README.md
In tidySummaries: Tidy Statistical Summaries for Exploratory Data Analysis

tidySummaries

Tidy statistical summaries made simple

tidySummaries provides a modern and extensible set of functions for descriptive statistics, frequency analysis, and significance testing — all with tidy output.

It’s ideal for both numeric and categorical exploratory data analysis, supporting group comparisons, normality checks, console coloring, and more.

Tidy descriptive statistics summarise_statistics() computes mean, median, standard deviation, variance, skewness, kurtosis, IQR, MAD, and CV in a single tidy tibble.
Frequency tables summarise_frequency() summarizes categorical variables with frequency counts, proportions, or percentages.
Normality and group significance testing Automatically perform Shapiro-Wilk tests for normality, plus t-tests, Wilcoxon tests, ANOVA, or Kruskal-Wallis tests for group comparisons.
Grouped summaries summarise_group_stats() groups data by one or more variables and summarizes selected numeric columns flexibly.
Correlation analysis summarise_correlation() computes pairwise correlations (Pearson, Spearman, Kendall) and highlights significant results.
Boxplot statistics with outlier detection summarise_boxplot_stats() returns min, Q1, median, Q3, max, range, IQR, and detected outliers for numeric data.
Colored console output for significance Statistically significant results are automatically highlighted in red for easy identification.
Support for vectors, matrices, and data frames Functions handle vectors, matrices, tibbles, and grouped data frames smoothly.
Tidyverse-friendly design Pipeable and fully compatible with tidyverse workflows. All outputs are clean tibbles ready for further analysis or visualization.