aqp: missingDataGrid – R documentation

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aqp

missingDataGrid

Missing Data Grid

Description

Generate a levelplot of missing data from a SoilProfileCollection object.

Usage

missingDataGrid(
  s,
  max_depth,
  vars,
  filter.column = NULL,
  filter.regex = NULL,
  cols = NULL,
  ...
)

Arguments

`s`	a SoilProfileCollection object
`max_depth`	integer specifying the max depth of analysis
`vars`	character vector of column names over which to evaluate missing data
`filter.column`	a character string naming the column to apply the filter REGEX to
`filter.regex`	a character string with a regular expression used to filter horizon data OUT of the analysis
`cols`	a vector of colors
`...`	additional arguments passed on to `levelplot`

Details

This function evaluates a missing data fraction based on slice-wise evaulation of named variables in a SoilProfileCollection object.

Value

A data.frame describing the percentage of missing data by variable.

Note

A lattice graphic is printed to the active output device.

Author(s)

D.E. Beaudette

Examples

# 10 random profiles
set.seed(10101)
s <- lapply(as.character(1:10), random_profile)
s <- do.call('rbind', s)

# randomly sprinkle some missing data
s[sample(nrow(s), 5), 'p1'] <- NA
s[sample(nrow(s), 5), 'p2'] <- NA
s[sample(nrow(s), 5), 'p3'] <- NA

# set all p4 and p5 attributes of `soil 1' to NA
s[which(s$id == '1'), 'p5'] <- NA
s[which(s$id == '1'), 'p4'] <- NA

# upgrade to SPC
depths(s) <- id ~ top + bottom

# plot missing data via slicing + levelplot
missingDataGrid(
  s,
  max_depth = 100,
  vars = c('p1', 'p2', 'p3', 'p4', 'p5'),
  main='Missing Data Fraction'
)

aqp

Algorithms for Quantitative Pedology

v1.29

GPL (>= 3)

Authors

Dylan Beaudette [aut, cre], Pierre Roudier [aut, ctb], Andrew Brown [aut, ctb]

Initial release

2021-04-05