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Data profiling report

As explained in Statistics Slam Dunk

A data profiling report is a consolidated summary of a dataset's structure, completeness, distributions, and relationships.

A data profiling report consolidates exploratory data analysis into a shareable interactive HTML file. It summarizes a dataset’s structure, missingness, distributions, categorical variables, and correlations. section 17.4.2

A generated report can include:

  • Dataset dimensions, variable types, missing values, complete rows, observations, and memory usage. section 17.4.2
  • Visual views of structure, missingness, histograms, QQ plots, density plots, correlations, and categorical frequencies. section 17.4.2
  • Grouped bar charts, such as categorical distributions organized by month. section 17.4.2

Profiling NBA betting data

After wrangling the oddsdf3 dataset, run create_report(oddsdf3) to generate a standalone interactive report. The dataset contains 1,230 rows, 14 columns, seven discrete columns, seven continuous columns, and no missing values. section 17.4.2

create_report(oddsdf3)

Run the DataExplorer report-generation command for the prepared dataset. section 17.4.2

How Statistics Slam Dunk covers it

How deep it goes
Combines many structural and visual summaries but stops short of the more selective interpretation of manual EDA.
Examples
Uses NBA odds data with structure plots, missingness profiles, histograms, QQ plots, density plots, heat maps, and bar charts.
What it assumes
Assumes a prepared R dataset and basic data wrangling, while demonstrating automated profiling from a single function call.
What you can do after
Evaluate a prepared dataset quickly through a consolidated interactive HTML summary.
How it connects
Connects exploratory data analysis with missing values, distributions, categorical frequencies, correlations, and data structure.
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Related concepts

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