Stata and R

gistfile1.txt

# 1) Stata command:
use growth_and_uptake_assumptions.dta

# Corresponding R command: 
load(file="my_data.RData")
attach(my_data)

# ------------------------------------------------

# 2) Stata command:
sort year

# Corresponding R command: 
my_order <- order(my_data$year)
# my_order will have the sorted index for "year"
# my_data[my_order, ] would show sorted values

# ------------------------------------------------

# 3) Stata command:
keep year *_trend

# Corresponding R command: 
my_new_data <- my_data[, 1:4]  # only keep the first 4 columns

# ------------------------------------------------

# 4) Stata command:
gen id = 1

# Corresponding R command: 
id <- 1

# ------------------------------------------------

# 5) Stata command:
reshape wide *_trend, i(id) j(year)

# Corresponding R command: 
attach(my_data)
install.packages("reshape")
library("reshape")
my_wide <- cast(my_data, wide + *_trend ~ id + year)

# ------------------------------------------------

# 6) Stata command:
merge category year using dumping_rate_append.dta

# Corresponding R command: 
my_data2 <- merge(mydata,my_data1, by=c("category","year") )	# second data is loaded as my_data1

# ------------------------------------------------

# 7) Stata command:
replace rate = 0 if category== "D" | category == "E"

# Corresponding R command: 
rate[category=="D" |category == "E"] = 0

# ------------------------------------------------

# 8) Stata command:
insheet using $dirprm/prmBasetrend_ByCvT_ByYear.txt, tab   

# Corresponding R command:
my_data <- read.csv(file="simple.csv",head=TRUE,sep="\t")


# ------------------------------------------------

# 9) Stata command:
clear

# Corresponding R command:
rm(list = ls())

# ------------------------------------------------

# 10) Stata command:
??

# Corresponding R command:
memory.limit(size=3000) # SET MEMORY TO USE