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Python Code Snippets

After some rather intensive courses, one of which was all about coding in Python - using Jupyter notebooks, I kind of got hooked. I continued doing some Python coding because it was, well. fun! If that makes me a geek, so be it. In the end, I wrote several little Python functions that did a lot of what my professor had been asking us to do during the semester, but did it in a much easier way (at least for anyone else who is using the functions). I have uploaded a couple of them here. If you find them at all useful, feel free to credit me. On the other hand, if you find they need reworking, I am also happy to hear about it. Contact me if you have suggestions or problems or want to talk about Pythonic issues!

CAVEAT: I have not gotten all this correct yet - but it is mostly there. Feel free to use and abuse...
The following code was tested on a Jupyter notebook (Anaconda version), and this cleansed version of the Titanic dataset.

Now for the code ...
NOTE on Code: in order to download the code:

1. Navigate to this page and the code links on it
2. Left click on the link you wish to download
3. Click the down arrow icon at the top right of the resulting page
4. If you let your mouse hover over the down arrow icon, it should say "download raw file"
5. Once you have clicked the download button, the file should be automatically downloaded onto your computer - check your downloads folder
6. ALTERNATELY, skip steps 2 - 5 and right-click on the file, choose "Save link as", find the file in your downloads folder

Jupyter notebooks (.ipynb files)

• Train, fit and evaluate different models
• Run other Jupyter notebooks and put resultant timings in Python dictionary

Python code (.py files)

• Create a scatter plot of the cleansed titanic dataset linked to above
• Python version of train, fit, and evaluate function - you can just use the import command and the name of the file
• Python version of the run other notebook and store timings file
• Function to read a file into python/jupyter notebook environment
• Read file and create a correlation matrix and a correlation plot
• Read file like above, but use an internal function call
• Plot the survival rate for passengers on the titanic