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data_analysis_pipeline_practice's Introduction

Building a Data Analysis pipeline tutorial

adapted from Software Carpentry

This example data analysis project analyzes the word count for all words in 4 novels. It reports the top 10 most occurring words in each book in a report.

Current usage:

  1. Clone this repo, and using the command line, navigate to the root of this project.

  2. Run the following commands:

bash runall.sh

Exercise:

Your task is to add a "smarter" data analysis pipeline using GNU Make! It should accomplish the same task as bash runall.sh when you type make all.

It should reset the analysis the starting point (the state when you first copied this repo) when you type make clean.

Depenedencies

  • Python & Python libraries:
    • matplotlib
    • numpy
    • sys
    • click
    • collections
    • wordcount
    • jupyter
    • jupyter book

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