cog: Cast Column as a Cognostic

In trelliscopejs: Create Interactive Trelliscope Displays

Description

Cast a column of a cognostics data frame as a cognostic object

Usage

cog(
  val = NULL,
  desc = "",
  group = "common",
  type = NULL,
  default_label = FALSE,
  default_active = TRUE,
  filterable = TRUE,
  sortable = TRUE,
  log = NULL
)

Arguments

val	a scalar value (numeric, character, date, etc.)
desc	a description for this cognostic value
group	optional categorization of the cognostic for organizational purposes in the viewer (currently not implemented in the viewer)
type	the desired type of cognostic you would like to compute (see details)
default_label	should this cognostic be used as a panel label in the viewer by default?
default_active	should this cognostic be active (available for sort / filter / sample) by default?
filterable	should this cognostic be filterable? Default is TRUE. It can be useful to set this to FALSE if the cognostic is categorical with many unique values and is only desired to be used as a panel label.
sortable	should this cognostic be sortable?
log	when being used in the viewer for visual univariate and bivariate filters, should the log be computed? Useful when the distribution of the cognostic is very long-tailed or has large outliers. Can either be a logical or a positive integer indicating the base.

Details

Different types of cognostics can be specified through the type argument that will affect how the user is able to interact with those cognostics in the viewer. This can usually be ignored because it will be inferred from the implicit data type of val. But there are special types of cognostics, such as geographic coordinates and relations (not implemented) that can be specified as well. Current possibilities for type are "key", "integer", "numeric", "factor", "date", "time", "href".

Value

object of class "cog"

Examples

library(dplyr)
library(tidyr)
library(purrr)
library(ggplot2)
library(plotly)

mpg_cog <- mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(
    cogs = map_cog(data, ~ tibble(
      mean_city_mpg = cog(mean(.$cty), desc = "Mean city mpg"),
      mean_hwy_mpg = cog(mean(.$hwy), desc = "Mean highway mpg"),
      most_common_drv = cog(tail(names(table(.$drv)), 1), desc = "Most common drive type")
    )),
    panel = map_plot(data, function(x) {
      plot_ly(data = x, x = ~cty, y = ~hwy,
        type = "scatter", mode = "markers") %>%
        layout(
          xaxis = list(range = c(9, 47)),
          yaxis = list(range = c(7, 37)))
    })
  )

trelliscope(mpg_cog, name = "city_vs_highway_mpg", nrow = 1, ncol = 2)

Example output

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union


Attaching package: ‘plotly’

The following object is masked from ‘package:ggplot2’:

    last_plot

The following object is masked from ‘package:stats’:

    filter

The following object is masked from ‘package:graphics’:

    layout

Warning message:
`arrange_()` is deprecated as of dplyr 0.7.0.
Please use `arrange()` instead.
See vignette('programming') for more help
This warning is displayed once every 8 hours.
Call `lifecycle::last_warnings()` to see where this warning was generated. 

trelliscopejs documentation built on Feb. 1, 2021, 9:05 a.m.