72}    page_content='Marlins' metadata={' "Payroll (millions)"': 118.07, ' "Wins"': 69}    page_content='Red Sox' metadata={' "Payroll (millions)"': 173.18, ' "Wins"': 69}    page_content='Indians' metadata={' "Payroll (millions)"': 78.43, ' "Wins"': 68}    page_content='Twins' metadata={' "Payroll (millions)"': 94.08, ' "Wins"': 66}    page_content='Rockies' metadata={' "Payroll (millions)"': 78.06, ' "Wins"': 64}    page_content='Cubs' metadata={' "Payroll (millions)"': 88.19, ' "Wins"': 61}    page_content='Astros' metadata={' "Payroll (millions)"': 60.65, ' "Wins"': 55}PreviousAmazon TextractNextPsychicCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
This notebook goes over how to load data from a polars DataFrame.
This notebook goes over how to load data from a polars DataFrame. ->: 72}    page_content='Marlins' metadata={' "Payroll (millions)"': 118.07, ' "Wins"': 69}    page_content='Red Sox' metadata={' "Payroll (millions)"': 173.18, ' "Wins"': 69}    page_content='Indians' metadata={' "Payroll (millions)"': 78.43, ' "Wins"': 68}    page_content='Twins' metadata={' "Payroll (millions)"': 94.08, ' "Wins"': 66}    page_content='Rockies' metadata={' "Payroll (millions)"': 78.06, ' "Wins"': 64}    page_content='Cubs' metadata={' "Payroll (millions)"': 88.19, ' "Wins"': 61}    page_content='Astros' metadata={' "Payroll (millions)"': 60.65, ' "Wins"': 55}PreviousAmazon TextractNextPsychicCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.