Statistical Process Control in Python

Summary

Statistical Process Control in Python Figure 2.1: Statistical Process Control! In this workshop, we will learn how to perform statistical process control in Python, using statistical tools and plotnine visualizations! Statistical Process Control refers to using statistics to (1) measure variation in product quality over time and (2) identify benchmarks to know when intervention is needed. Let’s get started! Getting Started Packages # Remember to install these packages using a terminal, if you haven't already! !pip install pandas plotnine scipy We’ll be using pandas for data manipulation, plotnine for visualization, and scipy for statistical functions. import pandas as pd from plotnine import * Custom Functions This workshop uses custom functions from the functions/ directory. You may need both: - functions_distributions.py - for reliability and distribution functions - functions_process_control.py - for statistical process control functions To use these functions, you need to acquire them from the repository at github.com/timothyfraser/sigma/tree/main/functions. Add the functions directory to your Python path import sys import os # Add the functions directory to Python path sys.path.append('functions') # or path to wherever you placed the functions folder Once you have the functions available, you can import them: from functions_distributions import density, tidy_density, approxfun # from functions_process_control import ggprocess, ggsubgroup, ggmoving, ggcapability # if needed Our Case For today’s workshop, we’re going to think about why quality control matters in a local economy, by examining the case of the Japanese Hot Springs bath economy! Hot springs, or onsen, are a major source of tourism and recreation for families in Japan, bringing residents from across the country every year to often rural communities where the right geological conditions have brought on naturally occurring hot springs. Restaurants, taxi and bus companies, and many service sector firms r...