Access Finnhub API for real-time stock quotes, company news, market data, financial statements, and trading signals

Access Finnhub API for real-time stock quotes, company news, market data, financial statements, and trading signals. Use when you need current stock prices, company news, earnings data, or market analysis.

Kibana Data Views

Manage Kibana Data Views (formerly index patterns) via REST API. Use when: (1) Creating, listing, updating, or deleting data views, (2) Checking data view ex...

Powerdrill Data Analysis

This skill should be used when the user wants to analyze, explore, visualize, or query data using Powerdrill. Covers listing, creating, and deleting datasets; uploading local files as data sources; creating analysis sessions; running natural-language data analysis queries; and retrieving charts, tables, and insights. Triggers on requests like "analyze my data", "query my dataset", "upload this file for analysis", "list my datasets", "create a dataset", "visualize sales trends", "continue my prev

Kalshi Fed Data Reaction Trader

Trades Fed rate markets on Kalshi based on macro data releases (CPI, jobs). Scans CPI bin markets for implied CPI, adjusts rate cut probabilities using data...

What is Data Science @ O'reilly

_Data scientists combine entrepreneurship with patience, the willingness to build data products incrementally, the ability to explore, and the ability to iterate over a solution. They are inherently interdisciplinary. They can tackle all aspects of a problem, from initial data collection and data conditioning to drawing conclusions. They can think outside the box to come up with new ways to view the problem, or to work with very broadly defined problems: “here’s a lot of data, what can you make from it?”_

Software Development Resources for Data Scientists

_Data scientists concentrate on making sense of data through exploratory analysis, statistics, and models. Software developers apply a separate set of knowledge with different tools. Although their focus may seem unrelated, data science teams can benefit from adopting software development best practices. Version control, automated testing, and other dev skills help create reproducible, production-ready code and tools._