README.Rmd

---
output: github_document
always_allow_html: true
editor_options: 
  markdown: 
    wrap: 72
  chunk_output_type: console
---

<!-- 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%",
  message = FALSE,
  warning = FALSE,
  fig.retina = 2,
  fig.align = 'center'
)
```

# Malawi Emergency Flood Response Water Point Survey (2019–2020)

<!-- badges: start -->

[![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/1162600560.svg)](https://doi.org/10.5281/zenodo.18755616)
<!-- badges: end -->

This dataset contains water point assessment data collected during an
emergency flood response in Malawi between 2019 and 2020. The survey was
conducted under the BASEflow program to evaluate the status,
functionality, and safety of water points affected by flooding events.

Data collection and subsequent data cleaning were conducted using the
mWater platform. The dataset includes geospatial coordinates,
functionality status, user population estimates, reported mechanical and
structural issues, pumping performance metrics, sediment observations,
and field-based water quality test information.

The survey covered the following districts in Malawi:

-   Zomba

-   Mangochi

-   Chikwawa

-   Balaka

-   Nsanje

-   Blantyre

-   Machinga

The primary purpose of this dataset is to support emergency response
planning, infrastructure rehabilitation prioritization, and monitoring
of rural water supply systems in flood-affected areas.

This dataset can be used for:

1.  Humanitarian WASH (Water, Sanitation, and Hygiene) response analysis

2.  Geospatial mapping of water point functionality

3.  Infrastructure vulnerability assessments

4.  Evidence-based resource allocation during disaster recovery

## Installation

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

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

```{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/mwefloodresponse/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 water point assessment data collected during an emergency flood response in Malawi between 2019 and 2020.

```{r}
library(mwefloodresponse)
```

### metadata

The dataset `mwefloodresponse` contains `r nrow(mwefloodresponse)`
observations and `r ncol(mwefloodresponse)` variables

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

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

```{r echo=TRUE, message=TRUE, warning=TRUE}
readr::read_csv("data-raw/dictionary.csv") |>
  dplyr::filter(file_name == "mwefloodresponse.rda") |>
  dplyr::select(variable_name:description) |> 
  knitr::kable() |> 
  kableExtra::kable_styling("striped") |> 
  kableExtra::scroll_box(height = "200px")
```

## Example

```{r}
library(mwefloodresponse)

# Visualization 1: Map of Water Points
# Show waterpoint functionality
# Load required libraries
library(leaflet)
library(dplyr)
library(htmltools)
library(scales)

# Validate coordinates
df <- mwefloodresponse %>%
  mutate(
    latitude = as.numeric(latitude),
    longitude = as.numeric(longitude),
    people_using = as.numeric(people_using)
  ) %>%
  filter(!is.na(latitude), !is.na(longitude))

# Assign specific colors to each functional status category
status_pal <- colorFactor(
  palette = c(
    "Functional" = "green",
    "Partially Functional" = "orange",
    "Not Functional" = "red"
  ),
  domain = df$functional_status
)

# Rescale number of people using the water point
# Bubble size will range between 4 and 15
df <- df %>%
  mutate(
    people_scaled = rescale(people_using, to = c(4, 15))
  )

# Displays district, community, status, population, problems, and water quality result
df <- df %>%
  mutate(
    popup_content = paste0(
      "<b>District:</b> ", district, "<br>",
      "<b>Community:</b> ", community, "<br>",
      "<b>Functional Status:</b> ", functional_status, "<br>",
      "<b>People Using:</b> ", people_using, "<br>",
      "<b>Problems Reported:</b> ", 
        ifelse(is.na(problems_reported), "None reported", problems_reported), "<br>",
      "<b>Water Quality Result:</b> ", 
        ifelse(is.na(color_change_health), "No test result", color_change_health)
    )
  )

leaflet(df) %>%
  
  # Add base map tiles
  addProviderTiles("CartoDB.Positron") %>%
  
  # Add circle markers for each water point
  addCircleMarkers(
    lng = ~longitude,                  
    lat = ~latitude,                   
    radius = ~people_scaled,           
    fillColor = ~status_pal(functional_status),  
    color = "#333333",                 
    weight = 1,                        
    fillOpacity = 0.8,                 
    popup = ~HTML(popup_content)      
  ) %>%
  
  # Add legend to explain functional status colors
  addLegend(
    "bottomright",
    pal = status_pal,
    values = ~functional_status,
    title = "Functional Status",
    opacity = 1
  )
```

## 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("mwefloodresponse")
```