Spatial boundary data for Malawi administrative levels
# mwmapdata
**mwmapdata** provides official spatial boundary datasets for Malawi, for use with the mwmap package or any spatial analysis workflow requiring Malawi administrative boundaries.
## Datasets
| Object | Level | Features | Description |
|---------------|---------------|---------------|-----------------------------|
| `mw_level_0` | 0 | 1 | National boundary |
| `mw_level_1` | 1 | 3 | Administrative regions (N, C, S) |
| `mw_level_2` | 2 | 32 | Districts (incl. 4 city districts) |
| `mw_level_3` | 3 | 433 | Traditional authorities |
| `major_lakes` | — | 1 | Lake Malawi / Lake Nyasa |
| `malawi_data` | 2 | 32 | Legacy alias for `mw_level_2` (**deprecated**) |
All levels include `area_sqkm`, `center_lat`, and `center_lon` columns.
Boundary data are the official **Common Operational Datasets (COD-AB)** sourced from the **National Statistics Office of Malawi**, distributed via OCHA Humanitarian Data Exchange (HDX), version 02 (valid from 05 April 2023).
## Installation
``` r
# From CRAN (once available)
install.packages("mwmapdata")
# Development version
remotes::install_github("bitacanalytics/mwmapdata")
```
## Usage
``` r
library(mwmapdata)
library(sf)
# Plot all 32 districts
plot(st_geometry(mw_level_2))
# Plot traditional authorities in a single district
lilongwe_tas <- mw_level_3[mw_level_3$DISTRICT == "Lilongwe", ]
plot(st_geometry(lilongwe_tas))
# Check data validity
mwmapdata_check()
```
## Data notes
- `mw_level_2` contains **32 districts**, including the 4 city districts (Blantyre City, Lilongwe City, Mzuzu City, Zomba City) added in the 2023 boundary update. Earlier datasets had 28 districts.
- `mw_level_3` contains **433 traditional authorities**, up from \~250 in earlier boundary versions.
- The `major_lakes` object contains Lake …