od_table(id) returns an R6-class object containing all relevant data
and metadata from https://data.statistik.gv.at/data/
Value
The returned objects is of class sc_table and inherits several parsing
methods from sc_data. See od_table_class for the full class
documentation.
Components
| Component | Corresponding File on Server |
$data | https://data.statistik.gv.at/data/${id}.csv |
$header | https://data.statistik.gv.at/data/${id}_HEADER.csv |
$field(code) | https://data.statistik.gv.at/data/${id}_${code}.csv |
$json | https://data.statistik.gv.at/ogd/json?dataset=${id} |
Examples
x <- od_table("OGD_krebs_ext_KREBS_1")
## metadata
x
#> Cancer statistics by reporting year, province of residence and
#> localisation of cancer
#>
#> Dataset: OGD_krebs_ext_KREBS_1 (data.statistik.gv.at)
#> Measures: Number of records F-KRE
#> Fields: Tumore ICD/10 3-Steller <98>, Reporting year <40>, Province
#> of residence <9>, Sex <2>
#>
#> Request: [2024-11-29 09:52:04.146076]
#> STATcubeR: 1.0.0
x$meta
#> $source
#> # STATcubeR metadata: 1 x 7
#> code label lang
#> <chr> <chr> <chr>
#> 1 OGD_krebs_ext_KREBS_1 Cancer statistics by reporting year, pr… en
#> # … with 4 more columns: 'label_de', 'label_en', 'requested', 'scr_version'
#>
#> $measures
#> # STATcubeR metadata: 1 x 7
#> code label NAs
#> <chr> <chr> <int>
#> 1 F-KRE Number of records F-KRE 0
#> # … with 4 more columns: 'label_de', 'label_en', 'de_desc', 'en_desc'
#>
#> $fields
#> # STATcubeR metadata: 4 x 9
#> code label total_code nitems type
#> <chr> <chr> <chr> <int> <chr>
#> 1 C-TUM_ICD10_3ST-0 Tumore ICD/10 3-Steller NA 98 Catego…
#> 2 C-BERJ-0 Reporting year NA 40 Time (…
#> 3 C-BUNDESLAND-0 Province of residence NA 9 Catego…
#> 4 C-KRE_GESCHLECHT-0 Sex NA 2 Catego…
#> # … with 4 more columns: 'label_de', 'label_en', 'de_desc', 'en_desc'
#>
x$field("Sex")
#> # STATcubeR metadata: 2 x 10
#> code label parsed
#> <chr> <chr> <chr>
#> 1 GESCHLECHT-1 male male
#> 2 GESCHLECHT-2 female female
#> # … with 7 more columns: 'label_de', 'label_en', 'parent', 'de_desc', 'en_desc', 'visible', 'order'
x$field(3)
#> # STATcubeR metadata: 9 x 10
#> code label parsed
#> <chr> <chr> <chr>
#> 1 BUNDESLAND-1 "Burgenland " "Burgenland "
#> 2 BUNDESLAND-2 "Carinthia" "Carinthia"
#> 3 BUNDESLAND-3 "Lower Austria" "Lower Austria"
#> 4 BUNDESLAND-4 "Upper Austria" "Upper Austria"
#> 5 BUNDESLAND-5 "Salzburg" "Salzburg"
#> 6 BUNDESLAND-6 "Styria" "Styria"
#> 7 BUNDESLAND-7 "Tyrol" "Tyrol"
#> 8 BUNDESLAND-8 "Vorarlberg" "Vorarlberg"
#> 9 BUNDESLAND-9 "Vienna" "Vienna"
#> # … with 7 more columns: 'label_de', 'label_en', 'parent', 'de_desc', 'en_desc', 'visible', 'order'
## data
x$data
#> # A STATcubeR tibble: 49,190 x 5
