run_ggquickeda() and clicking on use sample_data: The app will load the built-in example dataset and map the first column to y variable(s) and the second column to x variable and a simple scatter plot with points will be generated: 
This package/R Shiny app is a handy interface to ggplot2/table1. It enables you to quickly explore your data to detect trends on the fly. You can do scatter plots, dotplots, boxplots, barplots, histograms, densities and summary statistics tables For a quick overview using an older version of the app head to this Youtube Tutorial . To get started:
devtools::install_github("smouksassi/ggquickeda")
library(ggquickeda)Let us start by launching the app run_ggquickeda() and clicking on use sample_data: The app will load the built-in example dataset and map the first column to y variable(s) and the second column to x variable and a simple scatter plot with points will be generated:
We want to look at the Column Conc (concentration of drug in blood) versus Time joining each Subject data with a line:
Wait something is wrong! We forgot to tell the app that we want to group by ID.
While we are on this tab let us map Color By: and Column Split: to Gender: 
Now we want to add a loess trend line: * Go to Smooth/Linear/Logistic Regressions (?) and click on the Smooth radio button:
After we made the plot we wanted, now we are interested to do a summary statistics of Weight and Age columns by Gender this will require the following steps: * Change the mapped y variable(s) to Weight, Age and Race
* Go to One Row by ID(s) and select ID so we keep one row by ID
* Go to Descriptive Stats tab
select sample_df.csv
Now launch the application on your own data and start exploring: run_ggquickeda(yourdataname)