dlookr.R

install.packages("dlookr")

pacman::p_load(tidyverse,dlookr)

data(flights)
dim(flights)
flights
diagnose(flights)
diagnose_numeric(flights)
diagnose_category(flights)
diagnose_outlier(flights)

diagnose_outlier(flights)  |>   
  filter(outliers_cnt >0)

plot_normality(flights, distance)

carseats <-data(Carseats)
plot_correlate()


# Calculates the all categorical variables
all_var <- univar_numeric(heartfailure)

# Print univar_numeric class object
all_var

# Calculates the platelets, sodium variable
univar_numeric(heartfailure, platelets, sodium)

# Summary the all case : Return a invisible copy of an object.
stat <- summary(all_var)

# Summary by returned object
stat

# Statistics of numerical variables normalized by Min-Max method
summary(all_var, stand = "minmax")

# Statistics of numerical variables standardized by Z-score method
summary(all_var, stand = "zscore")

# one plot with all variables
plot(all_var)

# one plot with all normalized variables by Min-Max method
plot(all_var, stand = "minmax")

# one plot with all variables
plot(all_var, stand = "none")

# one plot with all robust standardized variables 
plot(all_var, viz = "boxplot")

# one plot with all standardized variables by Z-score method 
plot(all_var, viz = "boxplot", stand = "zscore")

# individual boxplot by variables
plot(all_var, indiv = TRUE, "boxplot")

# individual histogram by variables
plot(all_var, indiv = TRUE, "hist")

# individual histogram by robust standardized variable 
plot(all_var, indiv = TRUE, "hist", stand = "robust")

# plot all variables by prompt
plot(all_var, indiv = TRUE, "hist", prompt = TRUE)