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]))
| region | Region of the world to search PPI table from. Default is
|
|---|---|
| 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: |
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).
# # 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