Welcome to the Flight Crash Statistics Dashboard project! This application is designed to scrape flight crash data from Aviation Safety Network using Selenium in Python and present the statistics on your own website using Dash and Plotly graphs. The data covers flight crashes from 1919 to 2023.

• Features
• Installation
• Usage
• Screenshots
• Contributing
• License

• Web scraping flight crash data from Aviation Safety Network using Selenium.
• Displaying statistics and visualizations of flight crashes using Dash and Plotly.
• Data covers the period from 1919 to 2023, providing a comprehensive overview of historical flight incidents.
• Predicting by trained data future catastrophies with losses in crew and passengers.

Follow these steps to set up and run the Flight Crash Statistics Dashboard on your local machine:

1. Clone the repository:

   git clone https://github.com/Villad-dev/WebScraping.git
   cd WebScraping
   

To use this application, follow these steps:

1. Import the necessary modules for web scraping:

import csv from selenium import webdriver from selenium.webdriver.common.by import By from selenium.webdriver.chrome.options import Options from selenium.common.exceptions import NoSuchElementException from selenium.common.exceptions import NoSuchWindowException from selenium.common.exceptions import StaleElementReferenceException from selenium.common.exceptions import WebDriverException

1. Process and format the scraped data as needed using the Pandas library.

import pandas as pd from dateutil import parser

Dash Dashboard

1. Import the necessary modules for creating the Dash dashboard:

import dash import base64 import requests import pandas as pd import plotly.express as px from dash import dcc from dash import html from dash import dash_table from dash.dependencies import Input, Output

2. Launch the Dash application by running the app.py script:

python app.py

3. Open your web browser and navigate to http://localhost:8050 to interact with the dashboard.

4. Remember to customize the code as needed to fit your specific use case and data processing requirements.

This project is licensed under the MIT License.

For applying all visual features beter to use Visual Studio code or whatever.