DataExplorer (version 0.7.0)

create_report: create_report Function

Description

This function creates a data profiling report.

Usage

create_report(data, output_file = "report.html", output_dir = getwd(),
  y = NULL, config = list(), ...)

Arguments

data

input data

output_file

output file name. The default is "report.html".

output_dir

output directory for report. The default is user's current directory.

y

name of response variable if any. Response variables will be passed to appropriate plotting functions automatically.

config

report configuration with function arguments as list. See details.

…

other arguments to be passed to render.

Details

config is a named list to be evaluated by create_report. Each name should exactly match a function name. By doing so, that function and corresponding content will be added to the report. If you do not want to include certain functions/content, do not add it to config.

By default, there is a preset config object (refer to example). In case you would like to customize the report, copy and edit the code and pass it to config argument.

All function arguments will be passed to do.call as a list.

Examples

# NOT RUN {
#############################
## Default config file     ##
## Copy and edit if needed ##
#############################
config <- list(
  "introduce" = list(),
  "plot_str" = list(
    "type" = "diagonal",
    "fontSize" = 35,
    "width" = 1000,
    "margin" = list("left" = 350, "right" = 250)
  ),
  "plot_missing" = list(),
  "plot_histogram" = list(),
  "plot_qq" = list(sampled_rows = 1000L),
  "plot_bar" = list(),
  "plot_correlation" = list("cor_args" = list("use" = "pairwise.complete.obs")),
  "plot_prcomp" = list(),
  "plot_boxplot" = list(),
  "plot_scatterplot" = list(sampled_rows = 1000L)
)

# Create report
create_report(iris)
create_report(airquality, y = "Ozone")

# Load library
library(ggplot2)
library(data.table)
library(rmarkdown)

# Set some missing values
diamonds2 <- data.table(diamonds)
for (j in 5:ncol(diamonds2)) {
  set(diamonds2,
      i = sample.int(nrow(diamonds2), sample.int(nrow(diamonds2), 1)),
      j,
      value = NA_integer_)
}

# Create customized report for diamonds2 dataset
create_report(
  data = diamonds2,
  output_file = "report.html",
  output_dir = getwd(),
  y = "price",
  config = list(
    "introduce" = list(),
    "plot_missing" = list(),
    "plot_histogram" = list(),
    "plot_qq" = list("by" = "cut", sampled_rows = 1000L),
    "plot_bar" = list("with" = "carat"),
    "plot_correlation" = list("cor_args" = list("use" = "pairwise.complete.obs")),
    "plot_prcomp" = list(),
    "plot_boxplot" = list("by" = "cut")
  ),
  html_document(toc = TRUE, toc_depth = 6, theme = "flatly")
)
# }