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To find the standard deviation for rows in an R data frame, we can use mutate function of dplyr package and rowSds function of matrixStats package. For example, if we have a data frame called df that contains two columns x and y then we can find the standard deviation for rows using the below command −df%>%mutate(STDEV=rowSds(as.matrix(.[c("x","y")])))ExampleConsider the below data frame − Live Demox1
To find the correlation between corresponding columns of two matrices, we can use mapply function but we will have to read the matrices using as.data.frame function. For example, if we have two matrices called M_1 and M_2 and each of these matrices contains 5 columns then the correlation between corresponding columns of these matrices can be found by using the command mapply(cor,as.data.frame(M_1),as.data.frame(M_2))ExampleConsider the below matrices − Live DemoM1
To delete matrix rows if a particular column satisfies some condition, we can use subsetting with single square brackets and take the subset of the matrix based on the condition. For example, if we have a matrix M and want to delete rows if column first of M do not contain value 5 then we can use the command M[M[,1]==5,].ExampleConsider the below matrix − Live DemoM1
To filter rows by excluding a particular value in columns of the data frame, we can use filter_all function of dplyr package along with all_vars argument that will select all the rows except the one that includes the passed value with negation. For example, if we have a data frame called df and we want to filter rows by excluding value 2 then we can use the commanddf%>%filter_all(all_vars(.!=2))ExampleConsider the below data frame − Live Demox1
By default, R considers the vector or the data frame column values. But if we want to set the range for boxplot in base R, we can use ylim argument within the boxplot function. For example, if we have a vector called x that contains values starting from 21 to 50 and we want to have the range in the boxplot starting from 1 to 100 then we can use the commandboxplot(x,ylim=c(1,100))Example Live Demox
To separate string and a numeric value, we can use strplit function and split the values by passing all type of characters and all the numeric values. For example, if we have a data frame called df that contains a character column Var having concatenated string and numerical values then we can split them using the below command −strsplit(df$Var,split="(?
To find the mean for x number of rows in a column, we can use colMeans function by accessing the column and providing the number of rows. For example, if we have a matrix called M that contains 20 rows and 5 columns then we can find the mean of column 5 for 5 number of rows can use the command colMeans(matrix(M[,5],nrow=5))ExampleConsider the below data frame − Live DemoM1
To divide each value in a data frame by column total, we can use apply function and define the function for the division. For example, if we have a data frame called df that contains five columns then we can divide each value of these columns by column total using the command apply(df,2,function(x){x/sum(x)})ExampleConsider the below data frame − Live Demox1
To find the sum by two factor columns, we can use aggregate function. This is mostly required when we have frequency/count data for two factors. For example, if we have a data frame called df that contains two factor columns say f1 and f2 and one numerical column say Count then the sum of Count by f1 and f2 can be calculated by using the command aggregate(Count~f1+f2,data=df,sum).ExampleConsider the below data frame − Live Demox1
To convert an array into a matrix in R, we can use apply function. For example, if we have an array called ARRAY that contains 2 array elements then we can convert this array into a single matrix using the command apply(ARRAY,2,c). We need to understand the dimension of the array making the conversion otherwise the output will not be as expected.ExampleConsider the below array − Live Demox1