---
license: agpl-3.0
task_categories:
- text-generation
- text-classification
language:
- en
tags:
- Poem
size_categories:
- 10K<n<100K
---

From: https://www.kaggle.com/datasets/tgdivy/poetry-foundation-poems

**Poetry Foundation Poems Dataset**

**Overview**

This dataset contains a collection of 13.9k poems sourced from the Poetry Foundation website. Each poem entry includes its title, author, and associated tags (if available). The dataset provides a robust resource for exploring poetry, analyzing thematic trends, or creating applications such as poem generators.

**Dataset Structure**

The dataset consists of the following columns:

	1.	Title: The title of the poem.
    
	2.	Author: The name of the poem’s author.
    
	3.	Tags: The thematic tags or categories associated with the poems.

Dataset Highlights

	•	Size: The dataset includes 13.9k rows, with each row representing an individual poem.
    
	•	Diversity: Poems span a wide range of topics and authors, making it a rich resource for literary and thematic exploration.
    
	•	Tags: The tags provide a structured way to categorize and filter poems by themes, enhancing the dataset’s usability for research and creative projects.
    

**Use Cases**

	1.	Poem Generation:
    
Train models to generate poems based on user-inputted topics or tags.

	2.	Thematic and Sentiment Analysis:
    
Analyze trends in poetic themes, sentiments, or styles over time.

	3.	NLP Tasks:
    
Use the dataset for text classification, clustering, or other natural language processing tasks.

	4.	Educational Resources:
    
Develop tools or applications for poetry analysis, learning, or teaching.

	5.	Visualizations:
    
Create word clouds or charts using the tags to identify common themes in poetry.


**Technical Details**

	•	File Size: Approximately 13,900 rows of data.
    
	•	Format: Typically provided in CSV or JSON format.
    
	•	Dependencies:
    
	•	Pandas for data manipulation.
    
	•	NLTK or spaCy for natural language processing.
    
	•	Matplotlib or WordCloud for creating visualizations.


**Licensing**

This dataset is under **GNU Affero General Public License v3.0**.


**Acknowledgments**

The dataset was compiled to provide researchers, developers, and enthusiasts with a structured collection of poetry for creative and analytical purposes. All credits go to the original authors and the Poetry Foundation for their work in making these poems accessible.


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