Create README.md

README.md

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+---
+task_categories:
+- feature-extraction
+- text-generation
+language:
+- en
+size_categories:
+- 10K<n<100K
+---
+
+# 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()