Market Data

Phase 1 — Get and Read Market Data

Before Python can build a candlestick, calculate an indicator, or test a trading idea, it needs market data.

In this phase, you will learn how to download market data, understand OHLCV columns, find market symbols, save data, check it, and clean it before analysis. 

market
→ FinanceDataReader
→ pandas DataFrame
→ OHLCV
→ check the data
→ clean the data
→ ready for analysis

Phase 1 Lessons

What You Should Understand After Phase 1

  • Market data must enter Python before analysis can begin.
  • FinanceDataReader can retrieve financial data for Python.
  • pandas stores and works with the returned data in a DataFrame.
  • OHLCV describes Open, High, Low, Close, and Volume.
  • A market listing helps you find symbols that can be requested.
  • CSV files let you save and reload data.
  • Market data should be checked before it is used for analysis.
  • Missing, duplicated, or invalid rows should be handled deliberately.

Next: Read Price with Candlesticks

You now know how to download, read, save, check, and clean market data. The next step is to use OHLC data to understand price itself.

In Phase 2, you will start with one candlestick, build a complete candlestick chart, measure candle bodies and wicks, turn visual patterns into explicit Python rules, and finally combine those rules into a simple pattern scanner.

Continue to Phase 2 — Candlesticks →

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