undpcomposite

https://github.com/openwashdata/undpcomposite

Repository

README.Rmd

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

# undpcomposite



[![License: CC BY
4.0](https://img.shields.io/badge/License-CC_BY_4.0-lightgrey.svg)](https://creativecommons.org/licenses/by/4.0/)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.14845848.svg)](https://zenodo.org/doi/10.5281/zenodo.14845848)
[![R-CMD-check](https://github.com/openwashdata/undpcomposite/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/openwashdata/undpcomposite/actions/workflows/R-CMD-check.yaml)


The goal of undpcomposite is to provide tidy data from the UNDP composite data timeseries

## Installation

You can install the development version of undpcomposite from
[GitHub](https://github.com/) with:

``` r
# install.packages("devtools")
devtools::install_github("openwashdata/undpcomposite")
```

```{r}
## Run the following code in console if you don't have the packages
## install.packages(c("dplyr", "knitr", "readr", "stringr", "gt", "kableExtra"))
library(dplyr)
library(knitr)
library(readr)
library(stringr)
library(gt)
library(kableExtra)
```

Alternatively, you can download the individual datasets as a CSV or XLSX
file from the table below.

1.  Click Download CSV. A window opens that displays the CSV in
    your browser.
2.  Right-click anywhere inside the window and select "Save Page As...".
3.  Save the file in a folder of your choice.

```{r, echo=FALSE, message=FALSE, warning=FALSE}

extdata_path <- "https://github.com/openwashdata/undpcomposite/raw/main/inst/extdata/"

read_csv("data-raw/dictionary.csv") |> 
  distinct(file_name) |> 
  dplyr::mutate(file_name = str_remove(file_name, ".rda")) |> 
  dplyr::rename(dataset = file_name) |> 
  mutate(
    CSV = paste0("[Download CSV](", extdata_path, dataset, ".csv)"),
    XLSX = paste0("[Download XLSX](", extdata_path, dataset, ".xlsx)")
  ) |> 
  knitr::kable()

```

## Data

The package provides access to composite data from UNDP on all indices in the form of a timeseries.

```{r}
library(undpcomposite)
```

### undpcomposite

The dataset `undpcomposite` contains data about UNDP indicators over time. It has
`r nrow(undpcomposite)` observations and `r ncol(undpcomposite)`
variables

```{r}
undpcomposite |> 
  head(3) |> 
  gt::gt() |>
  gt::as_raw_html()
```

For an overview of the variable names, see the following table.

```{r echo=FALSE, message=FALSE, warning=FALSE}
library(readr)
library(dplyr)
library(knitr)
library(kableExtra)

# Read CSV with explicit encoding conversion
dictionary <- read_csv("data-raw/dictionary.csv", show_col_types = FALSE) |>
  mutate(across(where(is.character), ~ iconv(.,"UTF-8","UTF-8",sub="")))

# Filter and display table
dictionary |>
  filter(file_name == "undpcomposite.rda") |>
  select(variable_name:description) |> 
  kable() |> 
  kable_styling("striped") |> 
  scroll_box(height = "200px")

```

## Example

Less developed countries exhibit higher adolescent birth rates than more developed countries

```{r}
library(undpcomposite)
library(ggplot2)
library(dplyr)

# Ensure UTF-8 encoding for character columns
undpcomposite <- undpcomposite |>
  mutate(across(where(is.character), ~ iconv(.,"UTF-8","UTF-8",sub="")))

# Handle missing values in `abr`
undpcomposite_clean <- undpcomposite |> 
  filter(country %in% c("United States", "Germany", "Niger", "Mali")) |> 
  mutate(
    year = as.numeric(year),  # Convert year to numeric
    abr = ifelse(is.na(abr), 0, abr)  # Replace NA values in abr
  )

# Find min and max year
year_range <- range(undpcomposite_clean$year, na.rm = TRUE)

# Create the plot with decade-based x-axis
ggplot(undpcomposite_clean, aes(x = year, y = abr, color = country, group = country)) +
  geom_line() +
  scale_x_continuous(breaks = seq(floor(year_range[1] / 10) * 10, ceiling(year_range[2] / 10) * 10, by = 10)) +  
  labs(
    title = "Adolescent Birth Rate in Two High Income and Two Low Income Countries",
    x = "Year",
    y = "Adolescent Birth Rate (births per 1,000 women aged 15-29)"
  ) +
  theme_minimal()


```

## License

Data are available as
[CC-BY](https://github.com/openwashdata/%7B%7B%7Bpackagename%7D%7D%7D/blob/main/LICENSE.md).

## Citation

Please cite this package using:

```{r}
citation("undpcomposite")
```

Owner

Citation (CITATION.cff)

# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "undpcomposite" in publications use:'
type: software
license: CC-BY-4.0
title: 'undpcomposite: UNDP Composite Indicators Timeseries'
version: 0.1.0
doi: 10.5281/zenodo.14845848
abstract: Provides tidy data about all UNDP indicators in a composite timeseries.
authors:
- family-names: Dubey
  given-names: Yash
  email: ydubey@ethz.ch
  orcid: https://orcid.org/0009-0001-2849-970X
repository-code: https://github.com/openwashdata/undpcomposite
url: https://github.com/openwashdata/undpcomposite
date-released: '2025-02-10'
contact:
- family-names: Dubey
  given-names: Yash
  email: ydubey@ethz.ch
  orcid: https://orcid.org/0009-0001-2849-970X

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