PX-WEB API Interface for R

Available data sources and tools

A number of organizations use PXWEB to distribute hierarchical data. You can browse the available data sets at:

• Statistics Sweden with API Description
• Statistics Finland StatFi API Description
• Other organizations using PX-WEB

About PXWEB APIs

The data in PXWEB APIs consists of metadata and data parts. Metadata is structured in a hierarchical node tree, where each node contains information about subnodes. The leaf nodes have information on which the dimensions are available for the data at that leaf node.

Installation issues

We also recommend setting the UTF-8 encoding since each API may have local specific letters:

Sys.setlocale(locale = "UTF-8")

Creating data queries

To download data, we need both the URL to the table and a query specifying what parts of the table are of interest. An URL to a table is an URL that will return a metadata object if not a query is supplied. Creating a query can be done in three main ways. The first and most straightforward approach is to use pxweb_interactive() to explore the table URL and create a query interactively.

d <- pxweb_interactive("https://api.scb.se/OV0104/v1/doris/en/ssd/BE/BE0101/BE0101A/BefolkningNy")

The interactive function will return the query and the URL, even if the data is not downloaded.

d$url

## [1] "http://api.scb.se/OV0104/v1/doris/en/ssd/BE/BE0101/BE0101A/BefolkningNy"

d$query

## PXWEB QUERY
## query:
##  [[1]] Region (item):
##    00
##  [[2]] Civilstand (item):
##    OG, G, ÄNKL, SK
##  [[3]] Alder (item):
##    tot
##  [[4]] ContentsCode (item):
##    BE0101N1
##  [[5]] Tid (item):
##    2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017

We can also turn the query into a JSON query that we can use outside R.

pxweb_query_as_json(d$query, pretty = TRUE)

## {
##   "query": [
##     {
##       "code": "Region",
##       "selection": {
##         "filter": "item",
##         "values": ["00"]
##       }
##     },
##     {
##       "code": "Civilstand",
##       "selection": {
##         "filter": "item",
##         "values": ["OG", "G", "ÄNKL", "SK"]
##       }
##     },
##     {
##       "code": "Alder",
##       "selection": {
##         "filter": "item",
##         "values": ["tot"]
##       }
##     },
##     {
##       "code": "ContentsCode",
##       "selection": {
##         "filter": "item",
##         "values": ["BE0101N1"]
##       }
##     },
##     {
##       "code": "Tid",
##       "selection": {
##         "filter": "item",
##         "values": ["2010", "2011", "2012", "2013", "2014", "2015", "2016", "2017"]
##       }
##     }
##   ],
##   "response": {
##     "format": "json"
##   }
## }

The second approach is to specify the query either as an R list or a JSON object. Some Statistical Agencies, such as Statistics Sweden, supply queries directly as a JSON object on their web pages. We can use these queries directly. Below is another example of a JSON query for the table above. For details on setting up a JSON query, see the PXWEB API documentation.

{
  "query": [
    {
      "code": "Civilstand",
      "selection": {
        "filter": "item",
        "values": ["OG", "G", "ÄNKL", "SK"]
      }
    },
    {
      "code": "Kon",
      "selection": {
        "filter": "item",
        "values": ["1", "2"]
      }
    },
    {
      "code": "ContentsCode",
      "selection": {
        "filter": "item",
        "values": ["BE0101N1"]
      }
    },
    {
      "code": "Tid",
      "selection": {
        "filter": "item",
        "values": ["2015", "2016", "2017"]
      }
    }
  ],
  "response": {
    "format": "json"
  }
} 

To use this JSON query, we store the JSON query as a file and supply the path to the file to the “pxweb_query()”function.

pxq <- pxweb_query("path/to/the/json/query.json")

Finally, we can create a PXWEB query from an R list where each list element is a variable and selected observation.

pxweb_query_list <-
  list(
    "Civilstand" = c("*"), # Use "*" to select all
    "Kon" = c("1", "2"),
    "ContentsCode" = c("BE0101N1"),
    "Tid" = c("2015", "2016", "2017")
  )
pxq <- pxweb_query(pxweb_query_list)
pxq

## PXWEB QUERY
## query:
##  [[1]] Civilstand (all):
##    *
##  [[2]] Kon (item):
##    1, 2
##  [[3]] ContentsCode (item):
##    BE0101N1
##  [[4]] Tid (item):
##    2015, 2016, 2017

We can validate the query against the metadata object to asses that we can use the query. This validation is done automatically when the data is fetched with pxweb_get() but can also be done manually.

pxweb_validate_query_with_metadata(pxq, px_meta)

Downloading data

When we have the URL to a data table and a query, we can download the data with “pxweb_get()”. The function returns a pxweb_data object that contains the downloaded data.

pxd <- pxweb_get(
  "https://api.scb.se/OV0104/v1/doris/en/ssd/BE/BE0101/BE0101A/BefolkningNy",
  pxq
)
pxd

## PXWEB DATA
## With 4 variables and 24 observations.

If we instead want a JSON-stat object, we change the response format to JSON-stat, and we will get a JSON-stat object returned.

pxq$response$format <- "json-stat"
pxjstat <- pxweb_get(
  "https://api.scb.se/OV0104/v1/doris/en/ssd/BE/BE0101/BE0101A/BefolkningNy",
  pxq
)
pxjstat

