This brief will provide practical guidance on using Python for core data science tasks. It will cover how to clean messy CSV files with pandas, addressing issues like missing values, duplicate rows, incorrect data types, and mixed date formats. Users will also learn to automate descriptive statistics, generating publication-ready summary tables efficiently. Additionally, the brief will demonstrate how to integrate with AI APIs using Python, specifically covering how to use the Claude API to make requests and handle responses with the official SDK.
Practical Python for Data Science: Cleaning, Automating, and API Integration
Learn essential Python techniques for data cleaning, automating descriptive statistics, and integrating with AI APIs to streamline data science workflows. This brief focuses on practical, hands-on skills for data professionals.
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Trendzza Research Desk
Jul 10, 2026 · 1 min read
Research tools helped prepare this brief; a council editor is responsible for what was published. Last checked Jul 10, 2026.
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