Summarize Data by Hex Cell

Aggregates data within each hexagonal cell, similar to dplyr::group_by(cell_id) |> summarize(...). Returns a data.frame with one row per unique cell, including cell center coordinates and area.

Usage

hex_summarize(hex_data, ..., .fns = NULL, geometry = FALSE)

Arguments

hex_data

A HexData object (from hexify()).

...

Named summary expressions (tidyeval). Each expression is evaluated per cell group with the group's columns available by name. Examples: mean_temp = mean(temperature), n_species = length(unique(species)), max_elev = max(elevation, na.rm = TRUE). Provide either ... or .fns, not both.

.fns

Optional named list of functions for formula-style aggregation. Example: .fns = list(mean_temp = ~mean(temperature)). Provide either ... or .fns, not both.

geometry

Logical. If TRUE, attach cell center points as an sf geometry column (requires sf). Default FALSE.

Value

A data.frame with columns:

cell_id

Unique cell identifier

cell_cen_lon, cell_cen_lat

Cell center coordinates

cell_area_km2

Cell area in km^2

n_points

Number of data points in this cell

...

User-defined summary columns

If geometry = TRUE, returns an sf object with POINT geometry.

Details

The function works entirely in R (no C++ needed). It groups by cell_id and evaluates the summary expressions within each group.

If no summary expressions are provided, returns cell counts only.

See also

hexify() for creating HexData objects, get_neighbors() for finding neighboring cells

Examples

# \donttest{
df <- data.frame(
  lon = runif(100, -10, 10),
  lat = runif(100, 40, 55),
  temperature = rnorm(100, 15, 5),
  species = sample(letters[1:5], 100, replace = TRUE)
)
hd <- hexify(df, lon = "lon", lat = "lat", area_km2 = 500)

# Count points per cell
hex_summarize(hd)

# Custom summaries
hex_summarize(hd, mean_temp = mean(temperature),
                  n_species = length(unique(species)))
# }