This project utilizes Streamlit and Python to create a web application for analyzing website traffic data.
Streamlit URL:https://websitetrafficanalyzerusingapppython.streamlit.app/ Features CSV Upload: Users can upload a CSV file containing website traffic data. Model Prediction: The application trains a Linear Regression model on the uploaded data to predict unique visits based on page loads, first visits, returning visits, and days since launch. Visualization: It provides visualizations including line charts showing page loads, unique visits, first visits, and returning visits over time, histograms displaying unique visits for each day, and density heatmaps illustrating correlations between different data points. Installation To run the application locally:
Install the required dependencies using pip install -r requirements.txt. Run the application using streamlit run app.py. Usage Upload your CSV file containing website traffic data. Explore the actual vs. predicted values and visualizations to analyze website traffic trends. Technologies Used Python Streamlit Pandas Scikit-learn Matplotlib Seaborn Plotly
License This project is licensed under the MIT License.