This project aims to analyze and compare the monthly stock returns of two major e-commerce companies - Amazon and eBay. We conduct a visual examination of the return data by creating a series of plots: line graphs, bar graphs, and scatter plots, using Python's data visualization libraries Matplotlib and Seaborn.
Data
The data used in this project are the monthly return percentages of Amazon and eBay for a one-year period.
Dependencies
The project relies on the following Python libraries:
Pandas: For creating and manipulating dataframes. Matplotlib: For creating line plots and bar graphs. Seaborn: For creating scatter plots and regression lines. Numpy: For numerical operations.
The project generates the following visualizations:
Line plots showing the trend of monthly returns for Amazon and eBay. A bar graph comparing the monthly returns of Amazon and eBay. A scatter plot with a regression line, which indicates the relationship between Amazon's and eBay's returns.
License
This project is licensed under the terms of the MIT license.
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