Including a CURL package to grab the data from GITHUB link
getData <- getURL('https://raw.githubusercontent.com/vincentarelbundock/Rdatasets/master/csv/datasets/USArrests.csv')
USArrests <- read.csv(text = getData)
USArrests## X Murder Assault UrbanPop Rape
## 1 Alabama 13.2 236 58 21.2
## 2 Alaska 10.0 263 48 44.5
## 3 Arizona 8.1 294 80 31.0
## 4 Arkansas 8.8 190 50 19.5
## 5 California 9.0 276 91 40.6
## 6 Colorado 7.9 204 78 38.7
## 7 Connecticut 3.3 110 77 11.1
## 8 Delaware 5.9 238 72 15.8
## 9 Florida 15.4 335 80 31.9
## 10 Georgia 17.4 211 60 25.8
## 11 Hawaii 5.3 46 83 20.2
## 12 Idaho 2.6 120 54 14.2
## 13 Illinois 10.4 249 83 24.0
## 14 Indiana 7.2 113 65 21.0
## 15 Iowa 2.2 56 57 11.3
## 16 Kansas 6.0 115 66 18.0
## 17 Kentucky 9.7 109 52 16.3
## 18 Louisiana 15.4 249 66 22.2
## 19 Maine 2.1 83 51 7.8
## 20 Maryland 11.3 300 67 27.8
## 21 Massachusetts 4.4 149 85 16.3
## 22 Michigan 12.1 255 74 35.1
## 23 Minnesota 2.7 72 66 14.9
## 24 Mississippi 16.1 259 44 17.1
## 25 Missouri 9.0 178 70 28.2
## 26 Montana 6.0 109 53 16.4
## 27 Nebraska 4.3 102 62 16.5
## 28 Nevada 12.2 252 81 46.0
## 29 New Hampshire 2.1 57 56 9.5
## 30 New Jersey 7.4 159 89 18.8
## 31 New Mexico 11.4 285 70 32.1
## 32 New York 11.1 254 86 26.1
## 33 North Carolina 13.0 337 45 16.1
## 34 North Dakota 0.8 45 44 7.3
## 35 Ohio 7.3 120 75 21.4
## 36 Oklahoma 6.6 151 68 20.0
## 37 Oregon 4.9 159 67 29.3
## 38 Pennsylvania 6.3 106 72 14.9
## 39 Rhode Island 3.4 174 87 8.3
## 40 South Carolina 14.4 279 48 22.5
## 41 South Dakota 3.8 86 45 12.8
## 42 Tennessee 13.2 188 59 26.9
## 43 Texas 12.7 201 80 25.5
## 44 Utah 3.2 120 80 22.9
## 45 Vermont 2.2 48 32 11.2
## 46 Virginia 8.5 156 63 20.7
## 47 Washington 4.0 145 73 26.2
## 48 West Virginia 5.7 81 39 9.3
## 49 Wisconsin 2.6 53 66 10.8
## 50 Wyoming 6.8 161 60 15.6summary(USArrests)## X Murder Assault UrbanPop
## Length:50 Min. : 0.800 Min. : 45.0 Min. :32.00
## Class :character 1st Qu.: 4.075 1st Qu.:109.0 1st Qu.:54.50
## Mode :character Median : 7.250 Median :159.0 Median :66.00
## Mean : 7.788 Mean :170.8 Mean :65.54
## 3rd Qu.:11.250 3rd Qu.:249.0 3rd Qu.:77.75
## Max. :17.400 Max. :337.0 Max. :91.00
## Rape
## Min. : 7.30
## 1st Qu.:15.07
## Median :20.10
## Mean :21.23
## 3rd Qu.:26.18
## Max. :46.00mean(USArrests$Murder)## [1] 7.788median(USArrests$Murder)## [1] 7.25mean(USArrests$Assault)## [1] 170.76median(USArrests$Assault)## [1] 159myDataFrame <- data.frame(USArrests[sample(1:nrow(USArrests), 5), c(1:3)] ) #created a data.frame of USArrest csv, created 5 row and 3 column
names(myDataFrame) <- c("State", "TotalMurderByState", "TotalAssaultByState") #changes the column name of the data frame
row.names(myDataFrame) <- 1:5 # this edit the row name 1 - 5
myDataFrame## State TotalMurderByState TotalAssaultByState
## 1 Missouri 9.0 178
## 2 Massachusetts 4.4 149
## 3 Wyoming 6.8 161
## 4 Maryland 11.3 300
## 5 Florida 15.4 335myDataFrame$theft <- sample(c(1:5), size=5, replace=TRUE) #created a new column name called THEFT and assigned random value between 1 - 5
#the size determine the number of ROW
myDataFrame## State TotalMurderByState TotalAssaultByState theft
## 1 Missouri 9.0 178 3
## 2 Massachusetts 4.4 149 1
## 3 Wyoming 6.8 161 1
## 4 Maryland 11.3 300 3
## 5 Florida 15.4 335 1summary(myDataFrame)## State TotalMurderByState TotalAssaultByState theft
## Length:5 Min. : 4.40 Min. :149.0 Min. :1.0
## Class :character 1st Qu.: 6.80 1st Qu.:161.0 1st Qu.:1.0
## Mode :character Median : 9.00 Median :178.0 Median :1.0
## Mean : 9.38 Mean :224.6 Mean :1.8
## 3rd Qu.:11.30 3rd Qu.:300.0 3rd Qu.:3.0
## Max. :15.40 Max. :335.0 Max. :3.0# mean and median of murder
mean(myDataFrame$TotalMurderByState)## [1] 9.38median(myDataFrame$TotalMurderByState) ## [1] 9#median and median of assault
mean(myDataFrame$TotalAssaultByState)## [1] 224.6median(myDataFrame$TotalAssaultByState) ## [1] 178USArrests <- cbind(USArrests, theft = factor(NA, levels = 1)) # created a column in the existing dataset.
