scan_data: Thoroughly scan a table to better understand it

In pointblank: Data Validation and Organization of Metadata for Local and Remote Tables

Thoroughly scan a table to better understand it

Description

Generate an HTML report that scours the input table data. Before calling up an agent to validate the data, it's a good idea to understand the data with some level of precision. Make this the initial step of a well-balanced data quality reporting workflow. The reporting output contains several sections to make everything more digestible, and these are:

Overview

Table dimensions, duplicate row counts, column types, and reproducibility information

Variables

A summary for each table variable and further statistics and summaries depending on the variable type

Interactions

A matrix plot that shows interactions between variables

Correlations

A set of correlation matrix plots for numerical variables

Missing Values

A summary figure that shows the degree of missingness across variables

Sample

A table that provides the head and tail rows of the dataset

The resulting object can be printed to make it viewable in the RStudio Viewer. It's also a "shiny.tag.list" object and so can be integrated in R Markdown HTML output or in Shiny applications. If you need the output HTML, it's to export that to a file with the export_report() function.

Usage

scan_data(
  tbl,
  sections = "OVICMS",
  navbar = TRUE,
  width = NULL,
  lang = NULL,
  locale = NULL
)

Arguments

tbl	A data table ⁠obj:<tbl_*>⁠ // required The input table. This can be a data frame, tibble, a tbl_dbi object, or a tbl_spark object.
sections	Sections to include ⁠scalar<character>⁠ // default: "OVICMS" The sections to include in the finalized ⁠Table Scan⁠ report. A string with key characters representing section names is required here. The default string is "OVICMS" wherein each letter stands for the following sections in their default order: "O": "overview"; "V": "variables"; "I": "interactions"; "C": "correlations"; "M": "missing"; and "S": "sample". This string can be comprised of less characters and the order can be changed to suit the desired layout of the report. For tbl_dbi and tbl_spark objects supplied to tbl, the "interactions" and "correlations" sections are currently excluded.
navbar	Include navigation in HTML report ⁠scalar<logical>⁠ // default: TRUE Should there be a navigation bar anchored to the top of the report page?
width	Width option for HTML report ⁠scalar<integer>⁠ // default: NULL (optional) An optional fixed width (in pixels) for the HTML report. By default, no fixed width is applied.
lang	Reporting language ⁠scalar<character>⁠ // default: NULL (optional) The language to use for label text in the report. By default, NULL will create English ("en") text. Other options include French ("fr"), German ("de"), Italian ("it"), Spanish ("es"), Portuguese ("pt"), Turkish ("tr"), Chinese ("zh"), Russian ("ru"), Polish ("pl"), Danish ("da"), Swedish ("sv"), and Dutch ("nl").
locale	Locale for value formatting within reports ⁠scalar<character>⁠ // default: NULL (optional) An optional locale ID to use for formatting values in the report according the locale's rules. Examples include "en_US" for English (United States) and "fr_FR" for French (France); more simply, this can be a language identifier without a country designation, like "es" for Spanish (Spain, same as "es_ES").

Value

A ptblank_tbl_scan object.

Examples

Get an HTML document that describes all of the data in the dplyr::storms dataset.

tbl_scan <- scan_data(tbl = dplyr::storms)

Function ID

1-1

See Also

Other Planning and Prep: action_levels(), create_agent(), create_informant(), db_tbl(), draft_validation(), file_tbl(), tbl_get(), tbl_source(), tbl_store(), validate_rmd()

pointblank documentation built on Oct. 30, 2024, 9:29 a.m.