We’ll use one of the default datasets in R which is mtcars. Before starting, let’s create a data including everything inside mtcars.
data <- mtcars1.3.1 Use logical operators to output only those rows of data where column mpg is between 15 and 20(excluding 15 and 20).
data[data$mpg > 15 & data$mpg < 20,]## mpg cyl disp hp drat wt qsec vs am gear carb
## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
## Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
## Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
## AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
## Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
## Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 61.3.2 Use logical operators to output only those rows of data where column cyl is equal to 6 and column am is not 0.
data[data$cyl == 6 & data$am != 0,]## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
## Ferrari Dino 19.7 6 145 175 3.62 2.770 15.50 0 1 5 61.3.3 Use logical operators to output only those rows of data where column gear or carb has the value 4.
data[data$gear == 4 | data$carb == 4,]## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
## Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
## Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
## Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
## Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
## Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
## Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
## Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 21.3.4 Use logical operators to output only the even rows of data.
## odd columns or odd rows
## calld[ c(TRUE,FALSE), ] odd rows
## calld[ , c(TRUE,FALSE) ] odd columns
## calld[ !c(TRUE,FALSE), ] even rows
## calld[ , !c(TRUE,FALSE) ] even columns
## calld[ , c(TRUE,FALSE, FALSE) ] columns 1,4,7 , ....
data[!c(TRUE,FALSE),]## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
## Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
## Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
## Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
## Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
## Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
## Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
## Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 21.3.5 Use logical operators and change every fourth element in column mpg to 0.
data$mpg[c(FALSE, FALSE, FALSE, TRUE)] <- 0
data$mpg## [1] 21.0 21.0 22.8 0.0 18.7 18.1 14.3 0.0 22.8 19.2 17.8 0.0 17.3 15.2
## [15] 10.4 0.0 14.7 32.4 30.4 0.0 21.5 15.5 15.2 0.0 19.2 27.3 26.0 0.0
## [29] 15.8 19.7 15.0 0.01.3.6 Output only those rows of data where columns vs and am have the same value 1, solve this without using == operator.
## When you do not use the operator ==, argument gives the values that are different than 0.
data[(data$vs & data$am),]## mpg cyl disp hp drat wt qsec vs am gear carb
## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
## Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
## Toyota Corolla 0.0 4 71.1 65 4.22 1.835 19.90 1 1 4 1
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
## Lotus Europa 0.0 4 95.1 113 3.77 1.513 16.90 1 1 5 2
## Volvo 142E 0.0 4 121.0 109 4.11 2.780 18.60 1 1 4 21.3.7 (TRUE + TRUE) * FALSE , what does this expression evaluate to and why?
# TRUE = 1 & FALSE = 0. So, do the math seniorita.
(TRUE + TRUE) * FALSE## [1] 01.3.8 Output only those rows of data where at least vs or am have the value 1, solve this without using == or !=.
## remember 1.3.4
data[(data$vs | data$am),]## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 0.0 6 258.0 110 3.08 3.215 19.44 1 0 3 1
## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
## Merc 240D 0.0 4 146.7 62 3.69 3.190 20.00 1 0 4 2
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
## Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
## Toyota Corolla 0.0 4 71.1 65 4.22 1.835 19.90 1 1 4 1
## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
## Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
## Lotus Europa 0.0 4 95.1 113 3.77 1.513 16.90 1 1 5 2
## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
## Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
## Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
## Volvo 142E 0.0 4 121.0 109 4.11 2.780 18.60 1 1 4 21.3.9 Explain the difference between | , || , & and &&.
## Simple explanation and example from Aaron on stackoverflow: Single ones are vectorized meaning that they can return a vector.
((-2:2) >= 0) & ((-2:2) <= 0)## [1] FALSE FALSE TRUE FALSE FALSE# [1] FALSE FALSE TRUE FALSE FALSE
((-2:2) >= 0) && ((-2:2) <= 0)## [1] FALSE# [1] FALSE1.3.10 Change all values that are 0 in the column am in data to 2.
data$am[data$am == 0] <- 2
data$am## [1] 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 2 2 2 2 2 1 1 1 1 1 1 11.3.11 Add 2 to every element in the column vs without using numbers.
## Without using numbers? Shit :D
data$vs## [1] 0 0 1 1 0 1 0 1 1 1 1 0 0 0 0 0 0 1 1 1 1 0 0 0 0 1 0 1 0 0 0 1data$vs <- data$vs + 2
data$vs## [1] 2 2 3 3 2 3 2 3 3 3 3 2 2 2 2 2 2 3 3 3 3 2 2 2 2 3 2 3 2 2 2 31.3.12 Output only those rows of data where vs and am have different values, solve this without using == or !=.
## we made some changes on our data in previous exercises. Let's load the original data again first.
data <- mtcars
data[xor(data$vs,data$am),]## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
## Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
## Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
## Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8