#> `C-TUM_ICD10_3ST-0` `C-BERJ-0` `C-BUNDESLAND-0`
#> * <fct> <fct> <fct>
#> 1 TUM_ICD10_3ST-C00 BERJ-1983 BUNDESLAND-1
#> 2 TUM_ICD10_3ST-C00 BERJ-1983 BUNDESLAND-2
#> 3 TUM_ICD10_3ST-C00 BERJ-1983 BUNDESLAND-2
#> 4 TUM_ICD10_3ST-C00 BERJ-1983 BUNDESLAND-3
#> 5 TUM_ICD10_3ST-C00 BERJ-1983 BUNDESLAND-3
#> 6 TUM_ICD10_3ST-C00 BERJ-1983 BUNDESLAND-4
#> 7 TUM_ICD10_3ST-C00 BERJ-1983 BUNDESLAND-4
#> 8 TUM_ICD10_3ST-C00 BERJ-1983 BUNDESLAND-5
#> 9 TUM_ICD10_3ST-C00 BERJ-1983 BUNDESLAND-6
#> 10 TUM_ICD10_3ST-C00 BERJ-1983 BUNDESLAND-6
#> # ℹ 49,180 more rows
#> # ℹ 2 more variables: `C-KRE_GESCHLECHT-0` <fct>, `F-KRE` <int>
x$tabulate()
#> # A STATcubeR tibble: 49,190 x 5
#> `Tumore ICD/10 3-Steller` `Reporting year` Province of residenc…¹
#> * <fct> <date> <fct>
#> 1 <C00> Bösartige Neubildung… 1983-01-01 "Burgenland "
#> 2 <C00> Bösartige Neubildung… 1983-01-01 "Carinthia"
#> 3 <C00> Bösartige Neubildung… 1983-01-01 "Carinthia"
#> 4 <C00> Bösartige Neubildung… 1983-01-01 "Lower Austria"
#> 5 <C00> Bösartige Neubildung… 1983-01-01 "Lower Austria"
#> 6 <C00> Bösartige Neubildung… 1983-01-01 "Upper Austria"
#> 7 <C00> Bösartige Neubildung… 1983-01-01 "Upper Austria"
#> 8 <C00> Bösartige Neubildung… 1983-01-01 "Salzburg"
#> 9 <C00> Bösartige Neubildung… 1983-01-01 "Styria"
#> 10 <C00> Bösartige Neubildung… 1983-01-01 "Styria"
#> # ℹ 49,180 more rows
#> # ℹ abbreviated name: ¹`Province of residence`
#> # ℹ 2 more variables: Sex <fct>, `Number of records F-KRE` <int>
## tabulation: see `?sc_tabulate` for more examples
x$tabulate("Reporting year", "Sex")
#> # A STATcubeR tibble: 80 x 3
#> `Reporting year` Sex `Number of records F-KRE`
#> * <date> <fct> <int>
#> 1 1983-01-01 male 13626
#> 2 1983-01-01 female 16702
#> 3 1984-01-01 male 13996
#> 4 1984-01-01 female 16620
#> 5 1985-01-01 male 13658
#> 6 1985-01-01 female 16487
#> 7 1986-01-01 male 13592
#> 8 1986-01-01 female 16173
#> 9 1987-01-01 male 13957
#> 10 1987-01-01 female 16724
#> # ℹ 70 more rows
## switch language
x$language <- "de"
x
#> Krebsstatistik
#>
#> Dataset: OGD_krebs_ext_KREBS_1 (data.statistik.gv.at)
#> Measures: Anzahl der Datensätze F-KRE
#> Fields: Tumore ICD/10 3-Steller <98>, Berichtsjahr <40>, Bundesland
#> <9>, Geschlecht <2>
#>
#> Request: [2024-11-29 09:52:04.146076]
#> STATcubeR: 1.0.0
x$tabulate()
#> # A STATcubeR tibble: 49,190 x 5
#> `Tumore ICD/10 3-Steller` Berichtsjahr Bundesland Geschlecht
#> * <fct> <date> <fct> <fct>
#> 1 <C00> Bösartige Neubildung der … 1983-01-01 Burgenland männlich
#> 2 <C00> Bösartige Neubildung der … 1983-01-01 Kärnten männlich
#> 3 <C00> Bösartige Neubildung der … 1983-01-01 Kärnten weiblich
#> 4 <C00> Bösartige Neubildung der … 1983-01-01 Niederöst… männlich
