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Copy pathimporting from SAS STATA SPSS.R
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importing from SAS STATA SPSS.R
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#haven is an extremely easy-to-use package to import data from three software packages: SAS, STATA and SPSS. Depending on the software, you use different functions:
# SAS: read_sas()
# STATA: read_dta() (or read_stata(), which are identical)
# SPSS: read_sav() or read_por(), depending on the file type.
# Load the haven package
library(haven)
# Import sales.sas7bdat: sales
sales = read_sas("sales.sas7bdat")
# Display the structure of sales
str(sales)
# haven is already loaded
# Import the data from the URL: sugar
sugar <- read_dta("http://assets.datacamp.com/production/course_1478/datasets/trade.dta")
# Structure of sugar
str(sugar)
# Convert values in Date column to dates
sugar$Date <- as.Date(as_factor(sugar$Date))
# Structure of sugar again
str(sugar)
#The haven package can also import data files from SPSS. Again, importing the data is pretty straightforward. Depending on the SPSS data file you're working with, you'll need either read_sav() - for .sav files - or read_por() - for .por files.
# haven is already loaded
# Import person.sav: traits
traits <- read_sav("person.sav")
# Summarize traits
summary(traits)
# Print out a subset
subset(traits,Extroversion > 40 & Agreeableness > 40)
# haven is already loaded
# Import SPSS data from the URL: work
work <- read_sav("http://s3.amazonaws.com/assets.datacamp.com/production/course_1478/datasets/employee.sav")
# Display summary of work$GENDER
summary(work$GENDER)
# Convert work$GENDER to a factor
work$GENDER <- as_factor(work$GENDER)
# Display summary of work$GENDER again
summary(work$GENDER)
#The foreign package offers a simple function to import and read STATA data: read.dta().
# Load the foreign package
library(foreign)
# Import florida.dta and name the resulting data frame florida
florida <- read.dta("florida.dta")
# Check tail() of florida
tail(florida,6)
# foreign is already loaded
# Specify the file path using file.path(): path
path <- file.path("worldbank","edequality.dta")
# Create and print structure of edu_equal_1
edu_equal_1 <- read.dta(path)
str(edu_equal_1)
# Create and print structure of edu_equal_2
edu_equal_2 <- read.dta(path,convert.factors = F)
str(edu_equal_2)
# Create and print structure of edu_equal_3
edu_equal_3 <- read.dta(path,convert.underscore = T)
str(edu_equal_3)
# foreign is already loaded
# Import international.sav as a data frame: demo
demo <- read.spss("international.sav",to.data.frame = T)
# Create boxplot of gdp variable of demo
boxplot(demo$gdp)
# foreign is already loaded
# Import international.sav as demo_1
demo_1 <- read.spss("international.sav",to.data.frame = T)
# Print out the head of demo_1
head(demo_1)
# Import international.sav as demo_2
demo_2 <- read.spss("international.sav",to.data.frame = T, use.value.labels = F)
# Print out the head of demo_2
head(demo_2)