------|:-----------|-------:| |A10-1976 |VGRW04-1 |F_ISIS_4575 | 41853.8| |A10-1976 |VGRW04-2 |F_ISIS_4575 | 14974.9| |A10-1976 |VGRW04-3 |F_ISIS_4575 | 16556.6| |A10-1976 |VGRW04-4 |F_ISIS_4575 | 17803.1| |A10-1976 |VGRW04-5 |F_ISIS_4575 | -150.7|
baseURL <- "http://data.statistik.gv.at/web/catalog.jsp"
dataset_title <-
baseURL %>%
RCurl::getURL() %>%
XML::htmlParse(baseURL) %>%
XML::readHTMLTable() %>%
lapply(function(x) x[["Title"]]) %>%
unlist %>%
stringr::str_replace(pattern = "\\n.+", replacement = "")
## latin1 encoded - containing umlaute!!
dataset_id <-
baseURL %>%
RCurl::getURL() %>%
stringr::str_match_all("meta.jsp[?]dataset=.+[\"\"]") %>% # only dataset ID
unlist() %>%
stringr::str_replace(pattern = "meta.jsp[?]dataset=", replacement = "") %>%
stringr::str_replace(pattern = "\"", replacement = "")
df <- data.frame(ID = dataset_id, Title = dataset_title)
knitr::kable(df[1:n_table, ])
|ID |Title | |:------------------------|:--------------------------------------------------------------------------------------------| |OGD_touextsai_Tour_HKL_1 |Nächtigungsstatistik ab November 1973 - Nächtigungen nach Herkunftsländern und Bundesländern | |OGD_touextsai_Tour_UA_1 |Nächtigungsstatistik ab November 1973 - Nächtigungen nach Unterkunftsarten und Bundesländern | |OGD_vpi10_VPI_2010_1 |Verbraucherpreisindex Basis 2010 | |OGD_vpi05_VPI_2005_1 |Verbraucherpreisindex Basis 2005 | |OGD_vpi15_VPI_2015_1 |Verbraucherpreisindex Basis 2015 |
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