Label Dash

Label Dash is a quick text labeling tool built with Streamlit. It lets you quickly annotate your CSV data with custom labels in an interactive, fun way.

Features

• CSV Upload: Easily load any CSV file.
• Column Selector: Choose which columns from your CSV to display for labeling.
• Custom Labels: Define your own label set (e.g., Positive, Negative, Neutral).
• Interactive Labeling: Navigate through records with Previous/Next buttons and assign labels via radio buttons.
• Progress Tracking: Monitor your labeling progress with a real-time count of labeled records and a progress bar.
• Multiple Use Cases: Create annotations for sentiment analysis, topic categorization, intent classification, spam detection, and more.
• Export Results: Download a new CSV with an added label column containing your annotations. The output file name can be customized.

Use Cases

• Sentiment Classification: Rapidly label customer feedback, social media comments, or survey responses as positive, negative, or neutral.
• Topic Tagging: Annotate articles, blog posts, or news headlines with relevant topics or categories.
• Intent Recognition: Label user utterances for chatbots or virtual assistants (e.g., purchase intent, complaint, greeting).
• Spam Detection: Identify and tag spam or unwanted messages in your dataset.
• Custom Projects: Any CSV-based labeling task—fine-tune to your specific domain or workflow.

Getting Started

1. Clone the repo

   git clone https://github.com/danishjeetsingh/label_dash.git
   cd label_dash

2. Install dependencies

   pip install streamlit pandas

3. Run the app

   streamlit run app.py

4. Annotate & Export

   • Upload your CSV.
   • Select columns to display and define your labels.
   • Label each record by selecting an option from the radio buttons.
   • Download the labeled CSV when finished.

License

This project is open source and available under the MIT License.