These notebooks are my data science portfolio in Python programming language. These notebooks utilize data science libraries such as Pandas, NumPy, and scikit-learn. In addition, these notebooks also include the utilization of data visualization libraries such as seaborn, matplotlib, plotly, and many more.
For this project, I will be analyzing some 911 data from Kaggle. The data contains the following fields :
- lat : String variable, Latitude
- lng: String variable, Longitude
- desc: String variable, Description of the Emergency Call
- zip: String variable, Zipcode
- title: String variable, Title
- timeStamp: String variable, YYYY-MM-DD HH:MM:SS
- twp: String variable, Township
- addr: String variable, Address
- e: String variable, Dummy variable (always 1)
I also made several changes by created a new features in the dataframe :
- Reason
- Hour
- Month
- Day of Week
- Date
This data project will focus on exploratory data analysis of stock prices. This project is meant to practice my visualization and pandas skills, and it is not meant to be a robust financial analysis or be taken as financial advice.
I focused on the bank stocks and visualized how they progressed throughout the financial crisis all the way to early 2016.
To get the data, I used pandas datareader. I got stocks information for the following banks :
- Bank of America
- CitiGroup
- Goldman Sachs
- JPMorgan Chase
- Morgan Stanley
- Wells Fargo
