📊 Probability Project: Analyzing COVID Data

Welcome to the Probability Project! This Dash application is designed to provide a comprehensive analysis of COVID-19 data using various statistical methods and visualizations. 🌟

🚀 Introduction

This project leverages the power of Dash and Plotly to explore COVID-19 data in a fun and interactive way. With options for summary statistics, probability calculations, and predictions, this tool is your go-to for visualizing and analyzing COVID-19 statistics. Whether you're a student of probability and statistics or just curious about data trends, this app has something for you!

🔍 Features

• Summary Statistics: Get descriptive statistics of COVID-19 cases, deaths, and recoveries.
• Probability Analysis: Visualize the probabilities of deaths and recoveries across different provinces.
• Graphical Representations: Explore various plots including scatter plots, pie charts, and bar charts.
• Predictions: Make predictions about deaths and recoveries based on new case inputs.

1. Load Data

The app reads COVID-19 data from a CSV file. Make sure to update the file path to the location of your PKcovid.csv file.```python file_path = r"C:\Users\Admin\Downloads\pakCovid\PKcovid.csv" mydata = pd.read_csv(file_path)

2. App Layout

The layout consists of dropdowns, buttons, and various graphs:

• Dropdown Menu: Select the type of analysis you want to perform.
• Prediction Inputs: Enter new case values to predict deaths and recoveries.
• Graphs: Visualizations are updated based on your selection.

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3. Callbacks

The app uses Dash callbacks to update the content based on user interactions:

• Toggle Prediction Inputs: Shows or hides prediction inputs based on dropdown selection.
• Run Analysis: Computes and displays results based on the selected analysis type.

🔧 Dependencies

Make sure you have the following Python packages installed:

• dash: For building the interactive web application.
• dash_bootstrap_components: For enhanced styling and layout.
• pandas: For data manipulation and analysis.
• plotly: For creating interactive plots and charts.
• statsmodels: For statistical modeling and predictions.

You can install the dependencies using pip:

bash

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pip install dash dash-bootstrap-components pandas plotly statsmodels

📊 Available Analyses

1. Summary Statistics

Displays descriptive statistics for cases, deaths, and recoveries.

2. Probability Calculations

Calculates and visualizes the probabilities of death and recovery by province.

3. Graphical Representations

Generates various plots including:

• Scatter plots of deaths and recoveries.
• Pie charts of cases, deaths, and recoveries.
• Bar charts showing component values.

4. Predictions

Uses linear regression to predict deaths and recoveries based on user-provided case values.

Here are the results:

Linear Regression Prediction of Deaths and Recover Cases:

Linear Regression Prediction Recover Cases:

Pie Chart of Death Cases in each Province:

Pie Chart of Recover Cases in each Province:

Scatter Plot of death Cases in each Province:

Component bar Plot of death Cases in each Province:

Component bar Plot of Recover Cases in each Province:

📝 Running the App

To run the app, simply execute the following command in your terminal:

bash

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python app.py

The app will start running on your local server. Open your web browser and navigate to http://127.0.0.1:8050/ to start exploring the data.

📂 File Structure

• app.py: Main Python script for the Dash application.
• PKcovid.csv: CSV file containing the COVID-19 data.

💬 Contributing

If you'd like to contribute to this project, feel free to fork the repository, make changes, and submit a pull request. Contributions, feedback, and suggestions are always welcome!