USArrests## X Murder Assault UrbanPop Rape theft
## 1 Alabama 13.2 236 58 21.2 <NA>
## 2 Alaska 10.0 263 48 44.5 <NA>
## 3 Arizona 8.1 294 80 31.0 <NA>
## 4 Arkansas 8.8 190 50 19.5 <NA>
## 5 California 9.0 276 91 40.6 <NA>
## 6 Colorado 7.9 204 78 38.7 <NA>
## 7 Connecticut 3.3 110 77 11.1 <NA>
## 8 Delaware 5.9 238 72 15.8 <NA>
## 9 Florida 15.4 335 80 31.9 <NA>
## 10 Georgia 17.4 211 60 25.8 <NA>
## 11 Hawaii 5.3 46 83 20.2 <NA>
## 12 Idaho 2.6 120 54 14.2 <NA>
## 13 Illinois 10.4 249 83 24.0 <NA>
## 14 Indiana 7.2 113 65 21.0 <NA>
## 15 Iowa 2.2 56 57 11.3 <NA>
## 16 Kansas 6.0 115 66 18.0 <NA>
## 17 Kentucky 9.7 109 52 16.3 <NA>
## 18 Louisiana 15.4 249 66 22.2 <NA>
## 19 Maine 2.1 83 51 7.8 <NA>
## 20 Maryland 11.3 300 67 27.8 <NA>
## 21 Massachusetts 4.4 149 85 16.3 <NA>
## 22 Michigan 12.1 255 74 35.1 <NA>
## 23 Minnesota 2.7 72 66 14.9 <NA>
## 24 Mississippi 16.1 259 44 17.1 <NA>
## 25 Missouri 9.0 178 70 28.2 <NA>
## 26 Montana 6.0 109 53 16.4 <NA>
## 27 Nebraska 4.3 102 62 16.5 <NA>
## 28 Nevada 12.2 252 81 46.0 <NA>
## 29 New Hampshire 2.1 57 56 9.5 <NA>
## 30 New Jersey 7.4 159 89 18.8 <NA>
## 31 New Mexico 11.4 285 70 32.1 <NA>
## 32 New York 11.1 254 86 26.1 <NA>
## 33 North Carolina 13.0 337 45 16.1 <NA>
## 34 North Dakota 0.8 45 44 7.3 <NA>
## 35 Ohio 7.3 120 75 21.4 <NA>
## 36 Oklahoma 6.6 151 68 20.0 <NA>
## 37 Oregon 4.9 159 67 29.3 <NA>
## 38 Pennsylvania 6.3 106 72 14.9 <NA>
## 39 Rhode Island 3.4 174 87 8.3 <NA>
## 40 South Carolina 14.4 279 48 22.5 <NA>
## 41 South Dakota 3.8 86 45 12.8 <NA>
## 42 Tennessee 13.2 188 59 26.9 <NA>
## 43 Texas 12.7 201 80 25.5 <NA>
## 44 Utah 3.2 120 80 22.9 <NA>
## 45 Vermont 2.2 48 32 11.2 <NA>
## 46 Virginia 8.5 156 63 20.7 <NA>
## 47 Washington 4.0 145 73 26.2 <NA>
## 48 West Virginia 5.7 81 39 9.3 <NA>
## 49 Wisconsin 2.6 53 66 10.8 <NA>
## 50 Wyoming 6.8 161 60 15.6 <NA>head(USArrests, 20)## X Murder Assault UrbanPop Rape theft
## 1 Alabama 13.2 236 58 21.2 <NA>
## 2 Alaska 10.0 263 48 44.5 <NA>
## 3 Arizona 8.1 294 80 31.0 <NA>
## 4 Arkansas 8.8 190 50 19.5 <NA>
## 5 California 9.0 276 91 40.6 <NA>
## 6 Colorado 7.9 204 78 38.7 <NA>
## 7 Connecticut 3.3 110 77 11.1 <NA>
## 8 Delaware 5.9 238 72 15.8 <NA>
## 9 Florida 15.4 335 80 31.9 <NA>
## 10 Georgia 17.4 211 60 25.8 <NA>
## 11 Hawaii 5.3 46 83 20.2 <NA>
## 12 Idaho 2.6 120 54 14.2 <NA>
## 13 Illinois 10.4 249 83 24.0 <NA>
## 14 Indiana 7.2 113 65 21.0 <NA>
## 15 Iowa 2.2 56 57 11.3 <NA>
## 16 Kansas 6.0 115 66 18.0 <NA>
## 17 Kentucky 9.7 109 52 16.3 <NA>
## 18 Louisiana 15.4 249 66 22.2 <NA>
## 19 Maine 2.1 83 51 7.8 <NA>
## 20 Maryland 11.3 300 67 27.8 <NA>Bonus: I have used the original csv from the github and read the files from the link.