https://github.com/openwashdata/rwpfunctionality
Water point monitoring data associated with the paper "Rural water point functionality estimates and associations: evidence from nine countries in sub-Saharan Africa and South Asia".
https://github.com/openwashdata/rwpfunctionality
management open-data r wash water waterpoint
Last synced: 4 months ago
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Water point monitoring data associated with the paper "Rural water point functionality estimates and associations: evidence from nine countries in sub-Saharan Africa and South Asia".
- Host: GitHub
- URL: https://github.com/openwashdata/rwpfunctionality
- Owner: openwashdata
- License: cc-by-4.0
- Created: 2024-03-11T12:58:40.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-03-26T13:48:32.000Z (about 2 years ago)
- Last Synced: 2025-09-04T21:46:24.447Z (9 months ago)
- Topics: management, open-data, r, wash, water, waterpoint
- Language: TeX
- Homepage: https://openwashdata.github.io/rwpfunctionality/
- Size: 6.79 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE.md
- Citation: CITATION.cff
Awesome Lists containing this project
README
---
output: github_document
always_allow_html: true
editor_options:
markdown:
wrap: 72
chunk_output_type: console
bibliography: references.bib
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
library(tidyverse)
```
# rwpfunctionality
[](https://creativecommons.org/licenses/by/4.0/)
[](https://github.com/openwashdata/rwpfunctionality/actions/workflows/R-CMD-check.yaml)
[](https://zenodo.org/doi/10.5281/zenodo.10878634)
This package offers users comprehensive documentation on surveys conducted to assess water point functionality and management committees. These surveys were carried out across nine countries in both sub-Saharan Africa and South Asia. The data was published alongside the article "Rural water point functionality estimates and associations: evidence from nine countries in sub-Saharan Africa and South Asia" [@murray2024rural].
## Installation
You can install the development version of rwpfunctionality from [GitHub](https://github.com/) with:
```r
# install.packages("devtools")
devtools::install_github("openwashdata/rwpfunctionality")
```
Alternatively, you can download the dataset as a CSV or XLSX
file from the table below.
```{r, echo=FALSE, message=FALSE, warning=FALSE}
extdata_path <- "https://github.com/openwashdata/rwpfunctionality/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()
```
## Project goal
Sustained functionality of rural water systems is a global challenge. Addressing premature failures and unreliable performance of water points is crucial to achieve the 2030 Sustainable Development Goal (SDG) 6, which calls for universal and equitable access to safe and affordable drinking water for all [@safely]. As of 2020, 771 million people lacked a basic water service [@nina2021progressa]. Yet even for those with water services, unreliable water infrastructure that provides intermittent supply, or is broken down or abandoned, contributes to unsustainable and unsafe water access worldwide [@allaire2018national; @burt2018intermittent; @klug2018categorization; @valcourt2020understanding].
## Data
The dataset includes observations of water point functionality and management committee questionnaires. Displayed on the map are the locations of the water points.
The package provides access to one single dataset.
```{r, echo = TRUE}
library(rwpfunctionality)
```
The `rwpfunctionality` dataset has `r ncol(rwpfunctionality)`
variables and `r nrow(rwpfunctionality)` observations. For an overview
of the variable names, see the following table.
```{r, eval=FALSE}
rwpfunctionality
```
```{r, echo=FALSE, message=FALSE, warning=FALSE}
readr::read_csv("data-raw/dictionary.csv") |>
dplyr::filter(file_name == "rwpfunctionality.rda") |>
dplyr::select(variable_name:description) |>
knitr::kable() |>
kableExtra::kable_styling() |>
kableExtra::scroll_box(height = "400px")
```
## Examples
### Pie Chart of Water Points Functionality
What are the statuses of the water points? Are they functional?
```{r, message=FALSE}
library(dplyr)
library(ggplot2)
# Define custom colors
custom_colors <- c("lightblue", "orange", "purple")
# Create the pie chart
rwpfunctionality |>
count(functional3) |>
ggplot(aes(x = "", y = n, fill = functional3)) +
geom_bar(stat = "identity") +
coord_polar("y", start = 0) +
scale_fill_manual(values = custom_colors) + # Set custom colors
labs(title = "Functionality rating for water points", fill = NULL,
x = "", # Empty x-axis label
y = "Count") + # y-axis label
scale_fill_manual(labels = c("Functional", "Partially functional", "Abandoned or not functional"),
values = custom_colors) # Custom legend labels
```
Based on this pie chart, it could be interesting to redefine the category "Partially functional" to gain insights and precision on this aspect of the data. However, we still clearly see that only a small part of the water points are functional.
### Water Points Types
What are the different types of water points?
```{r, echo=TRUE, message=FALSE, warning=FALSE}
# Create a horizontal bar plot of water point types
ggplot(rwpfunctionality, aes(x = wptype)) +
geom_bar() +
labs(title = "Distribution of Water Points Types",
x = "Water Point Type",
y = "Frequency") +
coord_flip() # Flip coordinates to make it horizontal
```
This plot provides insight into the distribution of different types of water points present in the dataset. Understanding the prevalence of each type is valuable for various purposes, such as evaluating the functionality of each type to inform future development projects. For instance, it helps identifying which types are more common and could potentially inform decisions on prioritizing maintenance or constructing more efficient or suitable water point types.
## References
```{html, echo = FALSE}
```
## License
Data are available as
[CC-BY](https://github.com/openwashdata/rwpfunctionality/LICENSE.md).
## Citation
To cite this package, please use:
```{r}
citation("rwpfunctionality")
```