descriptr: Generate descriptive statistics and explore distributions
Author: Aravind Hebbali License: MIT
Overview
The goal of descriptr is to ease the process of generating descriptive statistics and exploring statistical distributions.
Installation
# install descriptr from CRAN
install.packages("descriptr")
# the development version from github
# install.packages("devtools")
devtools::install_github("rsquaredacademy/descriptr")Features
Descriptive Statistics
- Summary Statistics
- Two Way Tables
- One Way Table
- One Way Table (Continuous Data)
- Group Wise Summary
- Multiple Column Descriptive Statistics
- Multiple One Way Tables
- Multiple Two Way Tables
Explore Distributions
- Normal
- Binomial
- Chi Square
- F
- t
Shiny App
Use ds_launch_shiny_app() to explore the package using a shiny app.
Vignettes
Usage
Summary Statistics
ds_summary_stats(mtcars$mpg)
#> Univariate Analysis
#>
#> N 32.00 Variance 36.32
#> Missing 0.00 Std Deviation 6.03
#> Mean 20.09 Range 23.50
#> Median 19.20 Interquartile Range 7.38
#> Mode 10.40 Uncorrected SS 14042.31
#> Trimmed Mean 19.95 Corrected SS 1126.05
#> Skewness 0.67 Coeff Variation 30.00
#> Kurtosis -0.02 Std Error Mean 1.07
#>
#> Quantiles
#>
#> Quantile Value
#>
#> Max 33.90
#> 99% 33.44
#> 95% 30.09
#> 90% 31.30
#> Q3 22.80
#> Median 19.20
#> Q1 15.43
#> 10% 14.34
#> 5% 12.00
#> 1% 10.40
#> Min 10.40
#>
#> Extreme Values
#>
#> Low High
#>
#> Obs Value Obs Value
#> 15 10.4 20 33.9
#> 16 10.4 18 32.4
#> 24 13.3 19 30.4
#> 7 14.3 28 30.4
#> 17 14.7 26 27.3Two Way Table
ds_cross_table(mtcars$cyl, mtcars$gear)
#> Cell Contents
#> |---------------|
#> | Frequency |
#> | Percent |
#> | Row Pct |
#> | Col Pct |
#> |---------------|
#>
#> Total Observations: 32
#>
#> ----------------------------------------------------------------------------
#> | | gear |
#> ----------------------------------------------------------------------------
#> | cyl | 3 | 4 | 5 | Row Total |
#> ----------------------------------------------------------------------------
#> | 4 | 1 | 8 | 2 | 11 |
#> | | 0.031 | 0.25 | 0.062 | |
#> | | 0.09 | 0.73 | 0.18 | 0.34 |
#> | | 0.07 | 0.67 | 0.4 | |
#> ----------------------------------------------------------------------------
#> | 6 | 2 | 4 | 1 | 7 |
#> | | 0.062 | 0.125 | 0.031 | |
#> | | 0.29 | 0.57 | 0.14 | 0.22 |
#> | | 0.13 | 0.33 | 0.2 | |
#> ----------------------------------------------------------------------------
#> | 8 | 12 | 0 | 2 | 14 |
#> | | 0.375 | 0 | 0.062 | |
#> | | 0.86 | 0 | 0.14 | 0.44 |
#> | | 0.8 | 0 | 0.4 | |
#> ----------------------------------------------------------------------------
#> | Column Total | 15 | 12 | 5 | 32 |
#> | | 0.468 | 0.375 | 0.155 | |
#> ----------------------------------------------------------------------------One Way Table
ds_freq_table(mtcars$cyl)
#> Variable: cyl
#> |--------------------------------------------------------------------------|
#> | Cumulative Cumulative |
#> | Levels | Frequency | Frequency | Percent | Percent |
#> |--------------------------------------------------------------------------|
#> | 4 | 11 | 11 | 34.38 | 34.38 |
#> |--------------------------------------------------------------------------|
#> | 6 | 7 | 18 | 21.88 | 56.25 |
#> |--------------------------------------------------------------------------|
#> | 8 | 14 | 32 | 43.75 | 100 |
#> |--------------------------------------------------------------------------|One Way Table (Continuous Data)
ds_freq_cont(mtcars$mpg)
#> Variable: mpg
#> |-----------------------------------------------------------------------|
#> | Bins | Frequency | Cum Frequency | Percent | Cum Percent |
#> |-----------------------------------------------------------------------|
#> | 10.4 - 15.1 | 6 | 6 | 18.75 | 18.75 |
#> |-----------------------------------------------------------------------|
#> | 15.1 - 19.8 | 12 | 18 | 37.5 | 56.25 |
#> |-----------------------------------------------------------------------|
#> | 19.8 - 24.5 | 8 | 26 | 25 | 81.25 |
#> |-----------------------------------------------------------------------|
#> | 24.5 - 29.2 | 2 | 28 | 6.25 | 87.5 |
#> |-----------------------------------------------------------------------|
#> | 29.2 - 33.9 | 4 | 32 | 12.5 | 100 |
#> |-----------------------------------------------------------------------|Group Summary
ds_group_summary(mtcars$cyl, mtcars$mpg)
#> mpg by cyl
#> -----------------------------------------------------------------------------------------
#> | Statistic/Levels| 4| 6| 8|
#> -----------------------------------------------------------------------------------------
#> | Obs| 11| 7| 14|
#> | Minimum| 21.4| 17.8| 10.4|
#> | Maximum| 33.9| 21.4| 19.2|
#> | Mean| 26.66| 19.74| 15.1|
#> | Median| 26| 19.7| 15.2|
#> | Mode| 22.8| 21| 10.4|
#> | Std. Deviation| 4.51| 1.45| 2.56|
#> | Variance| 20.34| 2.11| 6.55|
#> | Skewness| 0.35| -0.26| -0.46|
#> | Kurtosis| -1.43| -1.83| 0.33|
#> | Uncorrected SS| 8023.83| 2741.14| 3277.34|
#> | Corrected SS| 203.39| 12.68| 85.2|
#> | Coeff Variation| 16.91| 7.36| 16.95|
#> | Std. Error Mean| 1.36| 0.55| 0.68|
#> | Range| 12.5| 3.6| 8.8|
#> | Interquartile Range| 7.6| 2.35| 1.85|
#> -----------------------------------------------------------------------------------------Multiple Variable Statistics
ds_multi_stats(mtcars, mpg, disp, hp)
#> # A tibble: 3 x 16
#> vars min max mean t_mean median mode range variance
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 disp 71.1 472.0 230.72188 228.00000 196.3 275.8 400.9 15360.7998
#> 2 hp 52.0 335.0 146.68750 143.56667 123.0 110.0 283.0 4700.8669
#> 3 mpg 10.4 33.9 20.09062 19.95333 19.2 10.4 23.5 36.3241
#> # ... with 7 more variables: stdev <dbl>, skew <dbl>, kurtosis <dbl>,
#> # coeff_var <dbl>, q1 <dbl>, q3 <dbl>, iqrange <dbl>Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.