Server Side Programming Articles - Page 742 of 2650

To change the border color of box of a base R plot, we can use box function with col argument where we can pass the color other than black because black is the default color. We first need to create the plot using plot function and then box function will be used as shown in the below examples.Example 1To change the border color of box of a base R plot, use the command given below −plot(1:10) box(col="red")OutputIf you execute the above given command, it generates the following output −Example 2To change the border color of box of a base R ... Read More

To find the most frequent factor value in an R data frame column, we can use names function with which.max function after creating the table for the particular column. This might be required while doing factorial analysis and we want to know which factor occurs the most.Check out the below examples to understand how it can be done.Example 1Following snippet creates a sample data frame −Factor_1

To extract the first row of each matrix stored in a list in R, we can use lapply function. For example, if we have a list called LIST that contains some matrices then we can find the first row of each matrix by using the command given below − lapply(LIST,'[',1,)Check out the below given example to understand how it can be done.ExampleFollowing snippet creates a list of matrices −M1

To extract the outliers of a boxplot, we can use out function along with the boxplot function. For example, if we have a vector called X which contains some outliers then we can extract those outliers by using the command given below − boxplot(df$X, plot=FALSE)$outThis command will not create a plot as plot is set to FALSE.ExampleFollowing snippet creates a sample data frame −df=data.frame(x=rlnorm(25)) dfThe following dataframe is created −      x 1  0.5699270 2  3.5812629 3  0.3507882 4  0.1400328 5  0.7239948 6  2.5494114 7  3.1243611 8  5.3207739 9  0.1672539 10 7.6235529 11 0.4950263 12 1.1713592 13 1.6590328 14 ... Read More

Sometimes missing values are coded and when we perform analysis without replacing those missing values the result of the analysis becomes a little difficult to interpret, especially it is difficult to understand by first time readers.Therefore, we might want to remove rows that contains coded missing values. For this purpose, we can replace the coded missing values with NA and then replace the rows with NA as shown in the below given examples.Example 1Following snippet creates a data frame, if missing values are coded as 1 −x1

To replace zero with previous value in an R data frame column, we can use na.locf function of zoo package but to apply this we first need to replace the zero values with NA.For example, if we have a data frame called df that contains a column say Rate then we can use the below commands to replace 0 values in Rate with previous value by using the below given commands − df$Rate[df$Rate==0]

If we want to add two columns of an R data frame and each of them contains missing values then the addition of columns can be done in one of the following ways −Adding both the column values if they are numeric.Returning numeric if one of the columns has missing value.Returning NA if both the columns have missing value.To this we can take help of apply function and ifelse function as shown in the below given examples.Example 1Following snippet creates a sample data frame −x1

We can take the transpose of vectors stored in an R list by using Map function with do.call. For example, if we have a list called LIST that contains say ten vectors then we can transpose these vectors by using the command given below − do.call(Map,c(f=c,LIST))Check out the below examples to understand how it works.Example 1To take transpose of vectors stored in an R list, use the command given below −List1

To subset a matrix based on values in a particular column, we can use single square brackets and provide the row and column values. The column values will be set for the columns that we want to subset and the row value will be set for the values of the column using which we want to subset the matrix.Check out the below example to understand how it works.ExampleFollowing snippet creates a matrix −M

To highlight outliers in a boxplot, we can create the boxplot with the help of Boxplot function of car package by defining the id.method.For example, if we have a vector called V then the boxplot of V with highlighted outliers can be created by using the below given command −Boxplot(~V,id.method="y")Example 1To highlight outliers in a boxplot, use the command given below −library(car) x