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 27.3
ds_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| #> -----------------------------------------------------------------------------------------Multiple Variable Statistics
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.
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