boreholefuncmwi

The goal of boreholefuncmwi is to provide access to data which were collected in the Karonga district (North of Malawi) and contains answers from a 20-minute questionnaire about boreholes. The questionnaire was installed on koboToolbox to collect borehole functionality data from 300 respondents aged 18 and above.

Installation

You can install the development version of boreholefuncmwi from GitHub with:

# install.packages("devtools")
devtools::install_github("openwashdata/boreholefuncmwi")

## 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.

Data

library(boreholefuncmwi)

boreholefuncmwi

The dataset boreholefuncmwi contains data about borehole’s management in the North of Malawi. Questions included in the questionnaire are for example about the borehole maintenance contributions from the community, the availability of borehole spare parts, tariff collection frequency and presence of a service provider. It has 108 observations and 17 variables.

boreholefuncmwi |> 
  head(3) |> 
  gt::gt() |>
  gt::as_raw_html()

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

Example

It can be interesting to analyse the numbers of households who draw water from a borehole in each village. Here is a plot showing the distribution of boreholes’ use across villages.

library(boreholefuncmwi)
library(unhcrthemes)
library(ggplot2)
borehole_user <- boreholefuncmwi %>%
  group_by(village) %>%
  summarise(number_households = sum(number_households, na.rm = TRUE))

ggplot(borehole_user) +
  geom_col(aes(
    x = number_households,
    y = reorder(village, number_households)
  ),
  fill = "lightgreen",  # Change the color here to light green
  width = 0.8
  ) +
  geom_text(aes(
    x = number_households,
    y = reorder(village, number_households),
    label = round(number_households)
  ),
  hjust = -0.5,
  size = 8 / .pt
  ) +
  labs(
    title = "Number of households using a borehole",
    caption = "Boreholes distribution according to villages"

  ) +
  scale_x_continuous(expand = expansion(c(0, 0.1))) +
  theme_unhcr(
    grid = FALSE,
    axis = "y",
    axis_title = FALSE,
    axis_text = "y"
  )

Capstone Project

This dataset is shared as part of a capstone project in Data Science for openwashdata. For more information about the project and to explore further insights, please visit the project page at https://ds4owd-001.github.io/project-myesaya/

License

Data are available as CC-BY.

Citation

Please cite this package using:

citation("boreholefuncmwi")
#> To cite package 'boreholefuncmwi' in publications use:
#> 
#>   Yesaya M, Preisig J, Kayira H, Zhong M (2024). "boreholefuncmwi:
#>   Analysis of boreholes' functionality in Northern Malawi."
#>   doi:10.5281/zenodo.12635354
#>   <https://doi.org/10.5281/zenodo.12635354>,
#>   <https://github.com/openwashdata/boreholefuncmwi>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Misc{yesaya_etall:2024,
#>     title = {boreholefuncmwi: Analysis of boreholes' functionality in Northern Malawi},
#>     author = {Mabvuto Yesaya and Juliette Preisig and Hastings Kayira and Mian Zhong},
#>     year = {2024},
#>     doi = {10.5281/zenodo.12635354},
#>     url = {https://github.com/openwashdata/boreholefuncmwi},
#>     abstract = {The data is obtained from a survey conducted in Wasambo in Karonga district (Northen Malawi). This data is about boreholes and handpumps that people mostly rely on for drinking water, secondary to wells and rivers. The data were collected in June 2023.},
#>     keywords = {borehole,malawi,opendata,openwashdata,r,survey-data},
#>     version = {0.0.1},
#>   }