Data Pal

Inspiration

As a graduate student of Psychology, dealing with data is my everyday job. Many students in our lab and in the department are still using Excel or SPSS to clean and visualize data, I am a big fan of R language, and I hope everyone can appreciate the beauty of R language in data analysis. I create this interactive program for newcomers to R to do some data wrangling and to visualize results really quickly.

What it does

• import multiple data files
• summarize data
• explore bivariate relationships and plot
• more to come

How I built it

I used an R package named Shiny (http://shiny.rstudio.com/) to build this web application.

Challenges I ran into

I have used R language for years, but have no prior knowledge of Shiny, so I can say I start this project from scratch. I spent half of the time reading tutorials and ran into many problems when really started to program. I kind of regretted that I spent too much time figuring out harder challenges instead of building easier parts first.

Accomplishments that I'm proud of

I am proud that I learned a new package (the one I always want to learn) during this weekend, and was able to use it to build a real web application, which also I always want to do.

What I learned

• it is pretty hard to build an interactive program, I started to appreciate the complexity of Excel and SPSS.
• knowledge of Shiny

What's next for Data Pal

Submitting the project is not an end, I basically just built the backbone of the web application. In the future, more features will be added, including:

• More refined plot features
• When importing multiple files, the program currently combines all data into one data frame and do analyses on the whole. In the future, you will be able to apply same opearations on one data file to all the files you load and write out processed individual data
• Basic data clean features, such as filtering, recoding, renaming, mutating etc, will be added
• Saving and visualizing the processing steps you did on the data for future check
• Providing runnable analysis code. So, after some clicks, processing code which can do the same work as the web app will be generated, and you can just use it in your own R console.

Built With

• r