The ‘ExPanDaR’ package offers a toolbox for interactive exploratory data analysis (EDA). Closing down for the year, I finally wrapped up a new version that now allows exploring all sorts of data interactively and generates notebooks containing the analysis all more or less with one line of code and a click. So here comes my little Christmas present for the wonderful RStats community!
As CRAN is taking its well-deserved Christmas break, you will need to install the new version from Github. You can use it on any data frame that contains at least two numeric variables, although it is much more fun if the data frame also contains at least one variable that ExPanD can understand as a discrete variable. Let’s start with a classic:
devtools::install_github("joachim-gassen/ExPanDaR") library(ExPanDaR) ExPanD(mtcars)
Have fun exploring the probably most-explored 32 observations of the data science community. If you like cars and want to get an idea on how you can customize ExPanDaR, you can check-out this online app and the blog post explaining it.
Clicking around in a shiny app is nice but in the end you will most likely want to continue with your own more in-depth analysis. To support this, the new ‘ExPanDaR’ version contains an option to export data and code as a notebook so that you can take your exploratory data analysis to the next level. All it takes is one additional parameter so that you do not accidentally share your data with the world in case you are publicly hosting your shiny app:
ExPanD(mtcars, export_nb_option = TRUE)
After ‘ExPanD’ has started, scroll to the bottom of the page to see the “Export Data and Notebook Code” button.
After clicking the button a download dialog will let you store a zip file. The zip file contains two files
- A notebook file
- A data file
ExPanD_nb_data.RDataholding the data and variable definitions
Unzip the file and load the notebook file in R Studio. It contains the code to prepare all tables and visuals that are displayed by the ‘ExPanD’ app. When sourcing it to an HTML file you should see them rendered as expected.
If everything works as expected the next steps are up to you. Explore the code, modify it to as you please and integrate it in your own analysis. You will see that the code uses some functions of the ‘ExPanDaR’ package that I designed with the typical EDA workflow in mind. Feel free to reuse and remix them for your own analysis workflow.
Enjoy and Happy Holidays everybody!