## {
##   "dataset": {
##     "dimension": {
##       "Civilstand": {
##         "label": ["marital status"],
##         "category": {
##           "index": {
##             "OG": [0],
##             "G": [1],
##             "ÄNKL": [2],
##             "SK": [3]
##           },
##           "label": {
##             "OG": ["single"],
##             "G": ["married"],
##             "ÄNKL": ["widowers/widows"],
##             "SK": ["divorced"]
##           }
##         },
##         "extension": {
##           "show": ["value"]
##         }
##       },
##       "Kon": {
##         "label": ["sex"],
##         "category": {
##           "index": {
##             "1": [0],
##             "2": [1]
##           },
##           "label": {
##             "1": ["men"],
##             "2": ["women"]
##           }
##         },
##         "link": {
##           "describedby": [
##             {
##               "extension": {
##                 "Kon": ["Kön"]
##               }
##             }
##           ]
##         },
##         "extension": {
##           "show": ["value"]
##         }
##       },
##       "ContentsCode": {
##         "label": ["observations"],
##         "category": {
##           "index": {
##             "BE0101N1": [0]
##           },
##           "label": {
##             "BE0101N1": ["Population"]
##           },
##           "unit": {
##             "BE0101N1": {
##               "base": ["number"],
##               "decimals": [0]
##             }
##           }
##         },
##         "extension": {
##           "show": ["value"]
##         }
##       },
##       "Tid": {
##         "label": ["year"],
##         "category": {
##           "index": {
##             "2015": [0],
##             "2016": [1],
##             "2017": [2]
##           },
##           "label": {
##             "2015": ["2015"],
##             "2016": ["2016"],
##             "2017": ["2017"]
##           }
##         },
##         "extension": {
##           "show": ["code"]
##         }
##       },
##       "id": [
##         ["Civilstand"],
##         ["Kon"],
##         ["ContentsCode"],
##         ["Tid"]
##       ],
##       "size": [
##         [4],
##         [2],
##         [1],
##         [3]
##       ],
##       "role": {
##         "metric": [
##           ["ContentsCode"]
##         ],
##         "time": [
##           ["Tid"]
##         ]
##       }
##     },
##     "label": ["Population by marital status, sex, observations and year"],
##     "source": ["Statistics Sweden"],
##     "updated": ["2023-02-09T07:57:00Z"],
##     "value": [
##       [2762601],
##       [2820248],
##       [2870477],
##       [2394842],
##       [2437315],
##       [2477012],
##       [1651482],
##       [1672460],
##       [1687016],
##       [1639519],
##       [1657129],
##       [1671381],
##       [99751],
##       [99654],
##       [99682],
##       [345008],
##       [340709],
##       [335961],
##       [417132],
##       [420985],
##       [425487],
##       [540682],
##       [546653],
##       [553226]
##     ],
##     "extension": {
##       "px": {
##         "infofile": ["BE0101"],
##         "tableid": ["TAB638"],
##         "decimals": [0]
##       }
##     }
##   }
## }

Some return formats return files. Then, these responses are stored in the R tempdir() folded, and the file paths are returned by pxweb_get(). Currently, px and sdmx formats can be downloaded as files, but file an issue if you need other response formats.

pxq$response$format <- "px"
pxfp <- pxweb_get(
  "https://api.scb.se/OV0104/v1/doris/en/ssd/BE/BE0101/BE0101A/BefolkningNy",
  pxq
)
pxfp

## [1] "/var/folders/x9/dsgck_4s5mx2nrzzs8zd64rc0000gq/T//RtmpFdmiD7/50026bd2b2d8df2e3f190ca568b3b587d8207465.px"

If the queries are large (contain more values than the PXWEB API maximum allowed values), the query is chunked into optimal chunks and is then downloaded sequentially. PXWEB data objects are then combined into one large PXWEB data object, while JSON-stat objects are returned as a list of JSON-stat objects, and other files are stored in tempdir() as separate files.

For more advanced connections to the API, the pxweb_advanced_get() gives the flexibility to access the underlying HTTP calls using httr and log the HTTP calls for debugging.

We can then convert the downloaded PXWEB data objects to a data. frame or to a character matrix. The character matrix contains the “raw” data while data. frame returns an R data.frame in a tidy format. This conversion means missing values (such as “..” are converted to NA) in a data. frame. Using the arguments variable.value.type and column.name.type, we can choose if we want the code or the text column names and value types.

pxdf <- as.data.frame(pxd, column.name.type = "text", variable.value.type = "text")
head(pxdf)

##   marital status   sex year Population
## 1         single   men 2015    2762601
## 2         single   men 2016    2820248
## 3         single   men 2017    2870477
## 4         single women 2015    2394842
## 5         single women 2016    2437315
## 6         single women 2017    2477012

pxdf <- as.data.frame(pxd, column.name.type = "code", variable.value.type = "code")
head(pxdf)

##   Civilstand Kon  Tid BE0101N1
## 1         OG   1 2015  2762601
## 2         OG   1 2016  2820248
## 3         OG   1 2017  2870477
## 4         OG   2 2015  2394842
## 5         OG   2 2016  2437315
## 6         OG   2 2017  2477012

Similarly, we can access the raw data as a character matrix with as.matrix.

pxmat <- as.matrix(pxd, column.name.type = "code", variable.value.type = "code")
head(pxmat)

##      Civilstand Kon Tid    BE0101N1 
## [1,] "OG"       "1" "2015" "2762601"
## [2,] "OG"       "1" "2016" "2820248"
## [3,] "OG"       "1" "2017" "2870477"
## [4,] "OG"       "2" "2015" "2394842"
## [5,] "OG"       "2" "2016" "2437315"
## [6,] "OG"       "2" "2017" "2477012"

Access data footnotes/comments

In addition to the data, the PXWEB DATA object may also contain comments for the data. This can be accessed using pxweb_data_comments() function.

pxdc <- pxweb_data_comments(pxd)
pxdc

## NO PXWEB DATA COMMENTS

In this case, we did not have any comments. If we have comments, we can turn the comments into a data. frame with one comment per row.

as.data.frame(pxdc)