infinite-dataset-hub/PythonLibAspectSentiment

---
license: mit
tags:
- infinite-dataset-hub
- synthetic
---

# PythonLibAspectSentiment

tags: aspect-based sentiment, python libraries, sentiment analysis, classification

_Note: This is an AI-generated dataset so its content may be inaccurate or false_

**Dataset Description:**

The 'PythonLibAspectSentiment' dataset is curated for the purpose of conducting aspect-based sentiment analysis on online posts and reviews concerning well-known Python libraries. The dataset is designed to assist ML practitioners in identifying specific aspects of Python libraries that may require refinement, improvement, or attention based on public feedback. Each entry in the dataset contains a textual review or comment, a primary label that signifies the aspect of the library discussed, and a secondary label indicating the sentiment (positive, negative, or neutral) associated with that aspect.

**CSV Content Preview:**

```csv
Text,Label,Sentiment
"The documentation for NumPy is incredibly clear and helpful. I appreciate the community's effort in making it accessible for beginners.","Documentation","Positive"
"pandas has some issues with multi-index support, which can be really confusing.","Multi-Index","Negative"
"I love how Matplotlib makes data visualization so simple and intuitive. It's a must-have for any data scientist!","Data Visualization","Positive"
"The development team behind scikit-learn has been proactive in releasing updates, but some of the newer features feel unpolished.","Feature Update","Neutral"
"I encountered some frustrating bugs while using Flask. It's good for small projects, but not production-ready for large-scale systems.","Bugs","Negative"
```

This CSV preview provides a taste of the type of data one would expect to find in the 'PythonLibAspectSentiment' dataset. The 'Text' column contains the actual content from user reviews or comments, while 'Label' and 'Sentiment' columns respectively specify the aspect discussed in the text and the sentiment expressed towards that aspect.

**Source of the data:**

The dataset was generated using the [Infinite Dataset Hub](https://huggingface.co/spaces/infinite-dataset-hub/infinite-dataset-hub) and microsoft/Phi-3-mini-4k-instruct using the query 'Aspect based sentiment analysis dataset. Details: the data comes from online posts and reviews and are about famous python libraries. The goal is to classify those posts to extract what aspects of the libraries that need refinements. The dataset has one label for the aspect and also for the sentiment.':

- **Dataset Generation Page**: https://huggingface.co/spaces/infinite-dataset-hub/infinite-dataset-hub?q=Aspect+based+sentiment+analysis+dataset.+Details:+the+data+comes+from+online+posts+and+reviews+and+are+about+famous+python+libraries.+The+goal+is+to+classify+those+posts+to+extract+what+aspects+of+the+libraries+that+need+refinements.+The+dataset+has+one+label+for+the+aspect+and+also+for+the+sentiment.&dataset=PythonLibAspectSentiment&tags=aspect-based+sentiment,+python+libraries,+sentiment+analysis,+classification
- **Model**: https://huggingface.co/microsoft/Phi-3-mini-4k-instruct
- **More Datasets**: https://huggingface.co/datasets?other=infinite-dataset-hub