The WhatsApp Chat Analyzer is a powerful tool designed to provide insightful analysis of WhatsApp conversations. By leveraging advanced data processing techniques, this application extracts and visualizes key metrics from chat logs, enabling users to gain a deeper understanding of their messaging patterns. Users can upload their WhatsApp chat exports, and the analyzer will generate comprehensive reports on various aspects such as the most active participants, peak chatting times, frequently used words, and emojis.
Working on the WhatsApp Chat Analyzer project provided several valuable learning experiences:
1> Data Processing: Gained hands-on experience with text data preprocessing, cleaning, and transformation.
2> Visualization: Learned how to create effective and insightful visualizations using Matplotlib and Seaborn.
3> Natural Language Processing: Applied NLP techniques to analyze chat sentiment and extract meaningful insights.
3> Streamlit: Developed a user-friendly interface for data analysis applications using Streamlit.
4> Project Management: Improved project organization and documentation skills by maintaining a clear and structured codebase.
1> Analyze chat activity and identify the most active participants.
2> Visualize peak chatting times.
3> Extract and display frequently used words and emojis.
4> User-friendly interface with detailed visualizations.
1> Python
2> Streamlit
3> Pandas
4> Matplotlib
5> Seaborn
6> NLP libraries (such as NLTK )