#> 5 <C00> Bösartige Neubildung der … 1983-01-01 Niederöst… weiblich
#> 6 <C00> Bösartige Neubildung der … 1983-01-01 Oberöster… männlich
#> 7 <C00> Bösartige Neubildung der … 1983-01-01 Oberöster… weiblich
#> 8 <C00> Bösartige Neubildung der … 1983-01-01 Salzburg männlich
#> 9 <C00> Bösartige Neubildung der … 1983-01-01 Steiermark männlich
#> 10 <C00> Bösartige Neubildung der … 1983-01-01 Steiermark weiblich
#> # ℹ 49,180 more rows
#> # ℹ 1 more variable: `Anzahl der Datensätze F-KRE` <int>
## other interesting tables
od_table("OGD_veste309_Veste309_1")
#> Structure of Earnings Survey (SES) 2018 Gross hourly earnings
#> in EUR by citizenship, region (NUTS 2) and form of employment
#>
#> Dataset: OGD_veste309_Veste309_1 (data.statistik.gv.at)
#> Measures: Arithmetic mean, 1st quartile, 2nd quartile (median), 3rd
#> quartile, Number of employees
#> Fields: Sex <3>, Citizenship <9>, Region (NUTS2) <10>, Form of
#> employment <7>
#>
#> Request: [2024-11-29 09:52:04.371603]
#> STATcubeR: 1.0.0
od_table("OGD_konjunkturmonitor_KonMon_1")
#> Economic Trend Monitor
#>
#> Dataset: OGD_konjunkturmonitor_KonMon_1 (data.statistik.gv.at)
#> Measures: Production index industry (wd; 2021=100), Technical total
#> production industry (in 1.000 €), Turnover index industry
#> (2021=100), Turnover industry (in 1.000 €), Index of new orders
#> industry (2021=100), Index of persons employed industry (2021=100),
#> Persons employed industry, Productivity index industry per employee
#> (2021=100), Productivity index industry per hours worked
#> (2021=100), Industrial output price index (2021=100), … (78 more)
#> Fields: reporting period <270>, value indication <3>
#>
#> Request: [2024-11-29 09:52:04.421465]
#> STATcubeR: 1.0.0
od_table("OGD_krankenbewegungen_ex_LEISTUNGEN_1")
#> Medical procedures during inpatient stays since 1989 by
#> patient characteristics (number of medical procedures)
#>
#> Dataset: OGD_krankenbewegungen_ex_LEISTUNGEN_1 (data.statistik.gv.at)
#> Measures: Medical procedures
#> Fields: Year of discharge <32>, Sex <2>, Age (four classes) <4>,
#> NUTS-2 region (place of residence) <12>, Medical procedures -
#> subchapters <115>
#>
#> Request: [2024-11-29 09:52:06.965219]
#> STATcubeR: 1.0.0
od_table("OGD_veste303_Veste203_1")
#> Structure of Earnings Survey (SES) 2018 Gross hourly earnings
#> in EUR by characteristics of the enterprise
#>
#> Dataset: OGD_veste303_Veste203_1 (data.statistik.gv.at)
#> Measures: Arithmetic mean, 1st quartile, 2nd quartile (median), 3rd
#> quartile, Number of employees
#> Fields: ÖNACE 2008 (NACE Rev.2) <97>, Sex <3>, Regions (Nuts1) <4>,
#> Size of the enterprise <6>
#>
#> Request: [2024-11-29 09:52:15.223783]
#> STATcubeR: 1.0.0