Skip to content

Latest commit

 

History

History
213 lines (173 loc) · 4.85 KB

DESCRIPTIVE_STATS.md

File metadata and controls

213 lines (173 loc) · 4.85 KB
Raw

Outline

R Workspace

## save to the current working directory
save.image()
## just checking what the current working directory is
getwd()
## save to a specific file and location
save.image("C:/mydir/filename.RData")
##list the objects in the current workspace
ls()  
## change to mydir
setwd("C:/mydir")   
setwd("C:\\mydir") #save the data in the local folder, not One Drive

Writing/reading table format

##To write a CSV file for input to Excel 
write.table(x, file = "foo.csv", sep = ",", col.names = NA,
            qmethod = "double")
           
## and to read this file back into R one needs
read.table("foo.csv", header = TRUE, sep = ",", row.names = 1)

### Alternatively
write.csv(x, file = "foo.csv")
read.csv("foo.csv", row.names = 1)

## or without row names
write.csv(x, file = "foo.csv", row.names = FALSE)
read.csv("foo.csv")

Back to Outline

Writing/reading ASCII files

  # Writing
   write.table(DATA,file='DATA.txt') # writes the data to an ASCII file
   list.files(pattern='.txt') # list the files in the current folder having *.txt in the name.
  
  # Reading
   DATA2=read.table('DATA.txt',header=T) # you can add sep="," or sep"\t" for comma and tab-spearated files, respectively
   head(DATA)
   head(DATA2)

Back to Outline

Descriptive Statistics

   summary(DATA$age)
   table(DATA$sex)
   quantile(DATA$age,p=.08)
   isTall<-ifelse(DATA$height>median(DATA$height),">median","<median")
   table(DATA$sex,isTall)

Plots

   barplot(table(DATA$sex))
   hist(DATA$age)
   boxplot(height~sex,data=DATA)
   plot(height~age,data=DATA)
   plot(density(DATA$height))

Back to Outline

Loops

df <- data.frame(
  a = rnorm(10),
  b = rnorm(10),
  c = rnorm(10),
  d = rnorm(10)
)

Compute the maximum of each column.

max(df$a)
max(df$b)
max(df$c)
max(df$d)

Our rule of thumb: never copy and paste more than twice. Instead, we could use a for loop

output <- vector("double", ncol(df))  # 1. output
for (i in seq_along(df)) {            # 2. sequence
  output[[i]] <- max(df[[i]])      # 3. body
}
output

Unknown output length

Sometimes you might not know how long the output will be.

means <- c(0, 1, 2)
output <- double()
for (i in seq_along(means)) {
  n <- sample(100, 1)
  output <- c(output, rnorm(n, means[[i]]))
}
str(output)

But this is not very efficient because in each iteration, R has to copy all the data from the previous iterations. A better solution to save the results in a list, and then combine into a single vector after the loop is done:

out <- vector("list", length(means))
for (i in seq_along(means)) {
  n <- sample(100, 1)
  out[[i]] <- rnorm(n, means[[i]])
}
str(out)
str(unlist(out))

Unknown sequence length

for (i in seq_along(x)) {
  # body
}

# Equivalent to
i <- 1
while (i <= length(x)) {
  # body
  i <- i + 1 
}

Use a while loop to find how many tries it takes to get three sons in a row.

baby <- function() sample(c("D", "S"), 1)

tries <- 0
nsons <- 0

while (nsons < 3) {
  if (baby() == "S") {
    nsons <- nsons + 1
  } else {
    nsons <- 0
  }
  tries <- tries + 1
}
tries

In-class Assignment 0 (Due: Sep 4th 11:59PM; will not be graded)

  1. Create the data frame ‘readmission.df’ with the data provided below:
readmission.df = data.frame( name = c("P0001", "P0002", "P0003", "P0004"),
                         sex = c("f", "f", "m", "m"), 
                        days = c(102,302,31,9)); 
readmission.df

Use a simple ‘ifelse’ statement to add a new column ‘male.30’ to the data frame, which is a boolean column, indicating T if the patient is a male readmitted within 30 days.

ifelse( test, "T","F")
  1. Write a while loop starting with z = 0. The loop prints all numbers up to 20 but it skips numbers 5 and 10.
z<-0
while(z<20){
body
}
  1. Import recid.csv data and create a new column, termed married2, which assigns "Yes" to 1, "No" to 0. Provide the appropriate summary statistics (depending on the data types) of each column.
setwd("C:/mydir")   #or setwd("C:\\mydir")
#save the data in the local folder, not One Drive
recid<-read.csv("recid.csv",header=T)
recid$married2<-ifelse(...)
head(recid)
summary(recid)
  1. Create a pdf report using RMarkdown/knitr. Give the title of the report as "Last_name.First_name.Inclass0.pdf." Then upload both RMD and PDF files in the D2L:Assessments:Assignments:Inclass0.