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Exercise 7 #12

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Exercise 7
psharma-gif Nov 4, 2022
6b37b1b
added dataframe in q.2 (b)
psharma-gif Nov 4, 2022
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13 changes: 13 additions & 0 deletions Exercise07.Rproj
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Version: 1.0

RestoreWorkspace: Default
SaveWorkspace: Default
AlwaysSaveHistory: Default

EnableCodeIndexing: Yes
UseSpacesForTab: Yes
NumSpacesForTab: 2
Encoding: UTF-8

RnwWeave: Sweave
LaTeX: pdfLaTeX
35 changes: 35 additions & 0 deletions Sharma_R assignment_IntrotoBiometric.R
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#get working directory
getwd()
#set working directory
setwd("/Users/pujasharma/Documents/Exercise07")
#load csv file iris.csv
iris_data <- read.csv(file = "iris.csv", sep = ",", header = T)
#Write R code that will convert the comma-delimited iris.csv file
#to a tab-delimited version names iris.txt.
iris_tab_delimeted <- read.csv(file = "iris.csv", sep = "", header = T)
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@qtran4 qtran4 Nov 7, 2022

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you don't need this line

write.table(iris_data, "iris.txt", row.names = F,sep = "\t",)
#2. Provide R code that creates a list of length 5.

#**Ans**
a <- c(100,200,300,400,500,600,700,800,900,1000)
#or
a <- seq(from=100,to=1000,by=100)
a #a vector with length 10 containing 100, 200, . . . , 1000

b <- matrix(data = c("Standford","NotreDame",24,40), nrow = 2,ncol = 2, byrow=F)
data.frame(b)
#b two-row, two-column data frame with the team names and final score
#from last week’s Notre Dame football game

c <- 999
c #the number 999

d <- matrix(data=seq(1:50), nrow = 10, ncol = 5, byrow=T)
d #a 10-row, 5-column matrix containing integers from 1 to 50
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@qtran4 qtran4 Nov 7, 2022

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you don't need the byrow argument


e <- c("p","q","r")#a vector containing three letters.
e#a vector containing three letters.

