Auxiliary tables and the .pip environment

library(pipr)
#> Info: Session based caching is enabled.

The Poverty and Inequality Portal (PIP) not only provides the estimates to monitor global poverty and country-level inequality, but it also makes available all the underlying data necessary for such estimations. These data are called auxiliary tables and you can access them with the {pipr} package via the function get_aux(). You need to know the name of the auxiliary table you need to retrieve. For that you can use the function display_aux()

Display list of auxiliary tables

The main objective of display_aux() is to show the user all the auxiliary tables available in pip and give them the ability to download them by just clicking on their names. ¹ The idea of this feature is to simulate the behavior of the complementary PIP Stata wrapper {pip}.

display_aux()
#> -- Click on any of the tables below --
#> 
#> `aux versions`
#> `countries`
#> `country coverage`
#> `country list`
#> `cpi`
#> `decomposition`
#> `dictionary`
#> `framework`
#> `gdp`
#> `incgrp coverage`
#> `indicators`
#> `interpolated means`
#> `missing data`
#> `pce`
#> `pop`
#> `pop region`
#> `poverty lines`
#> `ppp`
#> `region coverage`
#> `regions`
#> `survey means`

When you click on any of the tables names in the console of your R IDE, {pipr} will store the desired table into the .pip environment, which is created at build time. That is, each time {pipr} is loaded or attached. To store the tables in the .pip environment, display_aux() makes use of the argument assign_tb in the get_aux() function. If TRUE, get_aux() assigns the requested auxiliary table to the .pip environment and returns and invisible TRUE instead of the table. If FALSE (the default), it behaves as usual. So, display_aux() is just a wrapper around get_aux() with assign_tb = TRUE.

Calling the tables in .pip env.

Since the .pip environment is created at build time inside {pipr} it is quite tricky to get its contents “by hand.” This why you need to use function call_aux to call any auxiliary table available in .pip env. In this way, you have the best of both words:

1. You can download aux tables by only clicking on their names (ala Stata).
2. You don’t mess up with the global env
3. you can call the tables you downloaded with call_aux()
4. The assign_tb option and call_aux are a powerful idea for developers who need to keep their environments clean.

# this simulates a `display_aux() call`
get_aux("gdp", assign_tb = TRUE)
#> ℹ Auxiliary table gdp successfully fetched. You can now call it by typing
#> `pipr::call_aux('gdp')`

# now you can call it
call_aux("gdp")
#> # A tibble: 10,120 × 4
#>    country_code data_level year   value
#>    <chr>        <chr>      <fct>  <dbl>
#>  1 ABW          national   1977     NA 
#>  2 ABW          national   1978     NA 
#>  3 ABW          national   1979     NA 
#>  4 ABW          national   1980     NA 
#>  5 ABW          national   1981     NA 
#>  6 ABW          national   1982     NA 
#>  7 ABW          national   1983     NA 
#>  8 ABW          national   1984     NA 
#>  9 ABW          national   1985     NA 
#> 10 ABW          national   1986  15222.
#> # ℹ 10,110 more rows

Using .pip in development

You can use the .pip environment in development when you need to interact with PIP auxiliary data in several instances during your project and need to make sure the data is not affected by the work in your global environment. .pip environment makes sure that all its tables remain unchanged and available when needed as long as {pipr} is not reloaded or a new R session is started

# for developers who may need several tables
tb <- c("cpi", "ppp", "pop")
l <- lapply(tb, get_aux, assign_tb = TRUE)
#> ℹ Auxiliary table cpi successfully fetched. You can now call it by typing
#> `pipr::call_aux('cpi')`
#> ℹ Auxiliary table ppp successfully fetched. You can now call it by typing
#> `pipr::call_aux('ppp')`
#> ℹ Auxiliary table pop successfully fetched. You can now call it by typing
#> `pipr::call_aux('pop')`
call_aux()
#> 
#> ── tables available in env pip ──
#> 
#> `gdp`
#> `ppp`
#> `cpi`
#> `pop`

call_aux("pop")
#> # A tibble: 29,900 × 4
#>    country_code data_level year  value
#>    <chr>        <chr>      <fct> <dbl>
#>  1 ABW          national   1977  61465
#>  2 ABW          rural      1977  30415
#>  3 ABW          urban      1977  31050
#>  4 ABW          national   1978  61738
#>  5 ABW          rural      1978  30559
#>  6 ABW          urban      1978  31179
#>  7 ABW          national   1979  62006
#>  8 ABW          rural      1979  30701
#>  9 ABW          urban      1979  31305
#> 10 ABW          national   1980  62267
#> # ℹ 29,890 more rows

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1. The availability of this feature depends on the IDE you use, which explained here. If you’re IDE does not support links, {pipr} will only display the list of available auxiliary tables.↩︎