Python and Data Primer
Learn Python fundamentals and the data workflow needed to start quantitative finance projects.
Why study Python and Data Primer?
Quantitative ideas become testable when you can turn them into small, repeatable calculations. Learn enough Python and data handling to inspect a dataset, spot a mistake and explain your result without depending on a spreadsheet workflow.
Who this is for
For first-time programmers and learners moving from spreadsheets to code. Basic arithmetic is enough to begin.
What you should be able to do
- Write Python functions and work with collections.
- Explore numerical and tabular data with NumPy and pandas.
- Use reproducible environments, files and financial data sources.
An example of the work this prepares you for
A reproducible notebook that reads a small dataset, checks missing values, calculates returns and produces a labelled chart.
Before you start
You can begin without prior quant-finance study. Use the resources below to refresh the basics as you work through the material.
A preview of the learning journey
The lessons build towards these kinds of reasoning and practical work.
Write small calculations
Break a financial question into functions you can inspect and reuse.
Work with tables
Recognise data types, missing observations and date indexes.
Make a run repeatable
Keep inputs, environment choices and outputs understandable.
Members work through the detailed lessons, derivations, worked examples and solutions inside the learning dashboard.
Explore lesson previews by topic
Open a topic preview to see its introduction, learning objectives and prerequisites. Previous and next links let you explore the lessons in study order. Full lessons are available in the member dashboard; selected samples are free to read in full.
Free resources to start learning
Use these alongside the programme or to prepare independently. Start with the introductory material, work through an example, then return to the research papers when the underlying ideas are familiar.
CS50’s Introduction to Programming with Python
Harvard · David Malan
Follow the free lectures and exercises for a first programming course.
How to Think Like a Computer Scientist
Open Book Project · Learning with Python 3
Use the short examples to practise control flow, functions and debugging.
Python for Data Analysis
Wes McKinney · third edition
Move on to NumPy and pandas after you can write basic functions.
Software Carpentry lessons
The Carpentries
Practise files, version control and a simple research workflow.
Links reviewed 14 October 2026. Free refers to the linked reading, notes or videos; printed books and certificates may cost extra.
Find more papers and learning materials in the SelfMadeQuant Directory.
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