Abstract
WhatsApp has emerged as the go-to method for communication. Conversations on WhatsApp cover a wide range of topics among individuals or groups. This data can be valuable for advancing technologies like machine learning, which rely on quality data for effective learning experiences. Our tool is designed to offer comprehensive analysis of WhatsApp data, regardless of the subject of the conversation. By using our developed code, a deeper insight into the data can be achieved. One great benefit of this tool is that it utilizes common Python libraries like Pandas, Matplotlib, Seaborn, Streamlit, Numpy, Re, Emojis, and sentiment analysis to generate data frames and visualizations. These are then showcased in a streamlit web app that is efficient and requires fewer resources. This makes it ideal for analyzing large datasets. Key Words: Inspecting, Examining, Research, Data Analysis, Matplotlib, Pandas, Streamlit
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