Fetch GHO Data

Retrieves observations for a specific indicator from the WHO GHO OData API, with optional filters by spatial level, country / region and year range.

Usage

gho_data(
  indicator,
  spatial_type = NULL,
  area = NULL,
  year_from = NULL,
  year_to = NULL,
  dim1 = NULL,
  dim2 = NULL,
  dim3 = NULL
)

Arguments

indicator: Character scalar. The indicator code (e.g. "NCDMORT3070"). Use gho_indicators() to find codes.
spatial_type: Character. Spatial dimension to filter on: one of "country", "region", "global", or NULL (all levels, the default).
area: Character vector of country or region codes (e.g. c("FRA", "DEU")). Default NULL returns all areas.
year_from: Numeric. Start year filter (inclusive). Default NULL.
year_to: Numeric. End year filter (inclusive). Default NULL.
dim1, dim2, dim3: Character vector of values to keep for the Dim1 / Dim2 / Dim3 breakdown columns, filtered server-side (e.g. dim1 = "SEX_BTSX" for both-sexes rows only, or dim1 = c("SEX_MLE", "SEX_FMLE")). The meaning of each dimension varies by indicator (Dim1 is sex for one indicator, an age group for another); use gho_dimensions() to discover the values available for a given indicator. Rows where the dimension is empty (null) are excluded by the filter. Default NULL (no filtering).

Value

A tibble of indicator observations, or an empty tibble when the service is unreachable.

Examples

# \donttest{
# Country-level data for one indicator
gho_data("NCDMORT3070", spatial_type = "country")
#> Fetching:
#> <https://ghoapi.azureedge.net/api/NCDMORT3070?$filter=SpatialDimType%20eq%20%27COUNTRY%27>
#> Waiting 2s for retry backoff ■■■■■■■■■■■■■■■                 
#> Waiting 2s for retry backoff ■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■  
#> # A tibble: 12,210 × 25
#>       Id IndicatorCode SpatialDimType SpatialDim TimeDimType ParentLocationCode
#>    <int> <chr>         <chr>          <chr>      <chr>       <chr>             
#>  1  3710 NCDMORT3070   COUNTRY        AGO        YEAR        AFR               
#>  2  4415 NCDMORT3070   COUNTRY        GMB        YEAR        AFR               
#>  3  4932 NCDMORT3070   COUNTRY        LKA        YEAR        SEAR              
#>  4  5503 NCDMORT3070   COUNTRY        KHM        YEAR        WPR               
#>  5  7878 NCDMORT3070   COUNTRY        ZWE        YEAR        AFR               
#>  6  7882 NCDMORT3070   COUNTRY        GMB        YEAR        AFR               
#>  7  7921 NCDMORT3070   COUNTRY        BRA        YEAR        AMR               
#>  8  9385 NCDMORT3070   COUNTRY        AFG        YEAR        EMR               
#>  9  9395 NCDMORT3070   COUNTRY        MUS        YEAR        AFR               
#> 10  9562 NCDMORT3070   COUNTRY        KWT        YEAR        EMR               
#> # ℹ 12,200 more rows
#> # ℹ 19 more variables: ParentLocation <chr>, Dim1Type <chr>, Dim1 <chr>,
#> #   TimeDim <int>, Dim2Type <chr>, Dim2 <chr>, Dim3Type <lgl>, Dim3 <lgl>,
#> #   DataSourceDimType <lgl>, DataSourceDim <lgl>, Value <chr>,
#> #   NumericValue <dbl>, Low <dbl>, High <dbl>, Comments <chr>, Date <chr>,
#> #   TimeDimensionValue <chr>, TimeDimensionBegin <chr>, TimeDimensionEnd <chr>

