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Visualize Spatial Point Data

Source: R/geom_loc.R
geom_loc.Rd

`geom_loc` is a wrapper around ggplot2::geom_sf() designed for visualizing spatial point data. It supports both sf objects and tabular data frames with longitude and latitude columns, automatically transforming them into the specified coordinate reference system (CRS).

Usage

geom_loc(
  data,
  lon = NULL,
  lat = NULL,
  crs = "+proj=aeqd +lat_0=35 +lon_0=105 +ellps=WGS84 +units=m +no_defs",
  mapping = ggplot2::aes(),
  ...
)

Arguments

data

A data frame, tibble, or sf object containing spatial point data.

lon

A character string. The name of the longitude column in data (required if data is tabular).

lat

A character string. The name of the latitude column in data (required if data is tabular).

crs

A character string. The target coordinate reference system (CRS) for the data. Defaults to "+proj=aeqd +lat_0=35 +lon_0=105 +ellps=WGS84 +units=m +no_defs".

mapping

Aesthetic mappings created by ggplot2::aes(), such as color or size.

...

Additional parameters passed to ggplot2::geom_sf(), such as size, alpha, or color.

Value

A ggplot2 layer for visualizing spatial point data, either from an `sf` object or a tabular data frame with longitude and latitude columns, after transforming the data to the specified coordinate reference system (CRS).

Details

This function simplifies the process of visualizing spatial data in ggplot2 by automatically handling CRS transformations and providing an interface for both sf and tabular data. If the input is a tabular data frame, it will be converted to an sf object using the specified longitude and latitude columns.

See ggplot2::geom_sf() for details on additional parameters and aesthetics.

See also

geom_boundary_cn

Examples

# Generate a random dataset with latitude and longitude
set.seed(123)
data_sim <- data.frame(
  Longitude = runif(100, 80, 120),
  Latitude = runif(100, 28, 40),
  Category = sample(c("Type A", "Type B", "Type C"), 100, replace = TRUE)
)

# Visualize the data with China's boundaries
ggplot() +
  geom_boundary_cn() +
  geom_loc(
    data = data_sim, lon = "Longitude", lat = "Latitude",
    mapping = aes(color = Category), size = 1, alpha = 0.7
  ) +
  theme_minimal()