Datasets:

numbers1234567
/

reddit-popular

Tasks:

Feature Extraction

Text Generation

Languages:

English

Size:

10K<n<100K

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train

The dataset viewer is not available for this split.

Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.

Error code:   FeaturesError
Exception:    ParserError
Message:      Error tokenizing data. C error: Expected 7 fields in line 6, saw 22

Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 233, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2998, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1918, in _head
                  return _examples_to_batch(list(self.take(n)))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2093, in __iter__
                  for key, example in ex_iterable:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1576, in __iter__
                  for key_example in islice(self.ex_iterable, self.n - ex_iterable_num_taken):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 279, in __iter__
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/csv/csv.py", line 190, in _generate_tables
                  for batch_idx, df in enumerate(csv_file_reader):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
                  return self.get_chunk()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
                  return self.read(nrows=size)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1923, in read
                  ) = self._engine.read(  # type: ignore[attr-defined]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
                  chunks = self._reader.read_low_memory(nrows)
                File "parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
                File "parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
                File "parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
                File "parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
                File "parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
              pandas.errors.ParserError: Error tokenizing data. C error: Expected 7 fields in line 6, saw 22

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Reddit Popular Dataset

Dataset of 10000 posts which appeared on /r/popular on Reddit.

Dataset Details

The Reddit API limits how many posts one can retrieve from a specific subreddit to 1000. This dataset contains data for almost all posts which appeared on /r/popular from Saturday, July 27, 2024 9:23:51 PM GMT to Saturday, August 24, 2024 9:48:19 PM GMT.

Additional data such as comments, scores, and media were obtained by Friday, November 15, 2024 5:00:00 AM GMT.

The Media Directory

This is a dump of all media in the dataset. It contains only PNGs.

ID Files

This dataset contains 2 files for identification: main.csv and media.csv.

main.csv Fields

main.csv includes metadata and text data about the post:

post_id: int - A unique, dataset-specific identifier for each post.
create_utc: int - The time (in seconds) the post was created, in epoch time.
post_url: string - The URL of the post. This can be used to collect further data depending on your purposes.
title: string - Title of the post.
comment[1-3]: string|nan - The text of the i-th top-scoring comment.
comment[1-3]_score: int|nan - The score of the i-th top-scoring comment.

media.csv Fields

media.csv includes identifiers for media:

post_id: int - Identifies the post the media is associated to. Refers to post_id in main.csv
media_path: str - Locates the file containing the media. This path is relative to media.csv's directory.

Data Collection

Every 2 hours, a routine scraped 200 posts from /r/popular through the Reddit API then saved the URL of every post to a database from about July 27, 2024 to August 24, 2024.

The script collect_all_reddit.py then created the dataset on November 15, 2024.

Usage Guide

This guide uses pandas and PIL to load data:

import pandas as pd
import csv

from PIL import Image

Load the main and media data using

df_main = pd.read_csv("main.csv", sep="\t", quoting=csv.QUOTE_NONE)
df_media = pd.read_csv("media.csv", sep="\t", quoting=csv.QUOTE_NONE)

To create a combined language-image dataset, use an SQL-Like join:

df_lang_img = pd.merge(df_main, df_media, how="left", on="post_id")

This creates a new dataframe with all the columns from main.csv and media.csv. In this new dataframe, each post is repeated for each associated image. If a post does not have an image, the media_path is NaN.

Let's consider one row:

row = df_lang_img.iloc[0]

Then the image can be loaded with

with Image.open(row["media_path"]) as im:
    im.show()

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