WhatsApp Chat Analyzer 📊

Welcome to the WhatsApp Chat Analyzer! This project uses Streamlit to provide insights and visualizations of WhatsApp chat data. Analyze message counts, media shared, activity patterns, and more.

Features 🌟

• Upload WhatsApp Chat Files: Upload your .txt chat export file.
• Message Statistics: Get total message counts, word counts, media shared, and links shared.
• User-based Analysis: Analyze data for a specific user or the entire group.
• Timelines:
  • 📅 Monthly timeline of messages.
  • 📆 Daily timeline of messages.
• Activity Map:
  • 📆 Most active day of the week.
  • 🗓️ Most active month.
  • 🌡️ Weekly activity heatmap.
• Busiest Users: Identify the most active users in a group chat.
• Word Cloud: Generate a word cloud of the most common words used.
• Common Words: Display frequently used words (excluding stop words).
• Emoji Analysis: Breakdown of the most frequently used emojis.

Installation 🚀

1. Clone this repository:

   git clone https://github.com/your-repository/whatsapp-chat-analyzer.git

2. Install the required dependencies:

   pip install -r requirements.txt
   

Usage 💻

1. Run the Streamlit app:

   streamlit run app.py
   

2. Upload your WhatsApp chat .txt file using the file uploader in the sidebar.

3. Select the user or "Overall" to analyze data for the entire chat.

4. Click on "Show Analysis" to view the results, including statistics, visualizations, and emoji usage.

File Structure 📂

• app.py: Main application file for the Streamlit dashboard.
• helper.py: Functions for data processing and generating statistics, timelines, and visualizations.
• preprocessor.py: Handles preprocessing of the WhatsApp chat data.
• stop_hinglish.txt: List of stop words excluded from analysis.
• requirements.txt: Lists project dependencies.

Preprocessing 🛠️

• The chat data is parsed to extract messages, user names, and timestamps.
• Columns generated include:
  • user: Sender of the message.
  • message: Content of the message.
  • date: Date and time of the message.
  • Additional time-based columns like day_name, hour, minute, etc.

Dependencies 📦

The project requires the following libraries:

• Streamlit: Web framework for the dashboard.
• Matplotlib: For graphs and plots.
• Seaborn: For heatmaps and additional plotting.
• Pandas: For data manipulation and analysis.
• WordCloud: For generating word clouds.
• Urlextract: For URL extraction from the chat.
• Emoji: For analyzing emoji usage.

Dependencies 📦

1. pip install -r requirements.txt
   

Example 🖼️

Here's a preview of the analysis features:

• Top Statistics: Overview of total messages, words, media, and links.
• Monthly and Daily Timelines: Visualize message activity over time.
• WordCloud: Display most frequent words used in the chat.
• Emoji Analysis: Breakdown of frequently used emojis.

Contributing 🤝

Feel free to fork the repository and make modifications. Contributions are welcome to enhance features or fix issues.