GDPuc

R package for GDP unit conversion

https://github.com/pik-piam/gdpuc

Science Score: 44.0%

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Low similarity (16.2%) to scientific vocabulary

Last synced: 7 months ago · JSON representation ·

Repository

R package for GDP unit conversion

Basic Info

Host: GitHub
Owner: pik-piam
License: gpl-3.0
Language: R
Default Branch: main
Homepage: https://pik-piam.github.io/GDPuc/
Size: 14.8 MB

Statistics

Stars: 1
Watchers: 2
Forks: 7
Open Issues: 3
Releases: 10

Created about 5 years ago · Last pushed over 1 year ago

Metadata Files

Readme Changelog License Citation

README.Rmd

---
output: github_document
always_allow_html: yes
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# GDPuc



[![CRAN status](https://www.r-pkg.org/badges/version/GDPuc)](https://CRAN.R-project.org/package=GDPuc) [![check](https://github.com/pik-piam/GDPuc/actions/workflows/check.yaml/badge.svg)](https://github.com/pik-piam/GDPuc/actions/workflows/check.yaml) 
[![codecov](https://codecov.io/gh/pik-piam/GDPuc/branch/main/graph/badge.svg?token=3GHXFQXARX)](https://app.codecov.io/gh/pik-piam/GDPuc) 
![Lifecycle: stable](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)


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))

Owner

Name: Potsdam Integrated Assessment Modelling (PIAM)
Login: pik-piam
Kind: organization
Location: Potsdam Institute for Climate Impact Research (PIK), Germany

Website: https://www.pik-potsdam.de/
Repositories: 50
Profile: https://github.com/pik-piam

Tools developed for use with data and models related to PIK's research.

Citation (CITATION.cff)

cff-version: 1.2.0
message: If you use this software, please cite it using the metadata from this file.
type: software
title: 'GDPuc: Easily Convert GDP Data'
version: 1.4.1
date-released: '2024-10-23'
abstract: Convert GDP time series data from one unit to another. All common GDP units
  are included, i.e. current and constant local currency units, US$ via market exchange
  rates and international dollars via purchasing power parities.
authors:
- family-names: Koch
  given-names: Johannes
  email: jokoch@pik-potsdam.de
license: GPL (>= 3)
repository-code: https://github.com/pik-piam/GDPuc
url: https://pik-piam.github.io/GDPuc/

GitHub Events

Total

Push event: 4
Pull request event: 5
Create event: 1

Last Year

Push event: 4
Pull request event: 5
Create event: 1

Committers

Last synced: about 2 years ago

All Time

Total Commits: 94
Total Committers: 4
Avg Commits per committer: 23.5
Development Distribution Score (DDS): 0.085

Past Year

Commits: 13
Committers: 3
Avg Commits per committer: 4.333
Development Distribution Score (DDS): 0.154

Top Committers

Name	Email	Commits
Johannes Koch	j**h@p**e	86
Pascal Führlich	p**h@p**e	6
David Chen	d**h@l**e	1
pre-commit-ci[bot]	6****]	1

Committer Domains (Top 20 + Academic)

pik-potsdam.de: 2 lt916.pik-potsdam.de: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time

Total issues: 16
Total pull requests: 23
Average time to close issues: 3 months
Average time to close pull requests: 20 days
Total issue authors: 2
Total pull request authors: 4
Average comments per issue: 0.25
Average comments per pull request: 0.26
Merged pull requests: 17
Bot issues: 0
Bot pull requests: 6

Past Year

Issues: 3
Pull requests: 7
Average time to close issues: 19 days
Average time to close pull requests: about 17 hours
Issue authors: 1
Pull request authors: 2
Average comments per issue: 0.0
Average comments per pull request: 0.43
Merged pull requests: 5
Bot issues: 0
Bot pull requests: 2

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Top Authors

Issue Authors

johanneskoch94 (15)
0UmfHxcvx5J7JoaOhFSs5mncnisTJJ6q (1)
caviddhen (1)

Pull Request Authors

johanneskoch94 (27)
pre-commit-ci[bot] (8)
fbenke-pik (2)
caviddhen (1)

Top Labels

Issue Labels

enhancement (1) bug (1)

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Packages

Total packages: 1
Total downloads:
- cran 355 last-month

Total dependent packages: 0
Total dependent repositories: 24
Total versions: 10
Total maintainers: 1

cran.r-project.org: GDPuc

Easily Convert GDP Data

Homepage: https://github.com/pik-piam/GDPuc
Documentation: http://cran.r-project.org/web/packages/GDPuc/GDPuc.pdf
License: GPL (≥ 3)
Latest release: 1.0.4
published over 1 year ago

Versions: 10
Dependent Packages: 0
Dependent Repositories: 24
Downloads: 355 Last month

Rankings

Dependent repos count: 5.6%

Forks count: 9.6%

Average: 22.6%

Dependent packages count: 28.7%

Stargazers count: 30.8%

Downloads: 38.3%

Maintainers (1)

jokoch@pik-potsdam.de

Last synced: 7 months ago

Dependencies

DESCRIPTION cran

R >= 2.10 depends
cli >= 2.4.0 imports
crayon * imports
dplyr * imports
glue * imports
lifecycle * imports
magrittr * imports
rlang >= 1.0.0 imports
tibble * imports
tidyselect * imports
withr * imports
WDI * suggests
covr * suggests
knitr * suggests
magclass * suggests
purrr * suggests
readxl * suggests
rmarkdown * suggests
stringr * suggests
testthat >= 3.0.0 suggests
tidyr * suggests
zoo * suggests

.github/workflows/R-CMD-check.yaml actions

actions/cache v2 composite
actions/checkout v2 composite
actions/upload-artifact main composite
r-lib/actions/setup-pandoc v1 composite
r-lib/actions/setup-r v1 composite

.github/workflows/lucode2-check.yaml actions

actions/checkout v2 composite
actions/setup-python v2 composite
pat-s/always-upload-cache v3 composite
r-lib/actions/setup-pandoc v1 composite

.github/workflows/pkgdown.yaml actions

actions/checkout v2 composite
r-lib/actions/setup-pandoc v1 composite
r-lib/actions/setup-r v1 composite
r-lib/actions/setup-r-dependencies v1 composite

.github/workflows/test-coverage.yaml actions

actions/cache v2 composite
actions/checkout v2 composite
r-lib/actions/setup-pandoc v1 composite
r-lib/actions/setup-r v1 composite

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GDPuc

Science Score: 44.0%

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README.Rmd

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Citation (CITATION.cff)

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