“Take a flight to Seattle and before landing get $500 and a job offer”
The title is like those ads you see on the Internet that get your curiosity hooked. You may be wondering: is this a fraud? and I would say: no, it’s not. Then, what does the fine print say? What’s the catch? Well, it’s only a matter of perspective.
tl;dr: this is the introduction of a series of posts which try to answer simple questions about flights’ costs by analyzing data available online.
When I was returning from my first trip to Seattle, I already wanted to visit that city again. Now, I’m living in Austin and I’m already looking for an opportunity to visit my family and friends in Mexico City.
We all have different reasons to visit other cities and countries. The farther these places are from our current city, or the shorter amount of time available for the entire trip make traveling by air almost mandatory. On the other hand, the affordability of the flights causes us to ask ourselves a series of questions when we begin planning a trip: Which are the best dates to fly? How many days in advance should we buy our tickets? Which is the best deal we can get for a given destination? Which season should we avoid?
Many of us love to travel. Most of us want to save money when traveling. Now, let’s take advantage of this opportunity to learn something new! This post introduces a series where we will try to answer the questions listed before with evidence based on data. We are going to acquire data available online, specifically on google flights (why this source? because google knows best), and clean the obtained dataset to get it ready for analysis and visualization. Based on the obtained results, we should be able to answer our own questions and discover when to book a flight and how much we can save when choosing trip dates. At the same time, by following these steps we will learn and develop a few skills that are highly valued in a data-related job.
So, that’s it. This is only a kind of data-centered Howdy World! (maybe now the article’s title makes more sense to you as an attempt of making this read easier and better to find). This under development series features:
- Acquiring Data: The Scraper Strikes Back!
- Manipulating Data: The Art of ETL
- Analyzing & Visualizing Data: Spark and the Two FlatMaps
- Some Answers: ¡A volar joven!
Next in series: coming soon…
