Unified interface to handle heterogeneous data
AiPy's built-in multi-format support capability simplifies mixed data processing:
- automatic recognition: Based on the file suffix (
.csv/.xlsx/.parquet) Selecting the optimal reading method - type conversion: By
ai("将JSON订单数据合并到SQLite数据库")Automatic handling of structural conversions - Memory Optimization: Automatic chunking of large data sets to avoid memory overflow
Typical application scenarios:
- Also analyze the server logs (
.txt), sales data (.xlsx) and the API return (.json) - utilization
ai("将所有数据按时间字段合并")Creating a unified view - Generate analytical reports across data sources
Exception handling: can be used when formatting problems are encountered--verboseparameter to see the detailed parsing process.
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 optimize analytical workflows for multi-format data sources?
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