Xorbits Pandas DataFrame
此笔记本介绍了如何从xorbits.pandas DataFrame 加载数据。
%pip install --upgrade --quiet xorbits
import xorbits.pandas as pd
df = pd.read_csv("example_data/mlb_teams_2012.csv")
df.head()
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<div>
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>Team</th>
<th>"Payroll (millions)"</th>
<th>"Wins"</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>Nationals</td>
<td>81.34</td>
<td>98</td>
</tr>
<tr>
<th>1</th>
<td>Reds</td>
<td>82.20</td>
<td>97</td>
</tr>
<tr>
<th>2</th>
<td>Yankees</td>
<td>197.96</td>
<td>95</td>
</tr>
<tr>
<th>3</th>
<td>Giants</td>
<td>117.62</td>
<td>94</td>
</tr>
<tr>
<th>4</th>
<td>Braves</td>
<td>83.31</td>
<td>94</td>
</tr>
</tbody>
</table>
</div>
from langchain_community.document_loaders import XorbitsLoader
API 参考：XorbitsLoader
loader = XorbitsLoader(df, page_content_column="Team")
loader.load()
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[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})]
# Use lazy load for larger table, which won't read the full table into memory
for i in loader.lazy_load():
print(i)
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page_content='Nationals' metadata={' "Payroll (millions)"': 81.34, ' "Wins"': 98}
page_content='Reds' metadata={' "Payroll (millions)"': 82.2, ' "Wins"': 97}
page_content='Yankees' metadata={' "Payroll (millions)"': 197.96, ' "Wins"': 95}
page_content='Giants' metadata={' "Payroll (millions)"': 117.62, ' "Wins"': 94}
page_content='Braves' metadata={' "Payroll (millions)"': 83.31, ' "Wins"': 94}
page_content='Athletics' metadata={' "Payroll (millions)"': 55.37, ' "Wins"': 94}
page_content='Rangers' metadata={' "Payroll (millions)"': 120.51, ' "Wins"': 93}
page_content='Orioles' metadata={' "Payroll (millions)"': 81.43, ' "Wins"': 93}
page_content='Rays' metadata={' "Payroll (millions)"': 64.17, ' "Wins"': 90}
page_content='Angels' metadata={' "Payroll (millions)"': 154.49, ' "Wins"': 89}
page_content='Tigers' metadata={' "Payroll (millions)"': 132.3, ' "Wins"': 88}
page_content='Cardinals' metadata={' "Payroll (millions)"': 110.3, ' "Wins"': 88}
page_content='Dodgers' metadata={' "Payroll (millions)"': 95.14, ' "Wins"': 86}
page_content='White Sox' metadata={' "Payroll (millions)"': 96.92, ' "Wins"': 85}
page_content='Brewers' metadata={' "Payroll (millions)"': 97.65, ' "Wins"': 83}
page_content='Phillies' metadata={' "Payroll (millions)"': 174.54, ' "Wins"': 81}
page_content='Diamondbacks' metadata={' "Payroll (millions)"': 74.28, ' "Wins"': 81}
page_content='Pirates' metadata={' "Payroll (millions)"': 63.43, ' "Wins"': 79}
page_content='Padres' metadata={' "Payroll (millions)"': 55.24, ' "Wins"': 76}
page_content='Mariners' metadata={' "Payroll (millions)"': 81.97, ' "Wins"': 75}
page_content='Mets' metadata={' "Payroll (millions)"': 93.35, ' "Wins"': 74}
page_content='Blue Jays' metadata={' "Payroll (millions)"': 75.48, ' "Wins"': 73}
page_content='Royals' metadata={' "Payroll (millions)"': 60.91, ' "Wins"': 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}