Generate descriptive statistics
# Install release version from CRAN
install.packages("descriptr")
# Install development version from GitHub
# install.packages("devtools")
devtools::install_github("rsquaredacademy/descriptr")
# Install the development version from `rsquaredacademy` universe
install.packages("descriptr", repos = "https://rsquaredacademy.r-universe.dev")We will use a modified version of the mtcars data set in
the below examples. The only difference between the data sets is related
to the variable types.
str(mtcarz)
#> 'data.frame': 32 obs. of 11 variables:
#> $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
#> $ cyl : Factor w/ 3 levels "4","6","8": 2 2 1 2 3 2 3 1 1 2 ...
#> $ disp: num 160 160 108 258 360 ...
#> $ hp : num 110 110 93 110 175 105 245 62 95 123 ...
#> $ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
#> $ wt : num 2.62 2.88 2.32 3.21 3.44 ...
#> $ qsec: num 16.5 17 18.6 19.4 17 ...
#> $ vs : Factor w/ 2 levels "0","1": 1 1 2 2 1 2 1 2 2 2 ...
#> $ am : Factor w/ 2 levels "0","1": 2 2 2 1 1 1 1 1 1 1 ...
#> $ gear: Factor w/ 3 levels "3","4","5": 2 2 2 1 1 1 1 2 2 2 ...
#> $ carb: Factor w/ 6 levels "1","2","3","4",..: 4 4 1 1 2 1 4 2 2 4 ...ds_summary_stats(mtcarz, mpg)
#> -------------------------------- Variable: 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% 31.30
#> 90% 30.09
#> 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 27.3ds_freq_table(mtcarz, 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 |
#> |-----------------------------------------------------------------------|
#> | Total | 32 | - | 100.00 | - |
#> |-----------------------------------------------------------------------|ds_freq_table(mtcarz, cyl)
#> Variable: cyl
#> -----------------------------------------------------------------------
#> Levels Frequency Cum Frequency Percent Cum Percent
#> -----------------------------------------------------------------------
#> 4 11 11 34.38 34.38
#> -----------------------------------------------------------------------
#> 6 7 18 21.88 56.25
#> -----------------------------------------------------------------------
#> 8 14 32 43.75 100
#> -----------------------------------------------------------------------
#> Total 32 - 100.00 -
#> -----------------------------------------------------------------------ds_cross_table(mtcarz, cyl, 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 | |
#> ----------------------------------------------------------------------------ds_group_summary(mtcarz, cyl, mpg)
#> by
#> -----------------------------------------------------------------------------------------
#> | 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|
#> -----------------------------------------------------------------------------------------ds_tidy_stats(mtcarz, mpg, disp, hp)
#> # A tibble: 3 × 16
#> vars min max mean t_mean median mode range variance stdev skew
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 disp 71.1 472 231. 228 196. 276. 401. 15361. 124. 0.420
#> 2 hp 52 335 147. 144. 123 110 283 4701. 68.6 0.799
#> 3 mpg 10.4 33.9 20.1 20.0 19.2 10.4 23.5 36.3 6.03 0.672
#> # ℹ 5 more variables: kurtosis <dbl>, coeff_var <dbl>, q1 <dbl>, q3 <dbl>,
#> # iqrange <dbl>If you encounter a bug, please file a minimal reproducible example using reprex on github. For questions and clarifications, use StackOverflow.