Up, Up & Away!

Photo by locationindie

Reason for project

Today, many people enjoy the life of a traveler. Travling presents an opportunity to enjoy life like you never will again. The ability to enjoy things without the idea of consequence is one that many aspire for as can’t escape their boring day. The world is still big even though today even the advancements of social media bring our most wonderous ideas of adventure at are finger tips. Still, nothing escapes the thrill of embarking on a new journey that you will talk about up until your next destination. Many of my constiuants, travel almost as a job and their knowledge in destination ideas through a survey that was conduscted between us all can provide unmeasured insights into your next travel plans. The ability to scale the technology in this project is endless as the tech feeds through an open source network or can be found on a simple .docx.

The Survey

The survey was taken down using a python speech recognition api that we fed into a word document to place verbal answers from the survey.The demographics of the survey consisted of people in the age range of 18-30 and included participants of over 25 different countries. The survey consisted of 4 questions:

  1. What the particiapnts enjoyed most about traveling
  2. What is your xext destination
  3. What was the most enjoyed activity
  4. What was the most memorable trip they took.

Data Analysis

Once the snap survey was complete, I generated a data analysis in R using NLP to understand the survey more clearly. NLP or Natural Language Processing is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. One of the main ways to access unstructured data is using techniques in NLP as the ability to understand words, word combinations, and sequences of phrases can provide insights that would take hours to find. For example, you can understand every Jane Austin book using the Jane Austin dataset available free to everyone and using NLP techniques you can find insights into each and every book, without flipping through one page. Book reports can now be done in minutes rather than hours and days. I also used advanced statitical thechniques in Naive Bayes Thereom and LDA. These two stats principles are the industry preferred ways to machine learn unstructed data.

Shiny App

To showase all of the findings visually I created a shiny app. A Shiny App is an open source R package that provides an elegant and powerful web framework for building web applications using R. Shiny helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge. A number of uses and other ideas are found on the R studio website.

App in Action

Here is to the app in action via link posted on my linkedin, which i recorded on video.


  1. Many of the survey participants showed a wide range of destinations, but the majority fancied places outside of their home contintent let along country.
  2. The app shows their is a desire to enjoy the places traveled to by foot the most, which plays into the demogrpahics of the survey.
  3. Traveling doesn’t come without disadvantageous as many survey participants cited that stealing and theft are a concern to note of.


Personally, I really enjoy traveling and i can’t wait to do so again! I believe this app can provide me an opportunity to take some much wnated advice as I look to embark on my next journey abroad. If you enjoy traveling, data science, or statistics then please find out more of my works across this website!

Andrew D'Armond
Andrew D'Armond

Leveraging data science to achieve results