Exploratory Data Analysis in R (edar) is a R package designed to reduce the amount of code needed to do EDA in R. It provides a set of wrap functions that incapsulate some tidyverse functionalities.
devtools::install_github("DiogoFerrari/edar")
# If you don't want to update the dependencies, use: (you may need to install some dependencies manually)
devtools::install_github("DiogoFerrari/edar", dependencies=F)
library(edar)
library(magrittr)
data(edar_survey)
data = edar_survey
# help(data)
## summarise all numerical variables
data %>% summarise_alln(., group=NULL, weight=NULL, spread=F)
data %>% summarise_alln(., group="gender", weight=NULL, spread=F)
## summarise all categorical variables
data %>% summarise_allc(., group=NULL)
data %>% summarise_allc(., group="gender")
## bundle all cateorical variables based on their categories and summarise them
tab = data %>% summarise_allcbundle(., group=NULL)
tab
tab$Table[[1]] ## Table with counts
tab$Tablep[[1]] ## Table with percentages
tab$Tablel[[1]] ## Table with counts and percentages
## check balance of covariates between two groups (ex: treatment vs control, see Imbens, G. W., & Rubin, D. B., Causal inference in statistics, social, and biomedical sciences: an introduction (2015), : Cambridge University Press.)
data %>% ebalance(., treatmentVar='treat')
See other functions in the package vignette.
vignette(edar)See this webpage and pdf with examples.