Data practitioners often use both SQL and Python, including query and wrangle data and build models and analyses. However, when using these tools, they must often switch between different interfaces (e.g., a Jupyter notebook and SQL workbench) and between tables and dataframes. To make analytical work more seamless, Hex has introduced DataframeSQL, which enables users to apply SQL operations on Pandas dataframes and to easily load the results of SQL queries in a dataframe.