# Specific countries and years
gho_data("WHOSIS_000001", area = c("FRA", "DEU"), year_from = 2015)
#> Assuming `spatial_type` = "country" since `area` was given.
#> ℹ Pass `spatial_type` explicitly to silence this message.
#> Fetching:
#> <https://ghoapi.azureedge.net/api/WHOSIS_000001?$filter=SpatialDimType%20eq%20%27COUNTRY%27%20and%20SpatialDim%20in%20%28%27FRA%27%2C%27DEU%27%29%20and%20TimeDim%20ge%202015>
#> # A tibble: 42 × 25
#>        Id IndicatorCode SpatialDimType SpatialDim TimeDimType ParentLocationCode
#>     <int> <chr>         <chr>          <chr>      <chr>       <chr>             
#>  1 8.84e5 WHOSIS_000001 COUNTRY        DEU        YEAR        EUR               
#>  2 9.64e5 WHOSIS_000001 COUNTRY        DEU        YEAR        EUR               
#>  3 1.77e6 WHOSIS_000001 COUNTRY        FRA        YEAR        EUR               
#>  4 2.06e6 WHOSIS_000001 COUNTRY        FRA        YEAR        EUR               
#>  5 2.33e6 WHOSIS_000001 COUNTRY        FRA        YEAR        EUR               
#>  6 3.15e6 WHOSIS_000001 COUNTRY        DEU        YEAR        EUR               
#>  7 3.28e6 WHOSIS_000001 COUNTRY        FRA        YEAR        EUR               
#>  8 3.39e6 WHOSIS_000001 COUNTRY        FRA        YEAR        EUR               
#>  9 3.64e6 WHOSIS_000001 COUNTRY        FRA        YEAR        EUR               
#> 10 4.21e6 WHOSIS_000001 COUNTRY        DEU        YEAR        EUR               
#> # ℹ 32 more rows
#> # ℹ 19 more variables: ParentLocation <chr>, Dim1Type <chr>, TimeDim <int>,
#> #   Dim1 <chr>, Dim2Type <lgl>, Dim2 <lgl>, Dim3Type <lgl>, Dim3 <lgl>,
#> #   DataSourceDimType <lgl>, DataSourceDim <lgl>, Value <chr>,
#> #   NumericValue <dbl>, Low <dbl>, High <dbl>, Comments <lgl>, Date <chr>,
#> #   TimeDimensionValue <chr>, TimeDimensionBegin <chr>, TimeDimensionEnd <chr>

# Keep only the both-sexes breakdown, filtered server-side
gho_data("NCDMORT3070", spatial_type = "country", dim1 = "SEX_BTSX")
#> Fetching:
#> <https://ghoapi.azureedge.net/api/NCDMORT3070?$filter=SpatialDimType%20eq%20%27COUNTRY%27%20and%20Dim1%20in%20%28%27SEX_BTSX%27%29>
#> Waiting 2s for retry backoff ■■■■■■■■■■■■■■■                 
#> Waiting 2s for retry backoff ■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■  
#> Waiting 4s for retry backoff ■■■■■■■■                        
#> Waiting 4s for retry backoff ■■■■■■■■■■■■                    
#> Waiting 4s for retry backoff ■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■  
#> # A tibble: 4,070 × 25
#>       Id IndicatorCode SpatialDimType SpatialDim TimeDimType ParentLocationCode
#>    <int> <chr>         <chr>          <chr>      <chr>       <chr>             
#>  1  4932 NCDMORT3070   COUNTRY        LKA        YEAR        SEAR              
#>  2  7878 NCDMORT3070   COUNTRY        ZWE        YEAR        AFR               
#>  3  7921 NCDMORT3070   COUNTRY        BRA        YEAR        AMR               
#>  4  9385 NCDMORT3070   COUNTRY        AFG        YEAR        EMR               
#>  5  9562 NCDMORT3070   COUNTRY        KWT        YEAR        EMR               
#>  6 12240 NCDMORT3070   COUNTRY        BGR        YEAR        EUR               
#>  7 12244 NCDMORT3070   COUNTRY        SOM        YEAR        EMR               
#>  8 13635 NCDMORT3070   COUNTRY        TZA        YEAR        AFR               
#>  9 14676 NCDMORT3070   COUNTRY        MDA        YEAR        EUR               
#> 10 15905 NCDMORT3070   COUNTRY        ITA        YEAR        EUR               
#> # ℹ 4,060 more rows
#> # ℹ 19 more variables: ParentLocation <chr>, Dim1Type <chr>, Dim1 <chr>,
#> #   TimeDim <int>, Dim2Type <chr>, Dim2 <chr>, Dim3Type <lgl>, Dim3 <lgl>,
#> #   DataSourceDimType <lgl>, DataSourceDim <lgl>, Value <chr>,
#> #   NumericValue <dbl>, Low <dbl>, High <dbl>, Comments <chr>, Date <chr>,
#> #   TimeDimensionValue <chr>, TimeDimensionBegin <chr>, TimeDimensionEnd <chr>
# }

Usage

Arguments

Value

See also

Examples