Last Minute Vacation

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Last Minute Vacation Taylor McGann Danny Christensen Russ Taylor

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Last Minute Vacation. Taylor McGann Danny Christensen Russ Taylor. Agenda. Introduction Data Collection Data Summarization Models Conclusions Future Research. Last minute vacation?...What?. How can we get a cheap ticket?. 1. What is the best day to purchas e tickets?. 2. - PowerPoint PPT Presentation

Transcript of Last Minute Vacation

Page 1: Last Minute Vacation

Last Minute Vacation

Taylor McGannDanny Christensen

Russ Taylor

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Agenda

Introduction

Data Collection

Data Summarization

Models

Conclusions

Future Research

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Last minute vacation?...What?

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How can we get a cheap ticket?

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1What is the best day to purchase tickets?

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2How far in advance should we purchase tickets?

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3Are we getting the best price?

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Ruby

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Selenium WebDriver

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Kayak

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Loads of CSV files

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"We don't want bots running about trying to book airline tickets. They tend to try to cram large suitcases in the overhead bin, and they prattle on about celebrities they

know while you are trying to watch the movie."

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How about that data?

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Name Type Description

Airline Text An airline. For example, AA equals American Airlines.

Arrive Text Arrival city as a three letter code

Arrive Date Date Arrival date.

Arrive Time Integer Flight arrival time in military hours.

Class Text Class of a flight. There are five different types of classes: Business, coach, mixed, premium, and first.

Depart Text Departure city as a three letter code.

Depart Date Date Departure date.

Depart Time Integer Flight departure time in military hours.

Departure Day Text Day of the week a flight departs.

Difference Integer Number of days between the download and departure data.

Download Date Date Download date or date a flight would have been purchased.

Download Day Text Day of the week flight data was downloaded.

Duration Integer Number of minutes in flight.

Equipment Text Type of plane.

Flight Integer Flight number.

Price Integer Total cost for a flight.

Record Integer Record number of each item in an individual csv. In the combined data set this number is meaningless.

Stops Integer Total number a stops or layovers for a flight.

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Name Type Description

Airline Text An airline. For example, AA equals American Airlines.

Arrive Text Arrival city as a three letter code

Arrive Time Integer Flight arrival time in military hours.

Class Text Class of a flight. There are five different types of classes: Business, coach, mixed, premium, and first.

Departure Day Text Day of the week a flight departs.

Difference Integer Number of days between the download and departure data.

Download Day Text Day of the week flight data was downloaded.

Duration Integer Number of minutes in flight.

Price Integer Total cost for a flight.

Stops Integer Total number a stops or layovers for a flight.

Predicting Price

Final Variables

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ANN

ANN

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ANN

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KNN

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KNN

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Linear Regression

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Linear Regression

*NOTE: Table does not include all variables

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1What is the best day to purchase tickets?

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Tuesday Sunday

Conclusions

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2How far in advance should we purchase tickets?

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Conclusions1 Day

60 Days

120 Days

180 Days

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3Are we getting the best price?

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Conclusions

Hard to determine.

Too many variables.

Out of scope.

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Future Research

Explore variables in isolation(E.g. destination, airline, etc.)

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Add a "Buy/Buy Not" variable to do categorical analysis.

Future Research

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Collect data over a longer period of time.

Isolate seasonal and cyclical trends.

Future Research

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Questions