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# DataFrame Loader

This notebook goes over how to load data from a pandas dataframe

    import pandas as pd

    df = pd.read_csv('example_data/mlb_teams_2012.csv')

    df.head()

| Team | "Payroll (millions)" | "Wins"
--- | --- | --- | ---
0 | Nationals | 81.34 | 98
1 | Reds | 82.20 | 97
2 | Yankees | 197.96 | 95
3 | Giants | 117.62 | 94
4 | Braves | 83.31 | 94

    from langchain.document_loaders import DataFrameLoader

    loader = DataFrameLoader(df, page_content_column="Team")

    loader.load()

    [Document(page_content='Nationals', metadata={' "Payroll (millions)"': 81.34, ' "Wins"': 98}),
     Document(page_content='Reds', metadata={' "Payroll (millions)"': 82.2, ' "Wins"': 97}),
     Document(page_content='Yankees', metadata={' "Payroll (millions)"': 197.96, ' "Wins"': 95}),
     Document(page_content='Giants', metadata={' "Payroll (millions)"': 117.62, ' "Wins"': 94}),
     Document(page_content='Braves', metadata={' "Payroll (millions)"': 83.31, ' "Wins"': 94}),
     Document(page_content='Athletics', metadata={' "Payroll (millions)"': 55.37, ' "Wins"': 94}),
     Document(page_content='Rangers', metadata={' "Payroll (millions)"': 120.51, ' "Wins"': 93}),
     Document(page_content='Orioles', metadata={' "Payroll (millions)"': 81.43, ' "Wins"': 93}),
     Document(page_content='Rays', metadata={' "Payroll (millions)"': 64.17, ' "Wins"': 90}),
     Document(page_content='Angels', metadata={' "Payroll (millions)"': 154.49, ' "Wins"': 89}),
     Document(page_content='Tigers', metadata={' "Payroll (millions)"': 132.3, ' "Wins"': 88}),
     Document(page_content='Cardinals', metadata={' "Payroll (millions)"': 110.3, ' "Wins"': 88}),
     Document(page_content='Dodgers', metadata={' "Payroll (millions)"': 95.14, ' "Wins"': 86}),
     Document(page_content='White Sox', metadata={' "Payroll (millions)"': 96.92, ' "Wins"': 85}),
     Document(page_content='Brewers', metadata={' "Payroll (millions)"': 97.65, ' "Wins"': 83}),
     Document(page_content='Phillies', metadata={' "Payroll (millions)"': 174.54, ' "Wins"': 81}),
     Document(page_content='Diamondbacks', metadata={' "Payroll (millions)"': 74.28, ' "Wins"': 81}),
     Document(page_content='Pirates', metadata={' "Payroll (millions)"': 63.43, ' "Wins"': 79}),
     Document(page_content='Padres', metadata={' "Payroll (millions)"': 55.24, ' "Wins"': 76}),
     Document(page_content='Mariners', metadata={' "Payroll (millions)"': 81.97, ' "Wins"': 75}),
     Document(page_content='Mets', metadata={' "Payroll (millions)"': 93.35, ' "Wins"': 74}),
     Document(page_content='Blue Jays', metadata={' "Payroll (millions)"': 75.48, ' "Wins"': 73}),
     Document(page_content='Royals', metadata={' "Payroll (millions)"': 60.91, ' "Wins"': 72}),
     Document(page_content='Marlins', metadata={' "Payroll (millions)"': 118.07, ' "Wins"': 69}),
     Document(page_content='Red Sox', metadata={' "Payroll (millions)"': 173.18, ' "Wins"': 69}),
     Document(page_content='Indians', metadata={' "Payroll (millions)"': 78.43, ' "Wins"': 68}),
     Document(page_content='Twins', metadata={' "Payroll (millions)"': 94.08, ' "Wins"': 66}),
     Document(page_content='Rockies', metadata={' "Payroll (millions)"': 78.06, ' "Wins"': 64}),
     Document(page_content='Cubs', metadata={' "Payroll (millions)"': 88.19, ' "Wins"': 61}),
     Document(page_content='Astros', metadata={' "Payroll (millions)"': 60.65, ' "Wins"': 55})]