"Payroll (millions)"': '    110.30', ' "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"': '
This notebook goes over how to load data from a PySpark DataFrame.
This notebook goes over how to load data from a PySpark DataFrame. ->: "Payroll (millions)"': '    110.30', ' "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"': '