interactive.eda_d3js: Interactive Dashboard for Exploratory Data Analysis (d3js)
In Laurae2/Laurae: Advanced High Performance Data Science Toolbox for R

Description Usage Arguments Details Value Examples

This function runs an interactive dashboard which allows to explore data via 3djs and NVD3. Unlike its counterpart interactive.eda_ggplot, using 3djs is not efficient for large data (10K+ observations) and automated smart plotting is not available. In addition, the filtering method is currently broken. This function is not recommended if you want d3js plot and you should use interactive.eda_plotly.

interactive.eda_d3js(data, type = "scatterChart",
  dep_var = colnames(data)[1], indep_var = "None", group_var = "None",
  filter_var = "None", plot_width = 1500, plot_height = 820,
  f_back = "red", side_width = 300)

`data`	Type: data.table (preferred) or data.frame. The data you want to explore. Using a data.table increases the processing speed.
`type`	Type: character. The type of plot requested to d3js nvds. You may choose between `"lineChart"`, `"scatterChart"`, `"stackedAreaChart"`, `"discreteBarChart"`, `"multiBarChart"`, `"multiBarHorizontalChart"`, `"linePlusBarChart"`, `"cumulativeLineChart"`, `"lineWithFocusChart"`, `"pieChart"`, `"bulletChart"`. Defaults to `"scatterChart"`.
`dep_var`	Type: character (currently overriden). The dependent variable to plot. Defaults to `colnames(data)[1]`, a reference to the first column of `data`.
`indep_var`	Type: character (currently overriden). The independent variable to plot. Defaults to `"None"`.
`group_var`	Type: character (currently overriden). The grouping variable to plot. Defaults to `"None"`.
`filter_var`	Type: character (feature currently broken). The filtering variable to plot. Defaults to `"None"`.
`plot_width`	Type: numeric. The width for the plot. Defaults to `1500`, which fits nicely Full HD screens (1920 vertical pixels).
`plot_height`	Type: numeric. The height for the plot. Defaults to `820`, which fits nicely Full HD screens (1080 vertical pixels).
`f_back`	Type: character. A background color character for the header. Defaults to `"red"`.
`side_width`	Type: numeric. The width of the sidebar containing variable names. Defaults to `300`.

Plotting is done using rCharts, which must be loaded before running this function. There are issues if you open this in Internet Explorer 9 or under.

The colors (header: f_back) allowed are the following:

blue: blue color
black: black color
purple: purple color
green: green color
red: red color
yellow: yellow color

Nothing

## Not run: 
library(shiny)
library(shinydashboard)
library(rCharts)
library(datasets)
hair_eye <- as.data.frame(HairEyeColor)
interactive.eda_d3js(data = hair_eye,
                     type = "multiBarChart",
                     dep_var = "Hair", #ignored
                     indep_var = "Freq", #ignored
                     group_var = "Sex", #ignored
                     plot_width = 600,
                     plot_height = 420,
                     f_back = "red",
                     side_width = 300)

## End(Not run)