In this project, the skills acquired from advanced data wrangling course are applied to gather and wrangle real-world data with two datasets. They are retrieved and extractd, then assessed programmatically and visually, accross elements of data quality and structure, and a cleaning strategy for the data was implemented. Then the updated data is stored into the directiry ./data as a data store, combined the data, and tried to answer a research question with these datasets.
In this reserach, the stock prices of major tech companies (such as Apple, Microsoft, Google, Amazon, and META) and oil prices over the period spanning from January 2001 to December 2005 are investigated. By examining historical data for both sectors, the aim is to uncover insights into how changes in oil prices impact the financial performance of big tech companies, and vice versa. The datasets would include the stock market data for:
- META
- AMazon
- Apple
- Microsoft
- Gather Data
- Asses Data
- Clean Data
- Store Data
- Answering Research Questions