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portfolio_2026.xlsx
| Ticker | Weight | PnL | σ | |
|---|---|---|---|---|
| 1 | AAPL | 8.4% | +2.31 | 0.18 |
| 2 | MSFT | 7.9% | +1.92 | 0.21 |
| 3 | NVDA | 11.2% | +4.07 | 0.34 |
| 4 | JPM | 5.1% | −0.84 | 0.15 |
| 5 | BRK.B | 6.7% | +0.62 | 0.12 |
| 6 | GOOGL | 7.2% | +1.15 | 0.19 |
Rebalance — Q2 2026
DECISION · READY
rebalance.pyPYTHON · 3.12
1# Load portfolio + run AI-assisted rebalance
2import pandas as pd
3from pyfi import Portfolio, Agent
4
5book = Portfolio.read_xlsx("portfolio_2026.xlsx")
6agent = Agent(model="claude-haiku-4.5")
7
8@agent.tool(risk_budget=0.18)
agent.run()
01Ingest holdings0.4s
02Compute covariance1.2s
03Reason → reweight•
04Emit trade ticketsqueued
THE PYFI WORKFLOW
*These banks have used one or more PyFi products to train their employees
What We Teach
Three pillars. Built on the logic you already use.
pillar_1.module
01
excel
fxC2
=IF(C2>0,"BUY","SELL")
≡ same logic
python
1
signal = "BUY" if pnl > 0 else "SELL"
Python for Finance
You already think in logical operations, that's all a spreadsheet is. Python is the same logic, written once and built to scale, far past what a single sheet can hold.
pillar_2.module
02
model.predict()
actual
forecast
Automation & Machine Learning
Turn the work you repeat every month into code that runs on command, then go beyond fixed rules. Train machine learning models on your own data to forecast, classify, and surface the patterns a spreadsheet never could.
pillar_3.module
03
one auditable step at a time
Summarize a report
low stakes · approved
Transform · feed a model
stakes rising · approved
An output you defend
high stakes · signed · you
LOW
HIGH
AI, on your terms
AI belongs in your work, but on your terms. Python is the infrastructure that lets you introduce it deliberately, one auditable step at a time. Instead of trusting a black box, you bring it in across the finance function as the stakes rise: from summarizing a report, to transforming data and feeding a model, to producing an output you can stand behind and defend.
AI
Andre Irving
CFO
★★★★★
Live Python Class: 5 Stars!
Just finished the PyFi course and I can't recommend it enough! Four days, two hours a day — and every minute was worth it. The live instructors were fantastic: helpful, engaging, and clearly passionate about the material. They made Python feel approachable even for someone just starting out. What I loved most was how the course connected coding concepts directly to real finance scenarios, so you could immediately see the value of what you were learning. If you're in finance and have been thinking about picking up Python, stop thinking and just sign up. PyFi is the real deal!
DT
Dave T.
Financial Analyst
★★★★★
PyFi Personal Finance Demo
The PyFi demo today was fantastic. It showed how a simple personal-finance example can quickly scale into powerful, real-world automation using Python and AI. Fast, clear, and genuinely exciting for anyone looking to level up their financial workflows.
NI
Naquan Ishman
Principal
★★★★★
Highly Recommend!
What an excellent course. The Python portion gets you quickly up to speed on Python data structures, common libraries, and functions. The ML portion gives two end to end examples of structuring, training, testing, and selecting ML models. The pace of the demo and level of detail given were great.
BM
Bart Miller
Data Analytics Lead
★★★★★
Outstanding introduction to how Python with OpenAI works
Great intro to how OpenAI is called from within a Python program to best the process that Excel data analysis can't handle and automates data cleaning and normalization. It was really fun to see how AI is a powerful integrated tool to help expand the power you can have to analyze financial data.
RG
Rafael Guzman
Operations Analyst
★★★★★
Py-fi Demo
Thorough PyFi demo covering Python logic within a personal finance example utilizing OpenAI to automate analyses. I definitely see the benefit of using AI with Python to automate analyses and will be applying what I learn to my work in the future.
PB
Paul of Boise
Senior Accountant
★★★★★
Very informative
Zach laid out an easily understood problem that is similar to what many in finance have faced, and showed how to solve it using a combination of VS Code on GitHub and OpenAI through an API. Well laid out for even this zero programming Excel guy.
JC
James Childress
Finance Manager
★★★★★
Finally, I have an answer to "Why Python?"
I've been hearing about Python as being something I might need in years of work with data prep and visualization. I wanted to learn more and try to orient myself, and then PyFi stepped in and gave me a real chance to see the possibilities in action and ask questions that helped me orient myself and my team towards next steps. Much appreciated, and Zach broke things down clearly and easily.
The Library
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