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README.Rmd
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README.Rmd
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---
output: github_document
always_allow_html: yes
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# GDPuc
<!-- badges: start -->
[](https://CRAN.R-project.org/package=GDPuc) [](https://github.com/pik-piam/GDPuc/actions/workflows/check.yaml)
[](https://app.codecov.io/gh/pik-piam/GDPuc)
<!-- badges: end -->
GDPuc (a.k.a. the GDP unit-converter) provides a simple function to convert GDP time-series data from one unit to another.
**To note:** The default conversion parameters are from the World Bank's World Development Indicators (WDI) database (see [link](https://databank.worldbank.org/source/world-development-indicators)). The current parameters are from **April 30th 2024**, with the next update planned for April 2026.
## Installation
```{r, eval = FALSE}
# Install from CRAN
install.packages("GDPuc")
# Or the development version from GitHub
remotes::install_github("pik-piam/GDPuc")
```
## Usage
Load the package.
```{r eval=FALSE}
library(GDPuc)
```
The main function of the package is `convertGDP`.
```{r usage1, eval=FALSE}
convertGDP(
gdp = my_gdp,
unit_in = "constant 2005 LCU",
unit_out = "constant 2017 Int$PPP"
)
```
Here, the `gdp` argument takes a tibble or a data-frame that contains, at least:
- a column with iso3c country codes, (ideally named "iso3c"),
- a column with the year, (ideally named "year"),
- a column named "value", with the gdp data.
The `unit_in` and `unit_out` arguments specify the incoming and outgoing GDP units. All common GDP units are supported, i.e.:
- current LCU
- current US$MER
- current Int$PPP
- constant YYYY LCU
- constant YYYY US$MER
- constant YYYY Int$PPP
Here "YYYY" is a placeholder for a year, e.g. "2010" or "2015", and "LCU" stands for Local Currency Unit.
For a quick conversion of a single value use `convertSingle`.
```{r usage2, eval=FALSE}
convertSingle(
x = 100,
iso3c = "FRA",
year = 2000,
unit_in = "current LCU",
unit_out = "constant 2017 Int$PPP"
)
```
## Example
```{r example1}
library(GDPuc)
my_gdp <- tibble::tibble(
iso3c = "USA",
year = 2010:2014,
value = 100:104
)
print(my_gdp)
convertGDP(
gdp = my_gdp,
unit_in = "constant 2005 LCU",
unit_out = "constant 2017 Int$PPP"
)
convertSingle(
x = 100,
iso3c = "USA",
year = 2010,
unit_in = "current LCU",
unit_out = "constant 2017 Int$PPP"
)
# When converting between constant currencies, the year of the GDP value is not important,
# and can be left out.
convertSingle(
x = 100,
iso3c = "USA",
unit_in = "constant 2005 LCU",
unit_out = "constant 2017 Int$PPP"
)
```
## Further Options
`convertGDP` has other arguments that allow you to:
- choose conversion factors (see ["Choosing conversion factors"](https://pik-piam.github.io/GDPuc/articles/source.html))
- print out information on the conversion process and/or return the conversion factors used (see ["Getting information on the conversion process"](https://pik-piam.github.io/GDPuc/articles/verbose.html))
- handle missing conversion factors (see ["Handling missing conversion factors"](https://pik-piam.github.io/GDPuc/articles/handle_NAs.html))
- convert regional GDP data (see ["Converting regional GDP data"](https://pik-piam.github.io/GDPuc/articles/with_regions.html))