Urgent Python Developer for SciArt Visualization project in 1 day! -- 2

I am urgently looking for a highly skilled Python developer who can assist me in creating a SciArt/data visualization project within a one-day timeframe. I would like you to use jupyter notebook for this project due to the timeframe and its built in features. This SciArt project is the representation of planets (if you have a better idea, let me know) For example you could: 1)Gather scientific data about each planet, including size, color, texture, and any distinctive features. 2)Decide on the artistic style you want for your planets. You might want to create realistic representations, abstract representations, or a stylized artistic interpretation. 3) Utilize Python libraries like Matplotlib, Plotly, or Mayavi for 2D and 3D visualizations. These libraries allow you to create plots and visualizations directly in your Jupyter Notebook. 4)Start by representing each planet as a basic shape (e.g., spheres for planets). You can use Matplotlib's plot_surface or scatter functions for this. import [login to view URL] as plt from [login to view URL] import Axes3D # Example: Creating a simple 3D sphere representing a planet fig = [login to view URL]() ax = fig.add_subplot(111, projection='3d') [login to view URL](0, 0, 0, s=1000, color='orange', marker='o') # Example: Sun [login to view URL](10, 0, 0, s=100, color='blue', marker='o') # Example: Earth [login to view URL]() 5)Enhance the representation by adding details based on scientific data. For example, you can add textures, colors, and rings for planets like Saturn. # Example: Adding details to the Earth [login to view URL](0, 0, 0, s=1000, color='orange', marker='o') # Sun [login to view URL](10, 0, 0, s=100, color='blue', marker='o') # Earth [login to view URL](10, 0, 0, ' Earth', color='black', fontsize=8) [login to view URL]() 6)For more realistic representations, you might want to use texture mapping. You can either find high-resolution images of planets online or create your own textures. # Example: Texture mapping for Earth from matplotlib import cm import [login to view URL] as mpimg img = [login to view URL]('[login to view URL]') # Replace with the path to your texture image [login to view URL](img, extent=(-11, -9, -1, 1), alpha=0.8) [login to view URL]() 7)Adjust the colors and lighting to create visually appealing effects. You can use different color maps and shading techniques. # Example: Adjusting colors and lighting for Earth [login to view URL](0, 0, 0, s=1000, color='orange', marker='o') # Sun [login to view URL](10, 0, 0, s=100, color='blue', marker='o', edgecolors='black', linewidth=0.5) # Earth [login to view URL](10, 0, 0, ' Earth', color='black', fontsize=8) [login to view URL]() 8)Repeat the process for each planet, adjusting sizes and distances based on the scientific data. 9)Add artistic elements, such as blending, masking, or abstract patterns, to enhance the overall visual appeal. 10)Remember to balance scientific accuracy with artistic creativity to achieve a visually stunning and informative representation of the solar system. You could search for data on google or from the NASA website.