A powerful Streamlit web app to analyze WhatsApp chat exports. Get deep insights into your conversations with statistics, timelines, activity heatmaps, word clouds, emoji analysis, and sentiment detection.

• File Summary: Quick stats on messages, words, media, and links.
• User Selection: Analyze overall or individual user activity.
• Timelines: Interactive monthly and daily message trends.
• Activity Analysis: Most active days/months and weekly heatmaps.
• Wordcloud & Common Words: Visualize most used words.
• Emoji Analysis: Top emojis and their usage.
• Sentiment Analysis: Detect positive, negative, and neutral messages, with keyword and dangerous message detection.

1. Clone the repository:

   git clone https://github.com/yourusername/WhatsappChat_Analyzer.git
   cd WhatsappChat_Analyzer

2. Create and activate a virtual environment (recommended):

   python -m venv .venv
   .venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

1. Export your WhatsApp chat (without media) from your phone.
2. Run the app:

   streamlit run app.py

3. Open the web browser (usually at http://localhost:8501).
4. Upload your chat .txt file and explore the analysis!

WhatsappChat_Analyzer/
│
├── app.py                # Main Streamlit app
├── preprocessor.py       # Chat preprocessing functions
├── helper.py             # Analysis helper functions
├── sentiment.py          # Sentiment analysis logic
├── requirements.txt      # Python dependencies
├── logo.png              # App logo (optional)
└── README.md             # Project documentation

• Only supports WhatsApp chat exports in .txt format.
• For best results, export chats without media.
• Sentiment analysis uses a pre-trained ML model (see sentiment.py).

See requirements.txt for the full list. Key packages:

• streamlit
• matplotlib
• seaborn
• plotly
• pandas
• numpy
• scikit-learn
• wordcloud
• Tf/Idf Vector
• emoji

Developed by Param Dholakia.
Inspired by the need for better chat insights!

MIT License. See LICENSE for details.