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

get_table(region = levels(steer$region),
  country = as.character(steer$country[steer$region %in% region]),
  type = as.character(steer$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 poverty_definition) 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 x 7 #> country release_year filename type score poverty_definition ppi #> <fct> <fct> <fct> <fct> <int> <chr> <dbl> #> 1 Nepal 2013 ppiNPL2013 sps 0 nl100 100 #> 2 Nepal 2013 ppiNPL2013 sps 1 nl100 100 #> 3 Nepal 2013 ppiNPL2013 sps 2 nl100 100 #> 4 Nepal 2013 ppiNPL2013 sps 3 nl100 100 #> 5 Nepal 2013 ppiNPL2013 sps 4 nl100 100 #> 6 Nepal 2013 ppiNPL2013 sps 5 nl100 65 #> 7 Nepal 2013 ppiNPL2013 sps 6 nl100 65 #> 8 Nepal 2013 ppiNPL2013 sps 7 nl100 65 #> 9 Nepal 2013 ppiNPL2013 sps 8 nl100 65 #> 10 Nepal 2013 ppiNPL2013 sps 9 nl100 65 #> # ... with 1,101 more rows