list(a,b,c,d,e)
#####################

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+2

151 changes: 151 additions & 0 deletions iris.txt
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"Sepal.Length" "Sepal.Width" "Petal.Length" "Petal.Width" "Species"
5.1 3.5 1.4 0.2 "setosa"
4.9 3 1.4 0.2 "setosa"
4.7 3.2 1.3 0.2 "setosa"
4.6 3.1 1.5 0.2 "setosa"
5 3.6 1.4 0.2 "setosa"
5.4 3.9 1.7 0.4 "setosa"
4.6 3.4 1.4 0.3 "setosa"
5 3.4 1.5 0.2 "setosa"
4.4 2.9 1.4 0.2 "setosa"
4.9 3.1 1.5 0.1 "setosa"
5.4 3.7 1.5 0.2 "setosa"
4.8 3.4 1.6 0.2 "setosa"
4.8 3 1.4 0.1 "setosa"
4.3 3 1.1 0.1 "setosa"
5.8 4 1.2 0.2 "setosa"
5.7 4.4 1.5 0.4 "setosa"
5.4 3.9 1.3 0.4 "setosa"
5.1 3.5 1.4 0.3 "setosa"
5.7 3.8 1.7 0.3 "setosa"
5.1 3.8 1.5 0.3 "setosa"
5.4 3.4 1.7 0.2 "setosa"
5.1 3.7 1.5 0.4 "setosa"
4.6 3.6 1 0.2 "setosa"
5.1 3.3 1.7 0.5 "setosa"
4.8 3.4 1.9 0.2 "setosa"
5 3 1.6 0.2 "setosa"
5 3.4 1.6 0.4 "setosa"
5.2 3.5 1.5 0.2 "setosa"
5.2 3.4 1.4 0.2 "setosa"
4.7 3.2 1.6 0.2 "setosa"
4.8 3.1 1.6 0.2 "setosa"
5.4 3.4 1.5 0.4 "setosa"
5.2 4.1 1.5 0.1 "setosa"
5.5 4.2 1.4 0.2 "setosa"
4.9 3.1 1.5 0.2 "setosa"
5 3.2 1.2 0.2 "setosa"
5.5 3.5 1.3 0.2 "setosa"
4.9 3.6 1.4 0.1 "setosa"
4.4 3 1.3 0.2 "setosa"
5.1 3.4 1.5 0.2 "setosa"
5 3.5 1.3 0.3 "setosa"
4.5 2.3 1.3 0.3 "setosa"
4.4 3.2 1.3 0.2 "setosa"
5 3.5 1.6 0.6 "setosa"
5.1 3.8 1.9 0.4 "setosa"
4.8 3 1.4 0.3 "setosa"
5.1 3.8 1.6 0.2 "setosa"
4.6 3.2 1.4 0.2 "setosa"
5.3 3.7 1.5 0.2 "setosa"
5 3.3 1.4 0.2 "setosa"
7 3.2 4.7 1.4 "versicolor"
6.4 3.2 4.5 1.5 "versicolor"
6.9 3.1 4.9 1.5 "versicolor"
5.5 2.3 4 1.3 "versicolor"
6.5 2.8 4.6 1.5 "versicolor"
5.7 2.8 4.5 1.3 "versicolor"
6.3 3.3 4.7 1.6 "versicolor"
4.9 2.4 3.3 1 "versicolor"
6.6 2.9 4.6 1.3 "versicolor"
5.2 2.7 3.9 1.4 "versicolor"
5 2 3.5 1 "versicolor"
5.9 3 4.2 1.5 "versicolor"
6 2.2 4 1 "versicolor"
6.1 2.9 4.7 1.4 "versicolor"
5.6 2.9 3.6 1.3 "versicolor"
6.7 3.1 4.4 1.4 "versicolor"
5.6 3 4.5 1.5 "versicolor"
5.8 2.7 4.1 1 "versicolor"
6.2 2.2 4.5 1.5 "versicolor"
5.6 2.5 3.9 1.1 "versicolor"
5.9 3.2 4.8 1.8 "versicolor"
6.1 2.8 4 1.3 "versicolor"
6.3 2.5 4.9 1.5 "versicolor"
6.1 2.8 4.7 1.2 "versicolor"
6.4 2.9 4.3 1.3 "versicolor"
6.6 3 4.4 1.4 "versicolor"
6.8 2.8 4.8 1.4 "versicolor"
6.7 3 5 1.7 "versicolor"
6 2.9 4.5 1.5 "versicolor"
5.7 2.6 3.5 1 "versicolor"
5.5 2.4 3.8 1.1 "versicolor"
5.5 2.4 3.7 1 "versicolor"
5.8 2.7 3.9 1.2 "versicolor"
6 2.7 5.1 1.6 "versicolor"
5.4 3 4.5 1.5 "versicolor"
6 3.4 4.5 1.6 "versicolor"
6.7 3.1 4.7 1.5 "versicolor"
6.3 2.3 4.4 1.3 "versicolor"
5.6 3 4.1 1.3 "versicolor"
5.5 2.5 4 1.3 "versicolor"
5.5 2.6 4.4 1.2 "versicolor"
6.1 3 4.6 1.4 "versicolor"
5.8 2.6 4 1.2 "versicolor"
5 2.3 3.3 1 "versicolor"
5.6 2.7 4.2 1.3 "versicolor"
5.7 3 4.2 1.2 "versicolor"
5.7 2.9 4.2 1.3 "versicolor"
6.2 2.9 4.3 1.3 "versicolor"
5.1 2.5 3 1.1 "versicolor"
5.7 2.8 4.1 1.3 "versicolor"
6.3 3.3 6 2.5 "virginica"
5.8 2.7 5.1 1.9 "virginica"
7.1 3 5.9 2.1 "virginica"
6.3 2.9 5.6 1.8 "virginica"
6.5 3 5.8 2.2 "virginica"
7.6 3 6.6 2.1 "virginica"
4.9 2.5 4.5 1.7 "virginica"
7.3 2.9 6.3 1.8 "virginica"
6.7 2.5 5.8 1.8 "virginica"
7.2 3.6 6.1 2.5 "virginica"
6.5 3.2 5.1 2 "virginica"
6.4 2.7 5.3 1.9 "virginica"
6.8 3 5.5 2.1 "virginica"
5.7 2.5 5 2 "virginica"
5.8 2.8 5.1 2.4 "virginica"
6.4 3.2 5.3 2.3 "virginica"
6.5 3 5.5 1.8 "virginica"
7.7 3.8 6.7 2.2 "virginica"
7.7 2.6 6.9 2.3 "virginica"
6 2.2 5 1.5 "virginica"
6.9 3.2 5.7 2.3 "virginica"
5.6 2.8 4.9 2 "virginica"
7.7 2.8 6.7 2 "virginica"
6.3 2.7 4.9 1.8 "virginica"
6.7 3.3 5.7 2.1 "virginica"
7.2 3.2 6 1.8 "virginica"
6.2 2.8 4.8 1.8 "virginica"
6.1 3 4.9 1.8 "virginica"
6.4 2.8 5.6 2.1 "virginica"
7.2 3 5.8 1.6 "virginica"
7.4 2.8 6.1 1.9 "virginica"
7.9 3.8 6.4 2 "virginica"
6.4 2.8 5.6 2.2 "virginica"
6.3 2.8 5.1 1.5 "virginica"
6.1 2.6 5.6 1.4 "virginica"
7.7 3 6.1 2.3 "virginica"
6.3 3.4 5.6 2.4 "virginica"
6.4 3.1 5.5 1.8 "virginica"
6 3 4.8 1.8 "virginica"
6.9 3.1 5.4 2.1 "virginica"
6.7 3.1 5.6 2.4 "virginica"
6.9 3.1 5.1 2.3 "virginica"
5.8 2.7 5.1 1.9 "virginica"
6.8 3.2 5.9 2.3 "virginica"
6.7 3.3 5.7 2.5 "virginica"
6.7 3 5.2 2.3 "virginica"
6.3 2.5 5 1.9 "virginica"
6.5 3 5.2 2 "virginica"
6.2 3.4 5.4 2.3 "virginica"
5.9 3 5.1 1.8 "virginica"