Mini Project Slides Update

[KevinT-dson]

Will be detailed more ig

[malenamalka]

This is a great starting point. I would recommend thinking clearly about how GDP is included in this conversation and from where you would get this data. If you are looking to compare various regions in the United States, maybe other economic indicators would fit better in your research such as poverty/income levels within the area and the families.
Also you do not acknowledge any stakes or ethical implications, so make sure to address that next time!

[KevinT-dson]

I updated the first idea and also uploaded the draft for the 2nd idea. Big thanks!

[ernbilen]

About the big project progress:

• Fantastic data collection. Topic is amazing. Google flights API etc gives you general trends but having access to raw data is very nice. It is also eye catching because your strategy is starting to scrape today and wait until you build your own data set. Employers care about building pipelines which you already do, but one expansion to consider is to build a dashboard that uses to pulled data for consumers to interact with data themselves.
• I'm not a fan of the correlation maps. You could consider making maps, literally showing the routes on the map. Then for general summaries I think bar charts work better but feel free to come up with something crazy creative. (Check out r/dataisbeautiful for inspiration)
• I love the aircraft usage analysis section. Try to bring in some aircraft stats in there too which would be even cooler.
• Ok I see your dashboard now. I love it. Suggestion: instead of pie chart, try a, not sure what it's called, but a viz technique where you would literally show the counts of aircraft and then if say American Airlines has 10% of all aircraft, you'd highlight that 10% in the renderation of all aircraft. Let me know if you need to chat more about this.
• I love the temporal analysis section and price change. Also show the standard deviation of price ticket change by airline.
• I like the initial machine learning stuff you did. I think you need to think about your end goal and can come up with something super tangible here. Eg, either trying to predict what a price would be tomorrow. Because maybe it may be better to wait a day or two? Or suggesting people when to buy ticket? Earliest the best? But is there a sweet spot? Are last minute deals an urban legend?
• Nice consequences/implications. But think more about ethical implications.

[ernbilen]

Final presentation comments:
-The amount of data scraped is so cool.
-Average price changed by $200 is such a big highlight. Maybe mention this in the 'why you should care about our research' discussion at the very beginning.
-Very cool dashboard. Try adding some catch images in there somewhere in a smooth way. Probably like blueprint style different planes from birdeye view or something similar.
-Here is another thing you can add to your dashboard: average size or weight of plane by origin airport or origin destination combos. This can be a single bar chart or map.
-Boeing, airbus competition discussion is interesting to see. Maybe do one chart just for that.
-Exchange rate on the dashboard is really cool.
-Great idea to compare different model performances.
-What is the big takeaway? In terms of what the consumers are able to do, they usually come in two types: those who need to go to a set destination, and those who are shopping for cheap flights to a destination point and they may be flexible about destination. For first, when to buy is the only thing you can choose, for second you choose both destination and when to buy.