A step-by-step tutorial on converting CSV files to PostgreSQL database tables using Python's Pandas and SQLAlchemy libraries. The guide covers the entire process from data reading and transformation t
o database insertion, with emphasis on error handling and data verification.
Reasons to Read -- Learn:
how to implement a complete ETL pipeline for transferring CSV data to PostgreSQL databases using industry-standard Python libraries, with practical code examples for each step
essential data transformation techniques for ensuring database compatibility, including proper date formatting and data type conversions using Pandas
robust error handling strategies for database operations, including how to handle table conflicts and data insertion issues using SQLAlchemy's exception handling
4 min readauthor: Durga Gadiraju
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