openwashdata/mwefloodresponse

This dataset contains water point assessment data collected in Zomba, Machinga, Mangochi, Chikwawa, Balaka, Nsanje and Blantyre districts during an emergency flood response in Malawi between 2019 and 2020 # Malawi Emergency Flood Response Water Point Survey (2019–2020) 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 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 …