Get PPI table/s based on a specified PPI table/s search output

Usage

get_table(
  region = steer$region,
  country = steer$country[steer$region %in% region],
  type = steer$type[steer$country %in% country]
)

Arguments

region: Region of the world to search PPI table from. Default is c("Africa", "Asia", "Eastern Europe and Central Asia", "Latin America and the Carribean", "Middle East and North Africa"). Allows specification of one region or a vector of regions.
country: Country to search PPI table from. Default is vector of all country names from the specified region/s. Allows specification of one country name or a vector of country names.
type: Type of PPI calculation used. Can be one of two options: "sps" for the Simple Poverty Scorecard calculation or ipa for the International Poverty Alliance calculation. Default is vector of all calculation types available for the specified country/ies.

Value

A data frame in tibble format of corresponding PPI table/s matching the search parameters. The data frame is in tidy format and contains the corresponding poverty probability (ppi) for a specific score (score) for various poverty definitions) for the country (country) and PPI calculation type (type).

Examples

## Create a tidy format PPI table for Nepal
get_table(region = "Asia", country = "Nepal")
#> # A tibble: 1,111 × 7
#>    country release_year filename   type  score poverty_definition   ppi
#>    <chr>   <chr>        <chr>      <chr> <int> <chr>              <dbl>
#>  1 Nepal   2013         ppiNPL2013 sps       0 nl100                100
#>  2 Nepal   2013         ppiNPL2013 sps       0 ppp125               100
#>  3 Nepal   2013         ppiNPL2013 sps       0 ppp250               100
#>  4 Nepal   2013         ppiNPL2013 sps       1 nl100                100
#>  5 Nepal   2013         ppiNPL2013 sps       1 ppp125               100
#>  6 Nepal   2013         ppiNPL2013 sps       1 ppp250               100
#>  7 Nepal   2013         ppiNPL2013 sps       2 nl100                100
#>  8 Nepal   2013         ppiNPL2013 sps       2 ppp125               100
#>  9 Nepal   2013         ppiNPL2013 sps       2 ppp250               100
#> 10 Nepal   2013         ppiNPL2013 sps       3 nl100                100
#> # ℹ 1,101 more rows