I want to pull a table from Teradata as a Python data-frame. I know how to accomplish this step. Next I want to run algorithms on the data to transform it however I want. Once I am done with manipulating the data in Python, I want the resulting data-frame to be saved as a new table in Teradata so that I can perform joins with other tables in the database. My question is how do I save a python data-frame back into a database, I would like to do this inside of python using a script.
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One option is to use fastterdata, specifically the load_table function:
load_table(abs_path, df, table_name, env, db, connector = "teradata", clear_table=True)
Loads a pandas dataframe from memory into teradata via the optimized fastload functionality.
Note that you need to install requirements listed here.
Ghasem Naddaf
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although I never performed it by my self, but in theory each of following looks promising:
- SQL Alchemy for Teradata (https://downloads.teradata.com/tools/articles/teradata-sqlalchemy-introduction)
- pandas.to_sql (http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_sql.html#pandas.DataFrame.to_sql)
- above fasterdata (please note that fast load don't exist for MacOS)
- write to csv and Teradata Parallel Transporter the easy way with tdload
hhoeck
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