R code automation - r

Question

I am doing PCA. Here is the code for the same-
### Read .csv file #####
data<-read.csv(file.choose(),header=T,sep=",")
names(data)
data$qcountry
#### for the country-ARGENTINA#######
ar_data<-data[which(data$qcountry=="ar"),]
ar_data$qcountry<-NULL
names(ar_data)
names(ar_data)<-c("01_insufficient_efficacy","02_safety_issues","03_inconvenient_dosage_regimen","04_price_issues"
,"05_not_reimbursed","06_not_inculed_govt","07_insuficient_clinicaldata","08_previously_used","09_prescription_opted_for_some_patients","10_scientific_info_NA","12_involved_in_diff_clinical_trial"
,"13_patient_inappropriate_for_TT","14_patient_inappropriate_Erb","16_patient_over_65","17_Erbitux_alternative","95_Others")
names(ar_data)
ar_data_wdt_zero_columns<-ar_data[, colSums(ar_data != 0) > 0]
####Testing multicollinearity####
vif(ar_data_wdt_zero_columns)
#### Testing appropriatness of PCA ####
KMO(ar_data_wdt_zero_columns)
cortest.bartlett(ar_data_wdt_zero_columns)
#### Run PCA ####
pca<-prcomp(ar_data_wdt_zero_columns,center=F,scale=F)
summary(pca)
#### Compute the loadings for deciding the top4 most correlated variables###
load<-pca$rotation
write.csv(load,"loadings_argentina_2015_Q4.csv")
I have shown here for the one country, I have done this for 9countries. For each country I have to run this code. I am sure there must be easier way to automate this code. Please suggest !!
Thanks!!

Answer 1

Yes, this is doable for every country. You can make your custom function which takes appropriate parameters, e.g. country name and data. You do the magic inside and return an appropriate object (or not). Pass this magic to a processed data which you import and make pretty only once. The below code is not tested but should get you started.
A few comments.
Don't use file.choose() as it breaks your code 3 days down the line. How do you know what file to choose? Why click every time you run the script when you can make the script work for you? Be lazy in that sense.
You have a lot of clutter in your script. Adhere to some style and don't leave in random lines you try out for "shits and giggles". Use spaces in your code, at least.
Be more imaginative in choose object names. Try the name out first if perhaps the object already exists in a form of a base function, e.g. load.
myPCA <- function(my.country, my.data) {
ar_data <- data[data$qcountry %in% "ar", ]
ar_data$qcountry <- NULL
ar_data_wdt_zero_columns <- ar_data[, colSums(ar_data != 0) > 0]
#### Run PCA ####
pca <- prcomp(ar_data_wdt_zero_columns, center = FALSE, scale = FALSE)
#### Compute the loadings for deciding the top4 most correlated variables###
write.csv(pca$rotation, paste("loadings_", my.country, ".csv", sep = "")) # may need tweaking
return(list(pca = pca, vif = vif(ar_data_wdt_zero_columns),
kmo = KMO(ar_data_wdt_zero_columns), correlation = cortest.bartlett(ar_data_wdt_zero_columns))
}
data <- read.csv("relative_link_to_file", header = TRUE, sep = ",")
names(data) <- c("01_insufficient_efficacy","02_safety_issues","03_inconvenient_dosage_regimen","04_price_issues"
,"05_not_reimbursed","06_not_inculed_govt","07_insuficient_clinicaldata","08_previously_used","09_prescription_opted_for_some_patients","10_scientific_info_NA","12_involved_in_diff_clinical_trial"
,"13_patient_inappropriate_for_TT","14_patient_inappropriate_Erb","16_patient_over_65","17_Erbitux_alternative","95_Others")
sapply(data$qcountry, FUN = myPCA)