Datasets:
Update Yelpdata_663.py
Browse files- Yelpdata_663.py +29 -22
Yelpdata_663.py
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@@ -30,6 +30,7 @@ import os
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from typing import List
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import datasets
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import logging
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# TODO: Add BibTeX citation
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# Find for instance the citation on arxiv or on the dataset repo/website
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@@ -105,26 +106,32 @@ class YelpDataset(datasets.GeneratorBasedBuilder):
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citation=_CITATION,
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)
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from typing import List
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import datasets
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import logging
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import pandas as pd
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# TODO: Add BibTeX citation
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# Find for instance the citation on arxiv or on the dataset repo/website
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citation=_CITATION,
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)
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def _generate_examples(self, filepaths):
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logging.info("Generating examples from = %s", filepaths)
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# Load JSON files into pandas DataFrames
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business_df = pd.read_json(filepaths['business'], lines=True)
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review_df = pd.read_json(filepaths['review'], lines=True)
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# Merge DataFrames on 'business_id'
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merged_df = pd.merge(business_df, review_df, on='business_id')
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# Filter out entries where 'categories' does not contain 'Restaurants'
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filtered_df = merged_df[merged_df['categories'].str.contains("Restaurants", na=False)]
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# Convert to CSV (optional step if you need CSV output)
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# filtered_df.to_csv('filtered_dataset.csv', index=False)
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# Generate examples
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for index, row in filtered_df.iterrows():
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# Handle missing values for float fields
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for key, value in row.items():
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if pd.isnull(value):
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row[key] = None # or appropriate handling of nulls based on your requirements
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# Yield each row as an example
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yield index, row.to_dict()
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