README.Rmd

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# WASH and Sanitation Survey in Community-Based Childcare Centres – Thyolo and Chikwawa, Malawi (2021)

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[![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/1007587006.svg)](https://doi.org/10.5281/zenodo.17540498)

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This dataset provides detailed information on Water, Sanitation, and Hygiene (WASH) conditions and related management practices in Community-Based Childcare Centres (CBCCs) across Thyolo and Chikwawa Districts in Malawi, collected in 2021. Data were gathered by BASEflow using the mWater digital data collection platform.

The dataset contains metadata about the survey, including the geographical location of CBCCs, water sources and their functionality, sanitation infrastructure, hygiene practices, governance and management structures, funding mechanisms, cleanliness levels, and the availability of hygiene education and promotional materials.

Intended Users and Applications

1.  Local Government and Health Authorities: To monitor WASH conditions,
    inform resource allocation, and design targeted interventions within
    Thyolo’s CBCCs.

2.  CBCC Management and Caregivers: To identify gaps and improve
    maintenance, hygiene practices, and infrastructure.

3.  NGOs and Development Partners: To support planning, implementation,
    and evaluation of WASH programs aligned with community needs and WHO
    standards.

4.  Researchers and Policy Makers: To study the relationship between
    WASH facilities and child health outcomes for evidence-based
    decision-making.

5.  Donors and Funders: To assess infrastructure needs and measure
    impact of funded WASH initiatives.

## Installation

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

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

```{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/thyolocbcc/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 Community-Based Childcare Centres (CBCCs)
in Thyolo District, focusing on critical Water, Sanitation, and Hygiene
(WASH) infrastructure and practices

```{r}
library(thyolocbcc)
```

### thyolocbcc

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

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

## Example

```{r}
library(thyolocbcc)
library(forcats)
library(ggplot2)

# Create a bar chart of water source types, displaying NA as "Other"
ggplot(thyolocbcc, aes(x = fct_explicit_na(main_water_source, na_level = "Other"))) +
  geom_bar(fill = "#1f78b4") +
  labs(title = "Main Water Source Types Across CBCCs",
       x = "Water Source Type",
       y = "Number of CBCCs") +
  theme_minimal() +
  # Rotate x-axis labels for better readability
  theme(axis.text.x = element_text(angle = 45, hjust = 1))


#Pie Chart: Percentage of CBCCs with Year-Round Water Availability

# Prepare data for pie chart
year_round <- thyolocbcc %>%
  # Filter out rows where water availability data is missing
  filter(!is.na(water_available_year_round)) %>%
  
  # Count the number of CBCCs for each water availability category (Yes/No)
  count(water_available_year_round) %>%
  
  # Calculate percentage and create a label for each slice
  mutate(
    percent = round(100 * n / sum(n), 1),  # Percent of total
    label = paste0(water_available_year_round, " (", percent, "%)")  # Text label for the pie chart
  )

# Create pie chart
ggplot(year_round, aes(x = "", y = n, fill = water_available_year_round)) +
  # Create a stacked bar chart with white borders(to become pie slices)
  geom_col(width = 1, color = "white") +
  
  # Convert the stacked bar into a circular pie chart
  coord_polar(theta = "y") +
  
  # Add percentage labels inside each slice
  geom_text(aes(label = label),
            position = position_stack(vjust = 0.5),
            color = "white", size = 4) +
  
  # Add chart title and remove other axis elements
  labs(title = "Year-Round Water Availability at CBCCs") +
  theme_void() +
  
  # Use a nice color palette for the slices
  scale_fill_brewer(palette = "Set2")
```

## 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("thyolocbcc")
```