# Introduction to pkmapr

    library(pkmapr)

## Installation

Install pkmapr from GitHub:

    remotes::install_github("abdullahumer1101/pkmapr")

Or:

    # install.packages("pkmapr", repos = "https://abdullahumer1101.r-universe.dev")

## Your first map

Get province boundaries and create a quick map:

    provinces <- get_provinces()
    pk_map(provinces)

## Look up names before joining

Always check official names before filtering or joining:

    # All provinces with their codes
    pk_dictionary("provinces")

    # Districts in Punjab
    pk_dictionary("districts", province = "Punjab")

    # Tehsils in Lahore district
    pk_dictionary("tehsils", district = "Lahore")

## Join your own data

    library(dplyr)

    # Example: district-level data
    my_data <- data.frame(
      district_code = c("PK603", "PK604"),
      value = c(42, 37)
    )

    districts <- get_districts() |>
      pk_join(my_data, by = "district_code")

    # Map the result
    pk_map(districts, fill = "value", title = "My Values")

## Interactive maps

    pk_map_interactive(districts,
                        fill = "value",
                        popup = c("district_name", "value"))

## Next steps

- `vignette("spatial-analysis-pkmapr")` for buffers, centroids, and point-in-polygon
- `vignette("epidemiology-pkmapr")` for spatial autocorrelation and hotspots