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by wswope
1327 days ago
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I find Pandas vs. SQL to be complimentary, rather than an either-or type situation. For anything in the tens of GB range or smaller, it’s easy enough to move between the two with read_sql_query and to_sql. The general strategy is to build the core of any dataset as a SQL query that handles joins and performance-sensitive parts of the query, then polish/plot/yeet into weird shapes with Pandas since it offers much greater expressivity. |
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