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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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.