Downloaded and Analyzed Stock Data with yfinance

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📅 2024-01-15 — Session: Downloaded and Analyzed Stock Data with yfinance

🕒 20:50–21:10
🏷️ Labels: Yfinance, Python, Stock Data, Data Analysis, Pandas
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The goal of this session was to download and analyze stock data using Python’s yfinance library, focusing on both current and historical price comparisons.

Key Activities

  • Conversation Reset: Acknowledged a reset in conversation to ensure clarity and continuity in the session.
  • Downloading Stock Data: Implemented a Python script using yfinance to download the last 60 days of stock data for specified tickers, incorporating error handling and data concatenation.
  • DataFrame Concatenation: Developed a script snippet for combining downloaded stock data into a single DataFrame, managing missing data effectively.
  • Fetching Current and Historical Prices: Utilized yfinance to retrieve current stock prices and compare them with historical data from two months prior, using example code snippets.
  • Ranking Prices by Ticker: Applied pandas groupby and rank functions to rank closing prices within each ticker group in the DataFrame.

Achievements

  • Successfully downloaded and processed stock data using yfinance.
  • Developed robust scripts for data handling and analysis, including error management and price ranking.

Pending Tasks

  • Further analysis of ranked data to derive actionable insights or trends.
  • Integration of additional financial metrics for comprehensive market analysis.

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