mplfinance is a library that makes it simple to create beautiful charts of financial data:
• 22 example notebooks
• Plot user-defined data
• Includes built-in technical studies
• Animate data in Jupyter Notebook
• Plots OHLC bars, candlesticks, and line charts
Here's how:
Start by importing yfinance and mplfinance and downloading some data.
The most-used analytics software of the last 37 years:
Excel
But Excel on your resume is no longer enough to get a quant job.
Because Python is the new Excel.
But with 473,000,000 results for "python tutorial", most people struggle to start.
The 6 steps get started in 1 day:
In case you’re unsure if you should learn Python:
• 40% of all hedge fund jobs require it on job descriptions
• 100,000s of powerful pre-built packages
• Base salaries topping US$200,000
• Easy to learn for beginners
• Open source (FREE)
So… where do we start?
First, 3 dead-simple tips after 10 years of using Python:
• Study other people’s code (learn from the best)
• Find a real problem to solve (puzzles get boring)
• Learn how to ask questions (expect to ask A LOT of questions)
The only 12 Python visualization libraries you'll ever need:
Matplotlib: Visualization with Python
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible.
Dash is the original low-code framework for rapidly building data apps in Python. Dash is ideal for building and deploying data apps with customized user interfaces. It's particularly suited for anyone who works with data.
9 must-have Python time series libraries everyone working with data should know:
sktime
sktime is a library for time series analysis in Python. It provides a unified interface for multiple time series learning tasks. Currently, this includes time series classification, regression, clustering, annotation and forecasting.