X-bar and R Control Limits Python Script Generator

import csv
import statistics

N = 5
A2 = 0.577
D3 = 0
D4 = 2.114
D2 = 2.326
USL = 25.05
LSL = 24.95

values = []
with open("bore_diameter.csv", newline="") as f:
    for row in csv.DictReader(f):
        values.append(float(row["diameter"]))

# Split into consecutive subgroups of size N, drop the incomplete tail
groups = [values[i:i + N] for i in range(0, len(values) - N + 1, N)]
means = [statistics.mean(g) for g in groups]
ranges = [max(g) - min(g) for g in groups]

grand_mean = statistics.mean(means)
r_bar = statistics.mean(ranges)

print("Subgroups:", len(groups))
print("X-bar chart: CL=%.4f UCL=%.4f LCL=%.4f" % (grand_mean, grand_mean + A2 * r_bar, grand_mean - A2 * r_bar))
print("R chart: CL=%.4f UCL=%.4f LCL=%.4f" % (r_bar, D4 * r_bar, D3 * r_bar))

# Out of control points (rule 1 only)
for i, (m, r) in enumerate(zip(means, ranges), start=1):
    if m > grand_mean + A2 * r_bar or m < grand_mean - A2 * r_bar:
        print("Subgroup %d mean out of limits: %.4f" % (i, m))
    if r > D4 * r_bar or r < D3 * r_bar:
        print("Subgroup %d range out of limits: %.4f" % (i, r))

sigma_within = r_bar / D2
sigma_overall = statistics.stdev(values)

cp = (USL - LSL) / (6 * sigma_within)
cpk = min(USL - grand_mean, grand_mean - LSL) / (3 * sigma_within)
pp = (USL - LSL) / (6 * sigma_overall)
ppk = min(USL - grand_mean, grand_mean - LSL) / (3 * sigma_overall)

print("Cp=%.2f Cpk=%.2f Pp=%.2f Ppk=%.2f" % (cp, cpk, pp, ppk))