R代码自动化

Question

我在做PCA。下面是同样的代码-

### 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")

我在这里展示了一个国家，我已经为9个国家做了这件事。对于每个国家/地区，我都必须运行此代码。我相信一定有更简单的方法来自动化这段代码。请推荐!！谢谢！！