Today we explore how to import stock data from yahoo finance with pandas datareader using python. We also explore how to visualise and subsection stock data in pandas dataframe form. Using pandas describe method we are able to quickly derive useful information from specific stocks, and with the .plot method we can graph stock data with both matplotlib and/or plotly extremely easily.
As a high-level programming language, Python is a great tool for financial data analysis, with quick implementation and well documented API data sources, statistical modules and other frameworks related to the financial industry. We will be using Jupyter Lab as an interactive web browser editor for this series due to ease of use, and presenting code in a live notebook is ideal for this tutorial series.
This is the first video of many on the topic of Python for Finance. The series will include general techniques used for financial analysis and act as a introduction for more in depth tutorials that we may explore later (such as time series modelling, building financial dashboards, machine learning ect.).
★ ★ QuantPy GitHub ★ ★
Collection of resources used on QuantPy YouTube channel. [ Ссылка ]
★ ★ Discord Community ★ ★
Join a small niche community of like-minded quants on discord. [ Ссылка ]
★ ★ Support our Patreon Community ★ ★
Get access to Jupyter Notebooks that can run in the browser without downloading python.
[ Ссылка ]
★ ★ ThetaData API ★ ★
ThetaData's API provides both realtime and historical options data for end-of-day, and intraday trades and quotes. Use coupon 'QPY1' to receive 20% off on your first month.
[ Ссылка ]
★ ★ Online Quant Tutorials ★ ★
WEBSITE: [ Ссылка ]
★ ★ Contact Us ★ ★
EMAIL: pythonforquants@gmail.com
Disclaimer: All ideas, opinions, recommendations and/or forecasts, expressed or implied in this content, are for informational and educational purposes only and should not be construed as financial product advice or an inducement or instruction to invest, trade, and/or speculate in the markets. Any action or refraining from action; investments, trades, and/or speculations made in light of the ideas, opinions, and/or forecasts, expressed or implied in this content, are committed at your own risk an consequence, financial or otherwise. As an affiliate of ThetaData, QuantPy Pty Ltd is compensated for any purchases made through the link provided in this description.
