# Orion Constellation Project for Review

Hi Everyone,

Here is a link to my Orion Constellation Project. https://github.com/CSorrel58/personal_projects/blob/master/clinton_constellation.ipynb

Please let me know what you think and don’t hold back!

Congrats on finishing up. It’s hard to see from your figure but I think you may have fallen into the trap of using the standard `matplotlib.pyplot.scatter` function which only plots in 2D. You need to be using the `.scatter` method of the Axes3D object to get a proper z-axis value.

``````ax3d = fig_3d.add_subplot(1, 1, 1, projection="3d")
ax3d.scatter(...)  # Must use the method.
ax3d.set_zlabel(...)  # 3D Object has zlabel methods.
``````

That second plot could do with being a little more visible too but they might be a result of the 2D plot, if not check the docs for ways to change marker size, shape, colour etc. - https://matplotlib.org/3.3.0/api/_as_gen/mpl_toolkits.mplot3d.axes3d.Axes3D.html#mpl_toolkits.mplot3d.axes3d.Axes3D.scatter

Thanks for this! I was able to update the 3D plot, but not until I added the import information from the first kernel. So it ended up looking like this:

``````%matplotlib notebook
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
x = [-0.41, 0.57, 0.07, 0.00, -0.29, -0.32,-0.50,-0.23, -0.23]
y = [4.12, 7.71, 2.36, 9.10, 13.35, 8.13, 7.19, 13.25,13.43]
z = [2.06, 0.84, 1.56, 2.07, 2.36, 1.72, 0.66, 1.25,1.38]
ax3d = plt.figure()
ax3d = ax3d.add_subplot(1,1,1,projection="3d")
ax3d.scatter(x,y,z)
plt.title('Orion in 3d')
plt.xlabel('X Axis of Stars')
plt.ylabel('Y Axis of Stars')
ax3d.set_zlabel('Z Axis of Stars')
plt.show()
``````

is there something I need to do for that kernel’s information to be usable across the document instead of having to copy/paste it each time?

Good stuff, happy to hear it was sorted. If you like working with Jupyter notebooks and you’re frequently starting your files with those imports there’s probably a way to get them to import automatically when you start a session. I’m afraid it’s been a while since I used them so I can’t remember any details off-hand but I believe that it’s fairly straightforward. Alternatively you could probably set-up your new files to open with those lines ready to execute or delete as necessary. Might be worth looking into at least.

1 Like

Thanks! Your comment about Jupyter reminds me of something I’ve been curious about - so far it’s been the only tool outside of codeacademy where I’ve edited. where are you normally writing your python? When I search for where python is used I either get use cases or something like Sublime text that doesn’t appear to connect to any data.

If i’m looking to practice on my own, would I need to execute it in the command prompt and somehow hook it to something like Kaggle? Or is there some other tool I need to get?

As for writing there’s numerous options for writing from basic text editors like vim (sans plug-ins) to full fledged IDEs. Worth trying a few out to see what you like. I think there’s a forum thread or two around with a few folks preferences or a quick online search would offer you innumerable opinions on the same. Pick a couple of highly rated options and try a few out on the next big project if you have the time to invest. I think getting started in a proper IDE isn’t such a bad shout as with minimal configuration you’d have in-built code-completions, an interactive interpreter to test code snippets, access to a terminal and proper debugging tools to name but a few options. Alternatively you could focus on your writing and do it in a basic text editor. Defo worth looking into a few online suggestions anyway.

It depends on what you’re looking to do. You’ve probably already got most of the tools installed for writing so if you wrote a basic python file in plaintext and wanted to run it you could do in command line with `python myscript`. Any additional modules you might need are often accessible through pip. If you wanted specific datasets and tasks to complete then you may have to look elsewhere for them.