Page Specific Features

Homepage

• Layout: Organized into columns for a clean, user-friendly design. Features weather updates, dynamic date/time display, project showcases, Lottie animations, and a contact section.

• Weather: Fetches temperature data from the OpenWeatherMap API.

• Lottie Animations: Users can select and display various animations via a sidebar dropdown.

• Personal Introduction: A brief bio of the developer, including a link to a personal website.

• Image Upload/Camera: Allows users to interact by uploading or capturing images.

• Project Categories/Subcategories: Users can select from categories (e.g., Power BI, Python, SQL) and view detailed project descriptions and links for more information.

• Interactive Experience: Placeholder images for each category enhance visual appeal. Users can upload or capture images for a more personalized experience.

Project Page: Data Visualization for Earthquake Data

The Project Page provides an interactive platform for visualizing earthquake-related data, utilizing a CSV file upload feature and offering various options for data analysis and visualization. Upon loading the data, users can explore the dataset and select from the navigation menu to view different visual representations. Below is a breakdown of the available options:

Navigation Menu Options:

Once the earthquake-related CSV file is uploaded, the following options are available for data exploration:

1. Data Summary
   This section provides a comprehensive summary of the dataset, including key statistical metrics such as mean, standard deviation, and other summary statistics. It gives users an overview of the dataset's distribution and variability.

2. Data Header
   Displays the first few rows of the dataset, offering a snapshot of the data structure. This allows users to quickly understand the columns and types of data available before diving deeper into the analysis.

3. Scatter Plot
   This visualization charts the relationship between Magnitude and Depth of the earthquakes, displaying a scatter plot. It highlights the variability in the data, enabling users to visually analyze any correlations or patterns between these two key parameters.

4. Charting
   This section offers multiple visualizations of geographical occurrence, utilizing both a map and bar/column charts to represent earthquake data by location. The map visualization shows where the earthquakes occurred geographically, while the chart provides a clearer comparison of the data, such as frequency or magnitude across regions.

How It Works

• File Upload: Users begin by uploading a CSV file containing earthquake data. The system reads and processes the data to prepare it for analysis.

• Data Display: Upon successful file upload, the data structure is displayed. The user can then select from the navigation menu to view the desired visualization.

• Interactive Visualizations: Depending on the selected option, different types of charts and visual representations are rendered, offering valuable insights into the earthquake data.

Contact Page

• Form: Collects user name, email, and message, enabling communication with the developer.

• Submission Confirmation: Users are notified when their message has been successfully submitted.

Requirements

To run the project, the following Python packages are required:

• NumPy, Matplotlib, Pandas, Pillow, Streamlit, Streamlit-Lottie

Conclusion

This Streamlit-based web application offers a comprehensive, interactive platform that combines useful data displays, engaging animations, and a professional showcase of projects. Its modular design and straightforward setup make it an excellent starting point for more complex applications. The app is not only a demonstration of technical proficiency but also a reflection of Kiran's work and expertise.