README

Whenever I start working on a dataset, I need to take a glance at the data to see how the data are or it the format is the one that I am expecting. I found myself coding similar lines over and over again with each data set I put my hands on. I decided to put that lines together in an R package so I and others can use them. I called it glancedata.

There are already some cool R packages to summarize dataframes. The ones that I use more often are skimr and GGally.

Installation

install.packages("glancedata")

Functions

These are the main functions in the package. You can see their documentation with help, e.g., help("glance_data").

Example

Function	Description
`glance_data`	Alternative to `summary`. Emphasizes missing data and binary variables.
`glance_data_in_workbook`	Similar to `glance_data`. Creates list of dataframes instead and saves XLSX file.
`plot_numerical_vars`	Creates a plot per numerical variable. It might be histogram, density plot, qqplot, violin plot or scatterplot.
`plot_discrete_vars`	Creates a plot per numerical variable. It might be histogram, density plot, qqplot, violin plot or scatterplot.

You can copy and paste the code and use your own dataset. I am using the mtcars dataframe.


library(glancedata)

## This will generate a dataframe
glance_data(mtcars)

## Create a list of dataframes. If you provide the `filename` 
## parameter to be equal to, say, "myglance.xlsx", then it will create
## an Excel workbook and place the content of each dataframe in a 
## separate sheet.
glance_data_in_workbook(mtcars)

## These are the types of plots for numerical variables
plot_numerical_vars(mtcars, plot_type = "density")
plot_numerical_vars(mtcars, plot_type = "pairwise")
plot_numerical_vars(mtcars, plot_type = "histogram")
plot_numerical_vars(mtcars, plot_type = "violin")
plot_numerical_vars(mtcars, plot_type = "boxplot")
plot_numerical_vars(mtcars, plot_type = "qqplot")

## ... And here are barplots for variables with only a few different 
## values
plot_discrete_vars(mtcars)
plot_discrete_vars(mtcars, sort_by_frequency = TRUE)