Downloaded and Analyzed Stock Data with yfinance

• Day: 2024-01-15
• Time: 20:50 to 21:10
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Yfinance, Python, Stock Data, Data Analysis, Pandas

Description

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.

Evidence

• source_file=2024-01-15.sessions.jsonl, line_number=2, event_count=0, session_id=e1754afb2cd9a6696da47e9d383dcdef6174c5a2df6435bdb326e3f438cd15c4
• event_ids: []