Programming Articles - Page 883 of 3368

To convert a numeric column to binary factor based on a condition in R data frame, we can use factor function along with ifelse function.For Example, if we have a data frame called df that contains a numerical column say Num and we want to convert it to a binary factor if Num is less than 100 then it will be Minor otherwise Major then we can use the below given command −df$Num_Factor

To standardize data.table object column by group, we can use scale function and provide the grouping column with by function.For Example, if we have a data.table object called DT that contains two columns say G and Num where G is a grouping column and Num is a numerical column then we can standardize Num by column G by using the below given command −DT[,"Num":=as.vector(scale(Num)),by=G]Example 1Consider the below data.table object −library(data.table) Grp

Suppose we have three columns say X, Y, and Z in an R data frame called df and we want to replace values in columns X and Y with the same value if the values are greater than values in Z and if they are less than the values in Z then we can replace with Z values.Check out the below Examples to understand how it can be done.Example 1Following snippet creates a sample data frame −x1

The random replacement values in an R data frame column can be done with the help of sample function along with nrow function and single square subsetting.For Example, if we have a data frame called df that contains a columns say X and we want to randomly replace 5 values in X with 1.5 then we can use the below given command −df$X[sample(nrow(df),5)]

To multiply corresponding values from two data.table objects in R, we can follow the below steps −First of all, create two data.table objects.Then, use mapply function to multiply corresponding values from those two data.table objects.ExampleCreate the first data.table objectLet’s create a data.table object as shown below −library(data.table) x1

To find the percentage of zeros in each column of a matrix in R, we can follow the below steps −First of all, create a matrix.Then, use colSums function along with nrow function to find the percentage of zeros in each column.Example 1Create the matrixLet’s create a matrix as shown below −M1

To round each value in columns if some columns are categorical in R data frame, we can follow the below steps −First of all, create a data frame.Then, use numcolwise function from plyr package to round each value in columns if some columns are categorical.ExampleCreate the data frameLet’s create a data frame as shown below −Level

To change the color of a particular bar using geom_bar in R, we can provide the count corresponding to the value for which we want to change the color inside aes function.For Example, if we have a data frame called df that contains two columns say V and F where V is categorical and F is for frequency and we want to change the color of frequency 10 in bar plot then we can use the below mentioned command −ggplot(df, aes(V, F))+geom_bar(aes(fill=..F..==10), stat="identity")ExampleFollowing snippet creates a sample data frame −xRead More

To find the log2 of each value if some columns are categorical in R data frame, we can follow the below steps −First of all, create a data frame.Then, use numcolwise function from plyr package to find the log2 if some columns are categorical.ExampleCreate the data frameLet’s create a data frame as shown below −Level

To find the number of zeros in each column of an R data frame, we can follow the below steps −First of all, create a data frame.Then, use colSums function to find the number of zeros in each column.Example 1Create the data frameLet’s create a data frame as shown below −x