I am not sure if this does everything you want. Note at the bottom is an example of getting a summary of the Min_A qcc result.
library(tidyverse)
#> Warning: package 'tibble' was built under R version 4.1.2
library(qcc)
#> Warning: package 'qcc' was built under R version 4.1.2
#> Package 'qcc' version 2.7
#> Type 'citation("qcc")' for citing this R package in publications.
mydata <- read.csv("~/R/Play/Dummy.csv", header=TRUE)
CpFunc <- function(vec){
qccOut <- qcc(mydata[[vec]], type="xbar.one",title=vec)
ProcessCap <- process.capability(qccOut, spec.limits=c(0.2,0.5))
return(list(qcc=qccOut,Process=ProcessCap))
}
Nms <- colnames(mydata)[1:4]
CpList <- map(Nms,CpFunc)


#>
#> Process Capability Analysis
#>
#> Call:
#> process.capability(object = qccOut, spec.limits = c(0.2, 0.5))
#>
#> Number of obs = 67 Target = 0.35
#> Center = 0.2794 LSL = 0.2
#> StdDev = 0.02216 USL = 0.5
#>
#> Capability indices:
#>
#> Value 2.5% 97.5%
#> Cp 2.2560 1.8717 2.640
#> Cp_l 1.1942 1.0106 1.378
#> Cp_u 3.3178 2.8381 3.797
#> Cp_k 1.1942 0.9754 1.413
#> Cpm 0.6757 0.5182 0.833
#>
#> Exp<LSL 0.017% Obs<LSL 0%
#> Exp>USL 0% Obs>USL 0%


#>
#> Process Capability Analysis
#>
#> Call:
#> process.capability(object = qccOut, spec.limits = c(0.2, 0.5))
#>
#> Number of obs = 67 Target = 0.35
#> Center = 0.3975 LSL = 0.2
#> StdDev = 0.0227 USL = 0.5
#>
#> Capability indices:
#>
#> Value 2.5% 97.5%
#> Cp 2.2026 1.8274 2.577
#> Cp_l 2.8995 2.4791 3.320
#> Cp_u 1.5057 1.2799 1.731
#> Cp_k 1.5057 1.2367 1.775
#> Cpm 0.9504 0.7344 1.166
#>
#> Exp<LSL 0% Obs<LSL 0%
#> Exp>USL 0% Obs>USL 0%


#>
#> Process Capability Analysis
#>
#> Call:
#> process.capability(object = qccOut, spec.limits = c(0.2, 0.5))
#>
#> Number of obs = 67 Target = 0.35
#> Center = 0.2991 LSL = 0.2
#> StdDev = 0.01625 USL = 0.5
#>
#> Capability indices:
#>
#> Value 2.5% 97.5%
#> Cp 3.0764 2.5524 3.599
#> Cp_l 2.0325 1.7339 2.331
#> Cp_u 4.1202 3.5265 4.714
#> Cp_k 2.0325 1.6767 2.388
#> Cpm 0.9358 0.7178 1.153
#>
#> Exp<LSL 0% Obs<LSL 0%
#> Exp>USL 0% Obs>USL 0%


#>
#> Process Capability Analysis
#>
#> Call:
#> process.capability(object = qccOut, spec.limits = c(0.2, 0.5))
#>
#> Number of obs = 67 Target = 0.35
#> Center = 0.3813 LSL = 0.2
#> StdDev = 0.01786 USL = 0.5
#>
#> Capability indices:
#>
#> Value 2.5% 97.5%
#> Cp 2.799 2.322 3.275
#> Cp_l 3.384 2.895 3.873
#> Cp_u 2.214 1.890 2.538
#> Cp_k 2.214 1.828 2.600
#> Cpm 1.386 1.076 1.695
#>
#> Exp<LSL 0% Obs<LSL 0%
#> Exp>USL 0% Obs>USL 0%
names(CpList) <- Nms
summary(CpList$Min_A$qcc)
#>
#> Call:
#> qcc(data = mydata[[vec]], type = "xbar.one", title = vec)
#>
#> xbar.one chart for mydata[[vec]]
#>
#> Summary of group statistics:
#> Min. 1st Qu. Median Mean 3rd Qu. Max.
#> 0.210000 0.260000 0.280000 0.279403 0.300000 0.340000
#>
#> Group sample size: 1
#> Number of groups: 67
#> Center of group statistics: 0.279403
#> Standard deviation: 0.02216312
#>
#> Control limits:
#> LCL UCL
#> 0.2129136 0.3458923
Created on 2022-02-28 by the reprex package (v2.0.1)