This README provides an overview of the functionality and structure of the app.
The app is designed to provide various functionalities for working with data, including data loading, visualization, and showcasing skills and experience.
The app sets up the page configuration, including the title, icon, and layout. It displays a title and introduction text to provide context for users.
The load_data function reads a CSV file named "data.csv" attached alongside the code and caches the data for better performance.
The app creates a sidebar with navigation options for different pages: "Data Overview", "Data Visualization", and "Skills and Experience". The user can select a page from the radio buttons.
This function displays an overview of the dataset, including the number of rows and columns, and a sample of the data.
This function allows the user to select columns from the dataset for visualization. The App user can choose from different plot types (line plot, scatter plot, bar plot, and histogram), and the app displays the selected plot.
This function showcases My skills and experience, including programming languages, data analysis libraries, and a list of experience points.
The main function orchestrates the app's logic. It loads the data, creates the sidebar navigation, and calls the selected page function based on the user's choice.
To run this app, you'll need to have the following Python libraries installed: Streamlit, Pandas, Matplotlib, and Seaborn. You can install them using pip:
pip install streamlit pandas matplotlib seabornAfter installing the required libraries, you can run the app using the following command:
streamlit run app.pyThis command will start the app and open it in your default web browser.
For additional information or support, please refer to the app documentation or contact me.