Move from Excel to Python with Pandas Transcripts
Chapter: Course conclusion and review
Lecture: File structure for Jupyter
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in the next section of the course, we talked about how important it was to have an organized file system.
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Once you start to build out your Jupyter notebooks, I recommend a structure with a base directory and then subdirectories underneath it that it include
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all of your notebook files, keeping those separate from your Excel or CSP or input
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files. Keeping all of your input files in a raw directory underneath data where they can remain untouched so that you can repeat your analysis.
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And then, as you create intermediate files, you can store those in a process directory.
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And then, finally, the Reports directory is where you store your final output.
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We also walk through how to use cookie cutter to make it easier to set this all up so that you wouldn't have to do it by hand.
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After talking about the directory structure, we walk through how to launch your Jupyter notebook,
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and there were a couple of things we discussed about structuring your Jupyter notebooks.
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Make sure that you have a good notebook name at the top so you don't end up with a whole bunch of entitled files.
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Use the markdown text fields to give yourself information so that you can understand the rationale
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for your analysis and understand where the files came from. Then you contract your changes over time as well.
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I encourage you to keep all of your imports at the top of the notebook and then define your input and output files in the beginning as well.
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Finally, when you're all done,