intubate (version 1.0.0)

latticeExtra: Interfaces for latticeExtra package for data science pipelines.

Description

Interfaces to latticeExtra functions that can be used in a pipeline implemented by magrittr.

Usage

ntbt_ecdfplot(data, ...)
ntbt_mapplot(data, ...)
ntbt_rootogram(data, ...)
ntbt_segplot(data, ...)
ntbt_tileplot(data, ...)

Arguments

data

data frame, tibble, list, ...

...

Other arguments passed to the corresponding interfaced function.

Value

Object returned by interfaced function.

Details

Interfaces call their corresponding interfaced function.

Examples

## Not run: 
# library(intubate)
# library(magrittr)
# library(latticeExtra)
# 
# 
# ## ntbt_ecdfplot: Trellis Displays of Empirical CDF
# data(singer, package = "lattice")
# 
# ## Original function to interface
# ecdfplot(~height | voice.part, data = singer)
# 
# ## The interface puts data as first parameter
# ntbt_ecdfplot(singer, ~height | voice.part)
# 
# ## so it can be used easily in a pipeline.
# singer %>%
#   ntbt_ecdfplot(~height | voice.part)
# 
# 
# ## ntbt_mapplot: Trellis displays on Maps a.k.a. Choropleth maps
# library(maps)
# library(mapproj)
# data(USCancerRates)
# 
# ## Original function to interface
# ## Note: Alaska, Hawaii and others are not included in county map;
# ## this generates warnings with both USCancerRates and ancestry.
# suppressWarnings(print(
#   
#   mapplot(rownames(USCancerRates) ~ log(rate.male) + log(rate.female),
#           data = USCancerRates,
#           map = map("county", plot = FALSE, fill = TRUE,
#                     projection = "mercator"))
#   
# ))
# 
# ## The interface puts data as first parameter
# suppressWarnings(print(
#   
#   ntbt_mapplot(USCancerRates, rownames(USCancerRates) ~ log(rate.male) + log(rate.female),
#                map = map("county", plot = FALSE, fill = TRUE,
#                          projection = "mercator"))
# 
#   ))
# 
# ## so it can be used easily in a pipeline.
# suppressWarnings(print(
#   
#   USCancerRates %>%
#   ntbt_mapplot(rownames(USCancerRates) ~ log(rate.male) + log(rate.female),
#                map = map("county", plot = FALSE, fill = TRUE,
#                          projection = "mercator"))
# 
#   ))
# 
# 
# ## ntbt_rootogram: Trellis Displays of Tukey's Hanging Rootograms
# library(lattice)
# dta <- data.frame(x = rpois(1000, lambda = 50))
# 
# ## Original function to interface
# rootogram(~x, data = dta, dfun = function(x) dpois(x, lambda = 50))
# 
# ## The interface puts data as first parameter
# ntbt_rootogram(dta, ~x, dfun = function(x) dpois(x, lambda = 50))
# 
# ## so it can be used easily in a pipeline.
# dta %>%
#   ntbt_rootogram(~x, dfun = function(x) dpois(x, lambda = 50))
# 
# 
# ## ntbt_segplot: Plot segments using the Trellis framework
# data(USCancerRates)
# 
# ## Original function to interface
# segplot(reorder(factor(county), rate.male) ~ LCL95.male + UCL95.male,
#         data = subset(USCancerRates, state == "Washington"))
# 
# ## The interface puts data as first parameter
# ntbt_segplot(subset(USCancerRates, state == "Washington"),
#              reorder(factor(county), rate.male) ~ LCL95.male + UCL95.male)
# 
# ## so it can be used easily in a pipeline.
# subset(USCancerRates, state == "Washington") %>%
#   ntbt_segplot(reorder(factor(county), rate.male) ~ LCL95.male + UCL95.male)
# 
# USCancerRates %>%
#   subset(state == "Washington") %>%
#   ntbt_segplot(reorder(factor(county), rate.male) ~ LCL95.male + UCL95.male)
# 
# 
# ## ntbt_tileplot: Plot a spatial mosaic from irregular 2D points
# tmp <- state.center
# tmp$Income <- state.x77[,"Income"]
# library(deldir)
# 
# ## Original function to interface
# tileplot(Income ~ x * y, tmp, border = "black",
#          panel = function(x, y, ...) {
#            panel.voronoi(x, y, ..., points = FALSE)
#            panel.text(x, y, state.abb, cex = 0.6)
#          })
# 
# ## The interface puts data as first parameter
# ntbt_tileplot(tmp, Income ~ x * y, border = "black",
#               panel = function(x, y, ...) {
#                 panel.voronoi(x, y, ..., points = FALSE)
#                 panel.text(x, y, state.abb, cex = 0.6)
#               })
# 
# ## so it can be used easily in a pipeline.
# tmp %>%
#   ntbt_tileplot(Income ~ x * y, border = "black",
#                 panel = function(x, y, ...) {
#                   panel.voronoi(x, y, ..., points = FALSE)
#                   panel.text(x, y, state.abb, cex = 0.6)
#                 })
# ## End(Not run)