Package index • dataProfilerR

Main pipeline

The single entry point and the profile object it returns.

profile_data(): Profile a data frame
is_data_profile(): Is an object a data_profile?
report(): Render a profile to a self-contained HTML report

Methods for a profile

S3 methods on the data_profile object.

print(<data_profile>): Print a concise overview of a data profile
summary(<data_profile>): Detailed summary of a data profile
plot(<data_profile>): Plot a data profile

Profiling engine

Column types, missingness, summary statistics, data-quality score.

infer_column_types(): Infer a semantic type for each column
analyze_missing(): Analyse missing values
summarize_columns(): Summary statistics by column type
data_quality_score(): Data quality score
skewness(): Sample skewness
kurtosis(): Sample excess kurtosis

Statistical analysis

Normality, outliers, correlation, categorical association, dates, groups.

normality_tests(): Normality tests for numeric columns
detect_outliers(): Detect outliers in a numeric vector
outlier_summary(): Outlier summary across numeric columns
correlation_analysis(): Correlation analysis
categorical_association(): Categorical association (Cramer's V)
analyze_dates(): Profile date / datetime columns
compare_groups(): Compare numeric columns across groups

Visualisation

ggplot2 figures for each part of the profile.

plot_association(): Categorical association heatmap
plot_boxplots(): Boxplots for numeric columns
plot_correlation(): Correlation heatmap
plot_distribution(): Distribution plot for a single column
plot_missing(): Missing-value heatmap
plot_pairs(): Pairwise scatterplot matrix

Package

dataProfilerR dataProfilerR-package: dataProfilerR: automated exploratory data analysis