|
--- |
|
dataset_info: |
|
features: |
|
- name: id |
|
dtype: int64 |
|
- name: title |
|
dtype: string |
|
- name: text_markdown |
|
dtype: string |
|
- name: timestamp |
|
dtype: uint64 |
|
- name: author_id |
|
dtype: int64 |
|
- name: username |
|
dtype: string |
|
- name: rating |
|
dtype: int64 |
|
- name: pluses |
|
dtype: int64 |
|
- name: minuses |
|
dtype: int64 |
|
- name: url |
|
dtype: string |
|
- name: tags |
|
sequence: string |
|
- name: blocks |
|
sequence: |
|
- name: data |
|
dtype: string |
|
- name: type |
|
dtype: string |
|
- name: comments |
|
sequence: |
|
- name: id |
|
dtype: int64 |
|
- name: timestamp |
|
dtype: uint64 |
|
- name: parent_id |
|
dtype: int64 |
|
- name: text_markdown |
|
dtype: string |
|
- name: text_html |
|
dtype: string |
|
- name: images |
|
sequence: string |
|
- name: rating |
|
dtype: int64 |
|
- name: pluses |
|
dtype: int64 |
|
- name: minuses |
|
dtype: int64 |
|
- name: author_id |
|
dtype: int64 |
|
- name: username |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 96105803658 |
|
num_examples: 6907622 |
|
download_size: 20196853689 |
|
dataset_size: 96105803658 |
|
task_categories: |
|
- text-generation |
|
language: |
|
- ru |
|
size_categories: |
|
- 1M<n<10M |
|
--- |
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|
|
|
|
# Pikabu dataset |
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|
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## Table of Contents |
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- [Table of Contents](#table-of-contents) |
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- [Description](#description) |
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- [Usage](#usage) |
|
- [Data Instances](#data-instances) |
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- [Source Data](#source-data) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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|
|
## Description |
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|
|
**Summary:** Dataset of posts and comments from [pikabu.ru](https://pikabu.ru/), a website that is Russian Reddit/9gag. |
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|
|
**Script:** [convert_pikabu.py](https://github.com/IlyaGusev/rulm/blob/master/data_processing/convert_pikabu.py) |
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|
**Point of Contact:** [Ilya Gusev](ilya.gusev@phystech.edu) |
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|
**Languages:** Mostly Russian. |
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|
|
## Usage |
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|
|
Prerequisites: |
|
```bash |
|
pip install datasets zstandard jsonlines pysimdjson |
|
``` |
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|
|
Dataset iteration: |
|
```python |
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from datasets import load_dataset |
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dataset = load_dataset('IlyaGusev/pikabu', split="train", streaming=True) |
|
for example in dataset: |
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print(example["text_markdown"]) |
|
``` |
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|
|
## Data Instances |
|
|
|
``` |
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{ |
|
"id": 69911642, |
|
"title": "Что можно купить в Китае за цену нового iPhone 11 Pro", |
|
"text_markdown": "...", |
|
"timestamp": 1571221527, |
|
"author_id": 2900955, |
|
"username": "chinatoday.ru", |
|
"rating": -4, |
|
"pluses": 9, |
|
"minuses": 13, |
|
"url": "...", |
|
"tags": ["Китай", "AliExpress", "Бизнес"], |
|
"blocks": {"data": ["...", "..."], "type": ["text", "text"]}, |
|
"comments": { |
|
"id": [152116588, 152116426], |
|
"text_markdown": ["...", "..."], |
|
"text_html": ["...", "..."], |
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"images": [[], []], |
|
"rating": [2, 0], |
|
"pluses": [2, 0], |
|
"minuses": [0, 0], |
|
"author_id": [2104711, 2900955], |
|
"username": ["FlyZombieFly", "chinatoday.ru"] |
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} |
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} |
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``` |
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|
|
You can use this little helper to unflatten sequences: |
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|
|
```python |
|
def revert_flattening(records): |
|
fixed_records = [] |
|
for key, values in records.items(): |
|
if not fixed_records: |
|
fixed_records = [{} for _ in range(len(values))] |
|
for i, value in enumerate(values): |
|
fixed_records[i][key] = value |
|
return fixed_records |
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``` |
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|
|
|
|
## Source Data |
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|
|
* The data source is the [Pikabu](https://pikabu.ru/) website. |
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* An original dump can be found here: [pikastat](https://pikastat.d3d.info/) |
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* Processing script is [here](https://github.com/IlyaGusev/rulm/blob/master/data_processing/convert_pikabu.py). |
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|
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## Personal and Sensitive Information |
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|
|
The dataset is not anonymized, so individuals' names can be found in the dataset. Information about the original authors is included in the dataset where possible. |
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|
