Generate descriptive statistics
# Install release version from CRANinstall.packages("descriptr")# Install development version from GitHub# install.packages("devtools")devtools::install_github("rsquaredacademy/descriptr")# Install the development version from `rsquaredacademy` universeinstall.packages("descriptr",repos ="https://rsquaredacademy.r-universe.dev")We will use a modified version of themtcars data set inthe below examples. The only difference between the data sets is relatedto 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 exampleusingreprex ongithub. For questions and clarifications, useStackOverflow.