Python for Traders

Enough Python and pandas to hold price data, compute returns and indicators, generate a first signal and plot an equity curve — taught through trading examples.

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Start lesson 1

What you will be able to do

Set up a working Python environment with a package manager and a notebook or editor.
Write variables, lists and functions using trading examples.
Hold price data in a pandas DataFrame and select, resample and transform it.
Compute returns, moving averages and a simple signal, then plot the equity curve it produces.

Lessons

1 (not completed)
Setting up your environment
Install Python, create a project with its own packages, choose between Jupyter and VS Code, and confirm everything works with a short check script.
Beginner15 minDraft
2 (not completed)
Python basics through trading examples
Variables, numbers, text, lists, loops, conditions and functions, learned by building a position-size calculator and running it over a list of trade setups.
Beginner18 minDraft
3 (not completed)
pandas: price data as a table
Generate a synthetic year of daily OHLCV bars, store them in a pandas DataFrame indexed by date, then select columns, rows and conditions, and resample daily bars into weekly ones.
Beginner18 minDraft
4 (not completed)
Returns, moving averages, and a first signal in pandas
Compute simple and log returns, measure volatility, build moving averages with rolling windows, and turn them into a signal that only acts on information available at the time.
Beginner18 minDraft
5 (not completed)
Mini project: plot an equity curve for a simple rule
Put the module together in one script that turns a moving-average rule into an equity curve, compares it with buy and hold, measures drawdown, saves a chart, and then checks how much the result depends on luck.
Beginner20 minDraft