Delete a Row from an R Data Frame

While doing the analysis, we might come across with data that is not required and we want to delete it. This data can be a whole row or multiple rows. For example, if a row contains values greater than, less than or equal to a certain threshold then it might not be needed, therefore we can delete it. In R, we achieve this with the help of subsetting through single square brackets.

Example

Consider the below data frame −

> set.seed(99)
> x1<-rnorm(20)
> x2<-rnorm(20,0.1)
> x3<-rnorm(20,0.2)
> x4<-rnorm(20,0.5)
> x5<-rnorm(20,1)
> df<-data.frame(x1,x2,x3,x4,x5)
> df
              x1          x2          x3          x4          x5
1   0.2139625022  1.19892152  0.33297863  0.33708211  1.03661152
2   0.4796581346  0.85251346 -1.47926432  0.38578484  1.28852606
3   0.0878287050  0.04058331 -0.07847958  0.05534064 -0.10597134
4   0.4438585075 -0.24456879 -1.35241100  0.75695917  1.89223849
5  -0.3628379205  0.32266830 -1.17969925 -0.60013713  2.18146915
6   0.1226740295  0.65178634 -1.15705659 -0.83657589  1.35116793
7  -0.8638451881  0.78364282 -0.72113718  0.70489861  1.06300672
8   0.4896242667 -0.44587940 -0.66681774  0.53528735  2.39426172
9  -0.3641169125 -1.26743616  1.85664439  0.06108749  0.98749208
10 -1.2942420067  1.50005184  0.04492028  0.90040586  1.67807643
11 -0.7457690454  1.47305395 -1.37655243  1.08517131  0.94385342
12  0.9215503620  0.55025656  0.82408260  0.98212854  1.13599383
13  0.7500543504 -0.04629386  0.53022068 -0.30483385  2.86457602
14 -2.5085540159  0.22809724 -0.19812226  0.80307719  2.14870835
15 -3.0409340953 -2.19472095 -0.88139693 -0.32617573  0.06001394
16  0.0002658005 -1.26656892  0.12307794  0.64142892  0.93811373
17 -0.3940189942 -0.09747955 -0.32553662  1.24035721  0.62390950
18 -1.7450276608  0.16808578  0.59128965  1.88504655  1.20968885
19  0.4986314508  0.19050341 -0.48045326 -0.13357748  1.70545858
20  0.2709537888  0.42275997 -0.54869693  0.73858864  1.65208847

Suppose we want to delete row 1 then we can do it as follows −

> df = df[-1,]
> df
              x1          x2           x3          x4          x5
2   0.4796581346  0.85251346  -1.47926432  0.38578484  1.28852606
3   0.0878287050  0.04058331  -0.07847958  0.05534064 -0.10597134
4   0.4438585075 -0.24456879  -1.35241100  0.75695917  1.89223849
5  -0.3628379205  0.32266830  -1.17969925 -0.60013713  2.18146915
6   0.1226740295  0.65178634  -1.15705659 -0.83657589  1.35116793
7  -0.8638451881  0.78364282  -0.72113718  0.70489861  1.06300672
8   0.4896242667 -0.44587940  -0.66681774  0.53528735  2.39426172
9 - 0.3641169125 -1.26743616   1.85664439  0.06108749  0.98749208
10 -1.2942420067  1.50005184   0.04492028  0.90040586  1.67807643
11 -0.7457690454  1.47305395 - 1.37655243  1.08517131  0.94385342
12  0.9215503620  0.55025656   0.82408260  0.98212854  1.13599383
13  0.7500543504 -0.04629386   0.53022068 -0.30483385  2.86457602
14 -2.5085540159  0.22809724  -0.19812226  0.80307719  2.14870835
15 -3.0409340953 -2.19472095  -0.88139693 -0.32617573  0.06001394
16  0.0002658005 -1.26656892   0.12307794  0.64142892  0.93811373
17 -0.3940189942 -0.09747955  -0.32553662  1.24035721  0.62390950
18 -1.7450276608  0.16808578   0.59128965  1.88504655  1.20968885
19  0.4986314508  0.19050341  -0.48045326 -0.13357748  1.70545858
20  0.2709537888  0.42275997  -0.54869693  0.73858864  1.65208847

Consecutive rows can be deleted in the following way −

> df = df[-c(1:2),]
> df
              x1          x2          x3           x4         x5
4   0.4438585075 -0.24456879 -1.35241100   0.75695917  1.89223849
5  -0.3628379205  0.32266830 -1.17969925  -0.60013713  2.18146915
6   0.1226740295  0.65178634 -1.15705659  -0.83657589  1.35116793
7  -0.8638451881  0.78364282 -0.72113718   0.70489861  1.06300672
8   0.4896242667 -0.44587940 -0.66681774   0.53528735  2.39426172
9  -0.3641169125 -1.26743616  1.85664439   0.06108749  0.98749208
10 -1.2942420067  1.50005184  0.04492028   0.90040586  1.67807643
11 -0.7457690454  1.47305395 -1.37655243   1.08517131  0.94385342
12  0.9215503620  0.55025656  0.82408260   0.98212854  1.13599383
13  0.7500543504 -0.04629386  0.53022068  -0.30483385  2.86457602
14 -2.5085540159  0.22809724 -0.19812226   0.80307719  2.14870835
15 -3.0409340953 -2.19472095 -0.88139693  -0.32617573  0.06001394
16  0.0002658005 -1.26656892  0.12307794   0.64142892  0.93811373
17 -0.3940189942 -0.09747955 -0.32553662   1.24035721  0.62390950
18 -1.7450276608  0.16808578  0.59128965   1.88504655  1.20968885
19  0.4986314508  0.19050341 -0.48045326  -0.13357748  1.70545858
20  0.2709537888  0.42275997 -0.54869693   0.73858864  1.65208847

Now we might to want remove row 1 and row 3, therefore we will be removing 4 and 6 from df and it can be done as shown below −

> df = df[-c(1,3),]
> df
              x1          x2          x3          x4         x5
5  -0.3628379205  0.32266830 -1.17969925 -0.60013713 2.18146915
7  -0.8638451881  0.78364282 -0.72113718  0.70489861 1.06300672
8   0.4896242667 -0.44587940 -0.66681774  0.53528735 2.39426172
9  -0.3641169125 -1.26743616  1.85664439  0.06108749 0.98749208
10 -1.2942420067  1.50005184  0.04492028  0.90040586 1.67807643
11 -0.7457690454  1.47305395 -1.37655243  1.08517131 0.94385342
12  0.9215503620  0.55025656  0.82408260  0.98212854 1.13599383
13  0.7500543504 -0.04629386  0.53022068 -0.30483385 2.86457602
14 -2.5085540159  0.22809724 -0.19812226  0.80307719 2.14870835
15 -3.0409340953 -2.19472095 -0.88139693 -0.32617573 0.06001394
16  0.0002658005 -1.26656892  0.12307794  0.64142892 0.93811373
17 -0.3940189942 -0.09747955 -0.32553662  1.24035721 0.62390950
18 -1.7450276608  0.16808578  0.59128965  1.88504655 1.20968885
19  0.4986314508  0.19050341 -0.48045326 -0.13357748 1.70545858
20  0.2709537888  0.42275997 -0.54869693  0.73858864 1.65208847