Retains only rows where coordinates fall within specified latitude and
longitude bounds. Unlike latlong_filter, which validates
against absolute geographic limits, this function filters to a
user-defined bounding box. Use latlong_limits first to
inspect the coordinate extent of the data and inform suitable bound values.
Usage
latlong_range(
data,
latitude,
longitude,
lat_min,
lat_max,
lon_min,
lon_max,
drop_na = FALSE
)Arguments
- data
A data frame containing coordinate columns.
- latitude
Column name of the latitude column, supplied either unquoted (
lat) or quoted ("lat"). Must contain numeric or numeric-coercible values in decimal degrees.- longitude
Column name of the longitude column, supplied either unquoted (
lon) or quoted ("lon"). Must contain numeric or numeric-coercible values in decimal degrees.- lat_min
Numeric. Minimum latitude bound (inclusive). Must be in the range
[-90, 90].- lat_max
Numeric. Maximum latitude bound (inclusive). Must be in the range
[-90, 90].- lon_min
Numeric. Minimum longitude bound (inclusive). Must be in the range
[-180, 180].- lon_max
Numeric. Maximum longitude bound (inclusive). Must be in the range
[-180, 180].- drop_na
Logical. If
TRUE, rows withNAin either coordinate column are dropped before range filtering. Default isFALSE.
Value
A data frame containing only rows where latitude falls within
[lat_min, lat_max] and longitude falls within
[lon_min, lon_max], with the same columns as data. A console
message reports the total rows removed, broken down by NA rows and
out-of-range rows.
Details
Coordinate columns are coerced to numeric via as.numeric() before
filtering. Non-numeric values (including DMS or base-60 strings) will
produce NA after coercion and be treated as out-of-range. Use
latlong_convert to convert to decimal degrees before calling
this function if columns are not already numeric.
All bounds are inclusive. Rows with NA coordinates are excluded from
the retained set regardless of drop_na, as they cannot be evaluated
against the bounds. When drop_na = FALSE, NA rows contribute
to the out-of-range count in the console message rather than the NA
count.
See also
latlong_limits for inspecting the coordinate extent of a
data frame to inform bound selection,
latlong_filter for removing coordinates outside absolute
geographic validity ranges,
latlong_convert for converting DMS or base-60 columns to
decimal degrees before filtering,
latlong_split for separating a combined coordinate column
into distinct latitude and longitude columns before filtering as
latlong_range does not function with combined columns,
latlong_region for filtering to named geographic regions
rather than a numeric bounding box.
Examples
df <- data.frame(
id = 1:6,
lat = c(51.5, 48.8, -33.9, 40.7, 35.6, 55.8),
lon = c(-0.1, 2.3, 151.2, -74.0, 139.7, 37.6)
)
# Retain only rows within a European bounding box
latlong_range(df, latitude = lat, longitude = lon,
lat_min = 35, lat_max = 60,
lon_min = -10, lon_max = 40)
#> [latlong_range] 3 row(s) removed: 0 NA, 3 out of range
#> id lat lon
#> 1 1 51.5 -0.1
#> 2 2 48.8 2.3
#> 6 6 55.8 37.6
# Use latlong_limits first to inspect coordinate extent
df |>
latlong_limits(latitude = lat, longitude = lon) |>
latlong_range(latitude = lat, longitude = lon,
lat_min = 35, lat_max = 60,
lon_min = -10, lon_max = 40)
#> [latlong_limits] latitude — min: -33.900000, max: 55.800000
#> [latlong_limits] longitude — min: -74.000000, max: 151.200000
#> [latlong_range] 3 row(s) removed: 0 NA, 3 out of range
#> id lat lon
#> 1 1 51.5 -0.1
#> 2 2 48.8 2.3
#> 6 6 55.8 37.6
# Drop NA rows before filtering
df_na <- data.frame(
lat = c(51.5, NA, -33.9, 40.7),
lon = c(-0.1, 2.3, 151.2, NA)
)
latlong_range(df_na, latitude = lat, longitude = lon,
lat_min = 0, lat_max = 60,
lon_min = -10, lon_max = 40,
drop_na = TRUE)
#> [latlong_range] 3 row(s) removed: 2 NA, 1 out of range
#> lat lon
#> 1 51.5 -0.1