---
language:
- en
license: mit
task_categories:
- text-generation
- question-answering
tags:
- reddit
- education
- ipmat
- entrance-exam
- india
size_categories:
- 1K<n<10K
---

# r/IPMATtards Reddit Dataset

## Dataset Description

This dataset contains scraped posts and comments from the **r/IPMATtards** subreddit, a community dedicated to aspirants of the **Integrated Programme in Management Aptitude Test (IPMAT)** in India. 

The data is structured into two main components:
1. **Posts**: Top-level submissions including titles, body text, scores, and metadata.
2. **Comments**: Threaded replies associated with the posts, including recursion depth and parent-child relationships.

## Dataset Structure

The dataset is provided in **Parquet** format, optimized for the Hugging Face Hub.

### 1. Posts (`posts.parquet`)

| Feature | Type | Description |
|:--------|:-----|:------------|
| `id` | string | Unique Reddit ID for the post (e.g., `t3_xyz`) |
| `title` | string | Title of the post |
| `author` | string | Reddit username of the author |
| `body` | string | The main text content of the post |
| `score` | int64 | Net upvotes (karma) at time of scraping |
| `comments_count` | int64 | Number of comments on the post |
| `created_utc` | string | Creation timestamp (UTC) |
| `url` | string | Direct URL to the reddit post |
| `crawled_at` | string | Timestamp when the data was scraped |

### 2. Comments (`comments.parquet`)

| Feature | Type | Description |
|:--------|:-----|:------------|
| `id` | string | Unique Reddit ID for the comment (e.g., `t1_abc`) |
| `post_id` | string | ID of the parent post (`t3_...`) |
| `parent_id` | string | ID of the parent comment or post this replies to |
| `author` | string | Reddit username of the author |
| `body` | string | Text content of the comment |
| `score` | int64 | Net upvotes |
| `depth` | int64 | Nesting level (0 = top-level comment) |
| `path` | string | Materialized path for reconstructing the tree |
| `created_utc` | string | Creation timestamp (UTC) |

## Usage

You can load this dataset directly using the `datasets` library:

```python
from datasets import load_dataset

# Load posts
posts = load_dataset("parquet", data_files="parquet_export/posts.parquet", split="train")

# Load comments
comments = load_dataset("parquet", data_files="parquet_export/comments.parquet", split="train")

print(posts[0])
```

## Collection

This data was collected using a custom Python scraper utilizing `requests` and `BeautifulSoup`. It targets the old.reddit.com interface for efficiency.

## License

This dataset is distributed under the MIT License. Please respect Reddit's API cleaning rules and user privacy when using this data.