Space Data Analysis Project

This repository contains code and data for scraping spaceflight data from nextspaceflight.com using Python, and visualizing the results using Matplotlib, Seaborn, and Plotly in a Google Colab notebook.

Usage

1. Open the provided Google Colab notebook ('Space_Missions_Analysis_(start).ipynb') to visualize the analysis, to view ploty plots open the notebook in Google Colab.

Data Scraping

The main.py script uses Beautiful Soup to scrape data from nextspaceflight.com and saves it as a CSV file.

Reproducible Code Steps

To run the Web Scraping on your local machine, follow these steps:

1. Clone the Repository: Clone the Breakout Game repository to your local machine:

   git clone https://github.com/dieegogutierrez/SpaceRaceAnalysis.git

2. Navigate to the Project Directory: Change your current directory to the root of the cloned repository:

   cd SpaceRace

3. Install Python Dependencies: Make sure you have Python installed on your machine. Then, install the required dependencies using pip:

   python3.9 -m venv venv
   source venv/bin/activate
   pip install -r requirements.txt

4. Run the Code: Execute the main Python script to start scraping (it will take some time to finish):

   python main.py

Data Visualization

The 'Space_Missions_Analysis_(start).ipynb' notebook in Google Colab contains code to visualize the scraped data:

• Line charts using Matplotlib and Seaborn to show trends over time.
• Interactive Plotly graphs for detailed data exploration. Note that Plotly graphs are visible only when accessing the Google Colab notebook.

Results

The visualizations provide insights into spaceflight data trends and patterns, helping us understand various aspects of space exploration.