rowSums function in R sums up all the rows and returns the output
colSums function in R sums up all the columns and returns the output
rowMeans function in R find the mean of all the rows and returns the output
colMeans function in R find the mean of all the columns and returns the output
rowSums function in R:
lets use iris data set to depict example on rowSums function in R
# rowSums function in R rowSums(iris[,-5])
The above function calculates sum of all the rows of the iris data set. We will be neglecting fifth column because it is categorical. As we have 150 rows in the iris data set, the output will be with 150 elements.
So the output will be
[17] 11.0 10.3 11.5 10.7 10.7 10.7 9.4 10.6 10.3 9.8 10.4 10.4 10.2 9.7 9.7 10.7
[33] 10.9 11.3 9.7 9.6 10.5 10.0 8.9 10.2 10.1 8.4 9.1 10.7 11.2 9.5 10.7 9.4
[49] 10.7 9.9 16.3 15.6 16.4 13.1 15.4 14.3 15.9 11.6 15.4 13.2 11.5 14.6 13.2 15.1
[65] 13.4 15.6 14.6 13.6 14.4 13.1 15.7 14.2 15.2 14.8 14.9 15.4 15.8 16.4 14.9 12.8
[81] 12.8 12.6 13.6 15.4 14.4 15.5 16.0 14.3 14.0 13.3 13.7 15.1 13.6 11.6 13.8 14.1
[97] 14.1 14.7 11.7 13.9 18.1 15.5 18.1 16.6 17.5 19.3 13.6 18.3 16.8 19.4 16.8 16.3
[113] 17.4 15.2 16.1 17.2 16.8 20.4 19.5 14.7 18.1 15.3 19.2 15.7 17.8 18.2 15.6 15.8
[129] 16.9 17.6 18.2 20.1 17.0 15.7 15.7 19.1 17.7 16.8 15.6 17.5 17.8 17.4 15.5 18.2
[145] 18.2 17.2 15.7 16.7 17.3 15.8
colSums function in R:
lets use iris data set to depict example on colSums function in R
# colSums function in R colSums(iris[,-5])
The above function calculates sum of all the columns of the iris data set. We will be neglecting fifth column because it is categorical. As we have 4 columns in the iris data set, the output will be with 4 elements.
So the output will be
Sepal.Length Sepal.Width Petal.Length Petal.Width
876.5 458.6 563.7 179.9
rowMeans function in R:
lets use iris data set to depict example on rowMeans function in R
# rowMeans function in R rowMeans(iris[,-5])
The above function calculates Mean of all the rows of the iris data set. We will be neglecting fifth column because it is categorical. As we have 150 rows in the iris data set, the output will be with 150 elements.
So the output will be
[1] 2.550 2.375 2.350 2.350 2.550 2.850 2.425 2.525 2.225 2.400 2.700 2.500 2.325
[14] 2.125 2.800 3.000 2.750 2.575 2.875 2.675 2.675 2.675 2.350 2.650 2.575 2.450
[27] 2.600 2.600 2.550 2.425 2.425 2.675 2.725 2.825 2.425 2.400 2.625 2.500 2.225
[40] 2.550 2.525 2.100 2.275 2.675 2.800 2.375 2.675 2.350 2.675 2.475 4.075 3.900
[53] 4.100 3.275 3.850 3.575 3.975 2.900 3.850 3.300 2.875 3.650 3.300 3.775 3.350
[66] 3.900 3.650 3.400 3.600 3.275 3.925 3.550 3.800 3.700 3.725 3.850 3.950 4.100
[79] 3.725 3.200 3.200 3.150 3.400 3.850 3.600 3.875 4.000 3.575 3.500 3.325 3.425
[92] 3.775 3.400 2.900 3.450 3.525 3.525 3.675 2.925 3.475 4.525 3.875 4.525 4.150
[105] 4.375 4.825 3.400 4.575 4.200 4.850 4.200 4.075 4.350 3.800 4.025 4.300 4.200
[118] 5.100 4.875 3.675 4.525 3.825 4.800 3.925 4.450 4.550 3.900 3.950 4.225 4.400
[131] 4.550 5.025 4.250 3.925 3.925 4.775 4.425 4.200 3.900 4.375 4.450 4.350 3.875
[144] 4.550 4.550 4.300 3.925 4.175 4.325 3.950
colMeans function in R:
lets use iris data set to depict example on colMeans function in R
# colMeans function in R colMeans(iris[,-5])
The above function calculates mean of all the columns of the iris data set. We will be neglecting fifth column because it is categorical. As we have 4 columns in the iris data set, the output will be with 4 elements.
So the output will be
Sepal.Length Sepal.Width Petal.Length Petal.Width
5.843333 3.057333 3.758000 1.199333
