# Summary Statistics

`summary-statistics.Rd`

*collapse* provides the following functions to efficiently summarize and examine data:

`qsu`

, shorthand for quick-summary, is an extremely fast summary command inspired by the (xt)summarize command in the STATA statistical software. It computes a set of 7 statistics (nobs, mean, sd, min, max, skewness and kurtosis) using a numerically stable one-pass method. Statistics can be computed weighted, by groups, and also within-and between entities (for multilevel / panel data).`qtab`

, shorthand for quick-table, is a faster and more versatile alternative to`table`

. Notably, it also supports tabulations with frequency weights, as well as computing a statistic over combinations of variables. 'qtab's inherit the 'table' class, allowing for seamless application of 'table' methods.`descr`

computes a concise and detailed description of a data frame, including (sorted) frequency tables for categorical variables and various statistics and quantiles for numeric variables. It is inspired by`Hmisc::describe`

, but about 10x faster.`pwcor`

,`pwcov`

and`pwnobs`

compute (weighted) pairwise correlations, covariances and observation counts on matrices and data frames. Pairwise correlations and covariances can be computed together with observation counts and p-values. The elaborate print method displays all of these statistics in a single correlation table.`varying`

very efficiently checks for the presence of any variation in data (optionally) within groups (such as panel-identifiers). A variable is variant if it has at least 2 distinct non-missing data points.

## Table of Functions

Function / S3 Generic | Methods | Description | ||

`qsu` | `default, matrix, data.frame, grouped_df, pseries, pdata.frame, sf` | Fast (grouped, weighted, panel-decomposed) summary statistics | ||

`qtab` | No methods, for data frames or vectors | Fast (weighted) cross tabulation | ||

`descr` | `default, grouped_df` (default method handles most objects) | Detailed statistical description of data frame | ||

`pwcor` | No methods, for matrices or data frames | Pairwise (weighted) correlations | ||

`pwcov` | No methods, for matrices or data frames | Pairwise (weighted) covariances | ||

`pwnobs` | No methods, for matrices or data frames | Pairwise observation counts | ||

`varying` | `default, matrix, data.frame, pseries, pdata.frame, grouped_df` | Fast variation check |