| import csv |
| import json |
| import os |
| from datasets import GeneratorBasedBuilder, Features, Value, Sequence, SplitGenerator, BuilderConfig, DatasetInfo, Split, Image |
| import logging |
| import pandas as pd |
| from typing import Dict |
|
|
| CITATION = "" |
| _DESCRIPTION = "" |
| _HOMEPAGE = "https://huggingface.co/datasets/SarcasmNet/self-annotated_reddit_climate_comment" |
| _LICENSE = "MIT" |
|
|
| _URL = "https://github.com/catherine-ywang/Reddit-Climate-Environment-Sarcasm-Self-Annotated-Data/raw/main/self_annotated_comments.csv" |
|
|
| class NewDataset(GeneratorBasedBuilder): |
| def _info(self): |
| return DatasetInfo( |
| description=_DESCRIPTION, |
| features=Features({ |
| "id": Value("string"), |
| "post_title": Value("string"), |
| "post_author": Value("string"), |
| "post_body": Value("string"), |
| "post_url": Value("string"), |
| "post_pic": Image(), |
| "subreddit": Value("string"), |
| "post_timestamp": Value("string"), |
| "post_upvotes": Value("int32"), |
| "post_permalink": Value("string"), |
| "comments": Sequence({ |
| "CommentID": Value("string"), |
| "CommentAuthor": Value("string"), |
| "CommentBody": Value("string"), |
| "CommentTimestamp": Value("string"), |
| "CommentUpvotes": Value("int32"), |
| "CommentPermalink": Value("string"), |
| "Label": Value("int32") |
| }) |
| }), |
| homepage=_HOMEPAGE, |
| ) |
| def _split_generators(self, dl_manager): |
| return [SplitGenerator(name=Split.TRAIN, gen_kwargs={"filepath": dl_manager.download(_URL)})] |
| |
| def _generate_examples(self, filepath): |
| df = pd.read_csv(filepath) |
| for column in df.columns: |
| df[column] = df[column].replace({pd.NA: None}) |
| |
| grouped_df = df.groupby('PostID') |
|
|
| for post_id, group in grouped_df: |
| post_data = group.iloc[0] |
|
|
| post_title = post_data['PostTitle'] |
| post_author = post_data['PostAuthor'] |
| post_body = post_data['PostBody'] |
| post_url = post_data['PostUrl'] |
| post_pic = post_data['PostPic'] |
| subreddit = post_data['Subreddit'] |
| post_timestamp = post_data['PostTimestamp'] |
| post_upvotes = post_data['PostUpvotes'] |
| post_permalink = post_data['PostPermalink'] |
|
|
| comments = [] |
|
|
| |
| for comment_id in group['CommentID'].unique(): |
| comment_data = group[group['CommentID'] == comment_id].iloc[0] |
|
|
| comment_author = comment_data['CommentAuthor'] |
| comment_body = comment_data['CommentBody'] |
| comment_timestamp = comment_data['CommentTimestamp'] |
| comment_upvotes = comment_data['CommentUpvotes'] |
| comment_permalink = comment_data['CommentPermalink'] |
| comment_label = comment_data['Label'] |
|
|
| |
| comment = { |
| "CommentID": comment_id, |
| "CommentAuthor": comment_author, |
| "CommentBody": comment_body, |
| "CommentTimestamp": comment_timestamp, |
| "CommentUpvotes": comment_upvotes, |
| "CommentPermalink": comment_permalink, |
| "Label": comment_label |
| } |
| comments.append(comment) |
| |
| example = { |
| "id": post_id, |
| "post_title": post_title, |
| "post_author": post_author, |
| "post_body": post_body, |
| "post_url": post_url, |
| "post_pic": post_pic, |
| "subreddit": subreddit, |
| "post_timestamp": post_timestamp, |
| "post_upvotes": post_upvotes, |
| "post_permalink": post_permalink, |
| "comments": comments |
| } |
|
|
| yield post_id, example |
|
|
| |
| |
| |
