Datasets:
Tasks:
Text2Text Generation
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
1K - 10K
Tags:
text-to-sql
License:
HusnaManakkot
commited on
Update spider.py
Browse files
spider.py
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from datasets import load_dataset, Dataset
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import pandas as pd
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# Step 1: Download your uploaded Spider dataset
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my_spider_dataset = load_dataset("HusnaManakkot/new-spider-HM", split='train')
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# Step 2: Convert the dataset to a Pandas DataFrame
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my_spider_df = pd.DataFrame(my_spider_dataset)
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# Step 3: Add a new row to the DataFrame
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new_example = {
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'db_id': 'employee_database', # Replace with the actual database ID
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'query': "SELECT AVG(salary) FROM employees WHERE join_date > '2015-01-01' AND department = 'Marketing';",
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'question': 'What is the average salary of employees who joined after 2015 and work in the Marketing department?',
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'query_toks': ['SELECT', 'AVG', '(', 'salary', ')', 'FROM', 'employees', 'WHERE', 'join_date', '>', "'2015-01-01'", 'AND', 'department', '=', "'Marketing'", ';'],
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'query_toks_no_value': ['SELECT', 'AVG', '(', 'salary', ')', 'FROM', 'employees', 'WHERE', 'join_date', '>', 'VALUE', 'AND', 'department', '=', 'VALUE', ';'],
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'question_toks': ['What', 'is', 'the', 'average', 'salary', 'of', 'employees', 'who', 'joined', 'after', '2015', 'and', 'work', 'in', 'the', 'Marketing', 'department', '?'],
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'sql': {
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'select': [(0, [(3, (0, 'salary'))])], # (agg_id, val_unit), agg_id for AVG is 0, val_unit is (column_id, column_name)
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'from': {'table_units': [('table_unit', 0)], 'conds': []}, # ('table_unit', table_id), assuming 'employees' is the first table
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'where': [(0, False, [(2, (0, 'join_date')), '>', (1, "'2015-01-01'")]), 'AND', (0, False, [(2, (0, 'department')), '=', (1, "'Marketing'")])],
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'groupBy': [],
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'having': [],
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'orderBy': [],
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'limit': None,
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'intersect': None,
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'union': None,
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'except': None
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}
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}
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my_spider_df = my_spider_df.append(new_example, ignore_index=True)
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# Step 4: Convert the modified DataFrame back to a Hugging Face dataset
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modified_spider_dataset = Dataset.from_pandas(my_spider_df)
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# Step 5: Push the modified dataset back to your Hugging Face account
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modified_spider_dataset.push_to_hub("HusnaManakkot/new-spider-HM")
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