Plan out workshop #1
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…gement and logging
files with logging and progress tracking
…name prefix and adds error handling for missing files
…ames and adds progress bar functionality
…pping data, including data cleaning, merge validation, and interim output saving
…APPT_STATUS for improved data quality
… data, including pivoting and monthly summaries
…ns of functions for pivoting and summarizing practice-level appointment data
…appointments and attendance rates
…d violin plots, with functionality to save plots and batch processing for multiple summaries
…g data reading, processing, aggregation, and plotting with optional interim output saving
…dropping for testing purposes
…category and updating total appointment calculations
…e and remove the zip after extraction
…ieval capabilities
…rates download functionality in the main pipeline
…om version control
…unctions; updates configuration file description and removes unused import in data_in.py
…mprove test coverage
…and ensure accuracy of appointment metrics
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This pull request shows the development process I followed to create this example pandas pipeline. Currently the pipeline aggregates the data in a number of different ways and creates some plots of that data.
There are no tests yet as of writing, but adding them is on the list as it is important to demo