Deleting a row of data is variable is greater than 5.

[kfox383]

I am very new to R studio and am trying to write a line of code that removes an entire row of data if variable one is less than 5 or if variable two is greater than 20, I have ten columns of data total.

Could someone please point me in the right direction?

Thank you in advance.

[technocrat]

suppressPackageStartupMessages({library(dplyr)})

# in base
rbind(mtcars[which(mtcars[,1] < 20),],mtcars[which(mtcars[,2] > 4),])
#>                       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
#> Duster 360           14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
#> 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
#> 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
#> 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
#> Camaro Z28           13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
#> 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    6
#> Maserati Bora        15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
#> 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
#> Hornet Sportabout1   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
#> Valiant1             18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
#> Duster 3601          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
#> Merc 2801            19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
#> Merc 280C1           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
#> Merc 450SE1          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
#> Merc 450SL1          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
#> Merc 450SLC1         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
#> Cadillac Fleetwood1  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
#> Lincoln Continental1 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
#> Chrysler Imperial1   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
#> Dodge Challenger1    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
#> AMC Javelin1         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
#> Camaro Z281          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
#> Pontiac Firebird1    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
#> Ford Pantera L1      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
#> Ferrari Dino1        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
#> Maserati Bora1       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8

# with dplyr

mtcars %>% filter(mpg < 20 | cyl > 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
#> Hornet 4 Drive      21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
#> 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
#> Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
#> 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
#> 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
#> 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
#> Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
#> 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    6
#> Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8

^{Created on 2020-09-20 by the reprex package (v0.3.0.9001)}

[fcas80]

You can remove rows with the subset command

x<- c(1,2,3,4,5)
y <- c(6,7,8,9,10)
z <- c(11,12,13,14,15)
df <- data.frame(x, y, z)
df
df <- subset(df, x>3 | y<7)
df