Learn Python for finance from scratch
Start coding
- Where to run your Python code: Google Colab
- Ask for the input and print the output:
input()
andprint()
- Working with numbers, straings and dates
- Data structures, formats and places to save and read data.
- Functions and code structure.
Moving data around
- Data serialisation (JSON, CSV, XML).
- Reading and scraping data from web:
requests
andBS4
- Querying and building APIs:
requests
andFastAPI
Tables:
- Tables and dataframes using Excel and
pandas
. - SQL with simple abstractions (
SQLModel
) and puresqlite
.
Visuals:
streamlit
for dashboards.- Visualisations:
matplotlib
and whatever other library you choose.
Extra topics with code:
- Will there be multiple choice?
beaupy
library - Fast track to machine learning: scikit-learn lectures and Eric's examples
- Command line application with
sys.args
,docopt
orclick
- How to start a Telegram bot:
dotenv
for secrets.
Bank app design:
- Bank client onboarding: prototype vs real app.
- Many clients and a payment system.
- Bank reporting and capital requirements.
Financial and economic data (and what to do with it):
- Markets data. Portfolios, risk and algotrading.
- Corporate reports. Default scoring.
- Macroeconomic data:
- FRED
- EconDB
- IMF WEO forecasts
- Market intelligence: OpenBB terminal.
Demystifing decentrilised finance:
- Let's build our own blockchain
- Not so smart contracts
- Cryptocurrencies trading
Research tools:
- Bibliography with
manubot
pandoc
andquarto
document management- Extract video subtitles with
youtube-dl
- AI taking over: ChatGPT, you.com and a companion for paper reading
- Notetaking and Zettelkasten
Should everyone in economics and finance code (well)?
- QuantEcon
- "... for economists" guides
Missing:
- working with text and sentiment