print and summary method for "univar_numeric" class.

# S3 method for univar_numeric
summary(object, stand = c("robust", "minmax", "zscore"), ...)

# S3 method for univar_numeric
print(x, ...)

Arguments

object

an object of class "univar_numeric", usually, a result of a call to univar_numeric().

stand

character Describe how to standardize the original data. "robust" normalizes the raw data through transformation calculated by IQR and median. "minmax" normalizes the original data using minmax transformation. "zscore" standardizes the original data using z-Score transformation. The default is "robust".

...

further arguments passed to or from other methods.

x

an object of class "univar_numeric", usually, a result of a call to univar_numeric().

Value

An object of the class as indivisual variabes based list. The statistics returned by summary.univar_numeric() are different from the statistics returned by univar_numeric(). univar_numeric() is the statistics for the original data, but summary. univar_numeric() is the statistics for the standardized data. A component named "statistics" is a tibble object with the following statistics.:

  • variable : factor. The level of the variable. 'variable' is the name of the variable.

  • n : number of observations excluding missing values

  • na : number of missing values

  • mean : arithmetic average

  • sd : standard deviation

  • se_mean : standard error mean. sd/sqrt(n)

  • IQR : interquartile range (Q3-Q1)

  • skewness : skewness

  • kurtosis : kurtosis

  • median : median. 50% percentile

Details

print.univar_numeric() displays only the information of variables included in univar_numeric The "variables" attribute is not displayed.

See also

Examples

# \donttest{ # Calculates the all categorical variables all_var <- univar_numeric(heartfailure) # Print univar_numeric class object all_var
#> $statistics #> # A tibble: 7 x 10 #> variable n na mean sd se_mean IQR skewness kurtosis median #> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 age 299 0 6.08e1 1.19e1 6.88e-1 19 0.424 -0.184 6 e1 #> 2 cpk_enzyme 299 0 5.82e2 9.70e2 5.61e+1 466. 4.46 25.1 2.5 e2 #> 3 ejection_… 299 0 3.81e1 1.18e1 6.84e-1 15 0.555 0.0414 3.8 e1 #> 4 platelets 299 0 2.63e5 9.78e4 5.66e+3 91000 1.46 6.21 2.62e5 #> 5 creatinine 299 0 1.39e0 1.03e0 5.98e-2 0.5 4.46 25.8 1.1 e0 #> 6 sodium 299 0 1.37e2 4.41e0 2.55e-1 6 -1.05 4.12 1.37e2 #> 7 time 299 0 1.30e2 7.76e1 4.49e+0 130 0.128 -1.21 1.15e2 #>
# Calculates the platelets, sodium variable univar_numeric(heartfailure, platelets, sodium)
#> $statistics #> # A tibble: 2 x 10 #> variable n na mean sd se_mean IQR skewness kurtosis median #> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 platelets 299 0 263358. 97804. 5656. 91000 1.46 6.21 262000 #> 2 sodium 299 0 137. 4.41 0.255 6 -1.05 4.12 137 #>
# Summary the all case : Return a invisible copy of an object. stat <- summary(all_var) # Summary by returned object stat
#> # A tibble: 7 x 8 #> variable mean sd se_mean IQR skewness kurtosis median #> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 age 0.0437 0.626 0.0362 1 0.424 -0.184 0 #> 2 cpk_enzyme 0.713 2.08 0.121 1 4.46 25.1 0 #> 3 ejection_fraction 0.00557 0.789 0.0456 1 0.555 0.0414 0 #> 4 platelets 0.0149 1.07 0.0622 1 1.46 6.21 0 #> 5 creatinine 0.588 2.07 0.120 1 4.46 25.8 0 #> 6 sodium -0.0624 0.735 0.0425 1 -1.05 4.12 0 #> 7 time 0.117 0.597 0.0345 1 0.128 -1.21 0
# Statistics of numerical variables normalized by Min-Max method summary(all_var, stand = "minmax")
#> # A tibble: 7 x 8 #> variable mean sd se_mean IQR skewness kurtosis median #> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 age 0.379 0.216 0.0125 0.345 0.424 -0.184 0.364 #> 2 cpk_enzyme 0.0713 0.124 0.00716 0.0594 4.46 25.1 0.0290 #> 3 ejection_fraction 0.365 0.179 0.0104 0.227 0.555 0.0414 0.364 #> 4 platelets 0.289 0.119 0.00686 0.110 1.46 6.21 0.287 #> 5 creatinine 0.100 0.116 0.00672 0.0562 4.46 25.8 0.0674 #> 6 sodium 0.675 0.126 0.00729 0.171 -1.05 4.12 0.686 #> 7 time 0.449 0.276 0.0160 0.463 0.128 -1.21 0.395
# Statistics of numerical variables standardized by Z-score method summary(all_var, stand = "zscore")
#> # A tibble: 7 x 8 #> variable mean sd se_mean IQR skewness kurtosis median #> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 age 2.01e-16 1 0.0578 1.60 0.424 -0.184 -0.0697 #> 2 cpk_enzyme -1.33e-17 1 0.0578 0.480 4.46 25.1 -0.342 #> 3 ejection_fraction -2.48e-17 1 0.0578 1.27 0.555 0.0414 -0.00706 #> 4 platelets 8.98e-17 1 0.0578 0.930 1.46 6.21 -0.0139 #> 5 creatinine -7.88e-17 1 0.0578 0.483 4.46 25.8 -0.284 #> 6 sodium -8.82e-16 1 0.0578 1.36 -1.05 4.12 0.0849 #> 7 time -1.80e-16 1 0.0578 1.67 0.128 -1.21 -0.197
# }