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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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.