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.

Features

• 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.

Installation

You can install the development version from GitHub:

```r # install.packages(“devtools”) devtools::install_github(“kleanthisk10/tidySummaries”)