Sorry to dig this thread up, but I had to take a look at this recently. I think the most efficient way is to use pydal to make the sql query and then have pandas do it. As an example say you want a dataframe which has the user's id and their first_name
import pandas as pd conn = db._adapter.connection sqlquery = pd.read_sql_query(db(db.auth_user.id > 0)._select(db.auth_user.id , db.auth_user.first_name), conn) df = pd.DataFrame(sqlquery, columns=["id", "first_name"]) This uses the connection to the database already done by pydal, it uses sql produced by pydal, however pydal does not process the result as it goes directly to pandas. -- Resources: - http://web2py.com - http://web2py.com/book (Documentation) - http://github.com/web2py/web2py (Source code) - https://code.google.com/p/web2py/issues/list (Report Issues) --- You received this message because you are subscribed to the Google Groups "web2py-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to web2py+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/web2py/e99631fd-a5bd-41f5-904b-57a0b2b1d67a%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
