Automated Data Cleansing with AiPy
Data cleansing is one of the most time-consuming aspects of data analysis, and traditional methods require manually writing Python code to deal with missing values, format conversions, etc. AiPy solves this pain point with the following steps:
- natural language description task: Use something like
ai("清理sales.csv中的缺失值并用中位数填充")instructions, the system automatically generates the code - Automated library management: If you need a library such as pandas, you will be prompted to install it.
- Intelligent error correction: Detect and fix code syntax errors via AST
- visualization and verification: Additional
ai("显示清理后的数据分布")Verification results
Advanced Tip: Using Python Patterns in the%histView history of generated code, save as script for reuse. For complex cleaning processes, multiple ai() commands can be executed in stages.
This answer comes from the articleAiPy: automating the task of running Python code for data analysisThe
May not be reproduced without permission:AI productivity tools " How to solve the problem of tedious manual coding during data cleansing?
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