Data Analysis on Apple and Macs
The skills the author demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.
Introduction
Apple Inc. (AAPL), founded in 1976, became the first U.S. corporation to surpass $1 trillion in market capitalization last year as its iPhone fueled spectacular growth in sales, profits and its share price. Since then, the company aggressively moves to transform itself from a seller mainly of tech hardware devices into one of the world’s leading providers of digital services. To do that, Apple must sharply boost the sales it gets from software and services. As a result, data shows the sale of Macintosh Computers now makes up a mere 16% of its total revenue.
Data
To extract Data, I used Python & Scrapy. Scrapy is a wonderful tool within Python, it is a perfect fit for Data Scientists who want to answer a question where the current data set does not currently exist. For my implementation of the library, I decided to look at Macintosh computers, their prices over time & how they related to the interest rates & the price of Apple’s stock price.
To get the correct information for my data set I looked for websites that contain large amounts of data about historical pricing of Macintosh machines, as Apple.com has no pricing outside of their current product lineup. I eventually landed with everymac.com, as it stores large amounts of data, matched my query & had a wide range of different machines from 1991 to present.
You can find more information on this project here.
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