#1.
setwd("C:/Users/James/OneDrive/Desktop/R")
getwd()
## [1] "C:/Users/James/OneDrive/Desktop/R"
#2.
James = read.csv("data_inclass_activity1.csv")
#3.
write.csv(James,file = "New File")
#4.
View(James)
#5.
str(James)
## 'data.frame': 168 obs. of 15 variables:
## $ Grade : chr "3" "4" "5" "6" ...
## $ Year : int 2006 2006 2006 2006 2006 2006 2006 2007 2007 2007 ...
## $ Category : chr "Asian" "Asian" "Asian" "Asian" ...
## $ Number.Tested : int 9768 9973 9852 9606 9433 9593 58225 9750 9881 10111 ...
## $ Mean.Scale.Score: int 700 699 691 682 671 675 687 706 704 700 ...
## $ Level.1.. : int 243 294 369 452 521 671 2550 156 209 211 ...
## $ Level.1...1 : num 2.5 2.9 3.7 4.7 5.5 7 4.4 1.6 2.1 2.1 ...
## $ Level.2.. : int 543 600 907 1176 1698 1847 6771 402 564 626 ...
## $ Level.2...1 : num 5.6 6 9.2 12.2 18 19.3 11.6 4.1 5.7 6.2 ...
## $ Level.3.. : int 4128 4245 4379 4646 4690 4403 26491 3886 3968 4257 ...
## $ Level.3...1 : num 42.3 42.6 44.4 48.4 49.7 45.9 45.5 39.9 40.2 42.1 ...
## $ Level.4.. : int 4854 4834 4197 3332 2524 2672 22413 5306 5140 5017 ...
## $ Level.4...1 : num 49.7 48.5 42.6 34.7 26.8 27.9 38.5 54.4 52 49.6 ...
## $ Level.3.4.. : int 8982 9079 8576 7978 7214 7075 48904 9192 9108 9274 ...
## $ Level.3.4...1 : num 92 91 87 83.1 76.5 73.8 84 94.3 92.2 91.7 ...
#6.
#a.
ncol(James)
## [1] 15
#b.
nrow(James)
## [1] 168
#c.
colnames(James)
## [1] "Grade" "Year" "Category" "Number.Tested"
## [5] "Mean.Scale.Score" "Level.1.." "Level.1...1" "Level.2.."
## [9] "Level.2...1" "Level.3.." "Level.3...1" "Level.4.."
## [13] "Level.4...1" "Level.3.4.." "Level.3.4...1"
rownames(James)
## [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12"
## [13] "13" "14" "15" "16" "17" "18" "19" "20" "21" "22" "23" "24"
## [25] "25" "26" "27" "28" "29" "30" "31" "32" "33" "34" "35" "36"
## [37] "37" "38" "39" "40" "41" "42" "43" "44" "45" "46" "47" "48"
## [49] "49" "50" "51" "52" "53" "54" "55" "56" "57" "58" "59" "60"
## [61] "61" "62" "63" "64" "65" "66" "67" "68" "69" "70" "71" "72"
## [73] "73" "74" "75" "76" "77" "78" "79" "80" "81" "82" "83" "84"
## [85] "85" "86" "87" "88" "89" "90" "91" "92" "93" "94" "95" "96"
## [97] "97" "98" "99" "100" "101" "102" "103" "104" "105" "106" "107" "108"
## [109] "109" "110" "111" "112" "113" "114" "115" "116" "117" "118" "119" "120"
## [121] "121" "122" "123" "124" "125" "126" "127" "128" "129" "130" "131" "132"
## [133] "133" "134" "135" "136" "137" "138" "139" "140" "141" "142" "143" "144"
## [145] "145" "146" "147" "148" "149" "150" "151" "152" "153" "154" "155" "156"
## [157] "157" "158" "159" "160" "161" "162" "163" "164" "165" "166" "167" "168"
#d.
class(James)
## [1] "data.frame"
#e.
anyNA(James)
## [1] FALSE
#f.
str(James$Grade)
## chr [1:168] "3" "4" "5" "6" "7" "8" "All Grades" "3" "4" "5" "6" "7" "8" ...
str(James$Year)
## int [1:168] 2006 2006 2006 2006 2006 2006 2006 2007 2007 2007 ...
str(James$Category)
## chr [1:168] "Asian" "Asian" "Asian" "Asian" "Asian" "Asian" "Asian" ...
str(James$Number.Tested)
## int [1:168] 9768 9973 9852 9606 9433 9593 58225 9750 9881 10111 ...
str(James$Mean.Scale.Score)
## int [1:168] 700 699 691 682 671 675 687 706 704 700 ...
#7.
#a.
colnames(iris)
## [1] "Sepal.Length" "Sepal.Width" "Petal.Length" "Petal.Width" "Species"
#b.
rownames(iris)
## [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12"
## [13] "13" "14" "15" "16" "17" "18" "19" "20" "21" "22" "23" "24"
## [25] "25" "26" "27" "28" "29" "30" "31" "32" "33" "34" "35" "36"
## [37] "37" "38" "39" "40" "41" "42" "43" "44" "45" "46" "47" "48"
## [49] "49" "50" "51" "52" "53" "54" "55" "56" "57" "58" "59" "60"
## [61] "61" "62" "63" "64" "65" "66" "67" "68" "69" "70" "71" "72"
## [73] "73" "74" "75" "76" "77" "78" "79" "80" "81" "82" "83" "84"
## [85] "85" "86" "87" "88" "89" "90" "91" "92" "93" "94" "95" "96"
## [97] "97" "98" "99" "100" "101" "102" "103" "104" "105" "106" "107" "108"
## [109] "109" "110" "111" "112" "113" "114" "115" "116" "117" "118" "119" "120"
## [121] "121" "122" "123" "124" "125" "126" "127" "128" "129" "130" "131" "132"
## [133] "133" "134" "135" "136" "137" "138" "139" "140" "141" "142" "143" "144"
## [145] "145" "146" "147" "148" "149" "150"
#c.
class(iris)
## [1] "data.frame"
#8.
View(iris)
s <- iris
colMeans(subset(s, Species=="virginica", select=-Species), na.rm=TRUE)
## Sepal.Length Sepal.Width Petal.Length Petal.Width
## 6.588 2.974 5.552 2.026
colMeans(subset(s, Species=="versicolor", select=-Species), na.rm=TRUE)
## Sepal.Length Sepal.Width Petal.Length Petal.Width
## 5.936 2.770 4.260 1.326
colMeans(subset(s, Species=="setosa", select=-Species), na.rm=TRUE)
## Sepal.Length Sepal.Width Petal.Length Petal.Width
## 5.006 3.428 1.462 0.246
#9.
f <- function(a,b,c) {q <- a+b; c*q}
f(3,5,23)
## [1] 184
#10.
#a.
area <- function(b,h) {.5*b*h}
#b.
area(5,60)
## [1] 150
#c.
area(2,10)
## [1] 10