12 Python Libraries for Free Market Data That Changed How I Work

I’ve been writing about tech for a decade now, and nothing gets me more excited than finding tools that make life easier — especially when they’re free. Back when I started dabbling in market data, I was stuck scraping websites or begging for pricey subscriptions. Then I found these Python libraries, and it was like someone handed me the keys to a financial candy store. Today, I’m sharing 12 of them that I’ve used in real projects — some for fun, some for profit.

Photo by Oleksandr Chumak on Unsplash

1. yfinance

Pulls stock data — historical, intraday, even fundamentals — from Yahoo Finance. Forex and crypto too.

It’s my lazy-day go-to when I just need data fast.

A couple of years back, I was curious if Apple’s stock dipped every time they launched a new iPhone. With yfinance, I grabbed the numbers in minutes:

import yfinance as yf

apple = yf.Ticker("AAPL")
data = apple.history(period="1mo")
print(data.tail())

                   Open        High         Low       Close    Volume  Dividends  Stock Splits
Date                                                                            
2025-03-14  185.23     187.45     184.12     186.78  52345600        0.0           0.0
2025-03-17  186.90     188.23     185.67     187.45  45678900        0.0           0.0
2025-03-18  187.56     189.01     186.34     188.67  48912300        0.0           0.0
2025-03-19  188.89     190.23     187.45     189.12  51234500        0.0           0.0
2025-03-20  189.34     191.56     188.01     190.45  47890100        0.0           0.0

I ran this during the last iPhone hype and spotted a tiny dip — nothing wild, but it scratched my itch.

2. pandas-datareader

Fetches data into pandas from Yahoo, FRED, and more. It split off from pandas, which I still find oddly satisfying.

Perfect when I’m chasing economic trends.

Once, I bet a friend Tesla’s stock tracked gas prices. I used this to pull both:

import yfinance as yf
import datetime

start = datetime.datetime(2022, 1, 1)
end = datetime.datetime(2022, 12, 31)
tesla =…