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To add rows in an R data frame, we can follow the below steps −First of all, create a data frame.Then, use rbind function and the vectors that will be added as rows to the data frame.ExampleCreate the data frameLet’s create a data frame as shown below −x
To create a column of first non-zero value in each row of a data.table object in R, we can follow the below steps −First of all, create a data.table object with some zero values.Then, use apply function and a custom function to find the first non-zero in each row of the data.table object.ExampleCreate the data.table objectLet’s create a data.table object as shown below −library(data.table) v1
To find the percent of zeros in each row of an R data frame, we can follow the below steps −First of all, create a data frame.Then, use rowSums function along with ncol function to find the percent of zeros in each row of the data frame.ExampleCreate the data frameLet’s create a data frame as shown below −x
To subset an R data frame by ignoring a value in one of the columns, we can follow the below steps −First of all, create a data frame.Then, use single square brackets to subset the data frame by ignoring a value in one of the columns.ExampleCreate the data frameLet’s create a data frame as shown below −x
To remove percentage sign at last position from every value in R data frame column, we can follow the below steps −First of all, create a data frame with a column having percent sign at last position in every value.Then, use gsub function to remove the percent sign at last position from every value in the column.ExampleCreate the data frameLet’s create a data frame as shown below −var
To find the absolute maximum of each group in R data frame, we can follow the below steps −First of all, create a data frame.Then, use summarise_each function of dplyr package along with which.max and abs function to find the absolute maximum of each group after grouping with group_by.Example 1Create the data frameLet’s create a data frame as shown below −x
To find the rank of 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 find the rank of each value in columns if some columns are categorical.ExampleCreate the data frameLet’s create a data frame as shown below −Level
To find the range of 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 find the range of columns if some columns are categorical.ExampleCreate the data frameLet’s create a data frame as shown below −Level
To convert values in alternate rows to negative in R data frame column, we can follow the below steps −First of all, create a data frame.Then, use vector multiplication with 1 and minus 1 to convert values in alternate rows to negative.ExampleCreate the data frameLet’s create a data frame as shown below −x
To find the percent of NAs in each row of an R data frame, we can follow the below steps −First of all, create a data frame.Then, use rowSums function and ncol function along with apply function to find the percent of NAs in each row of the data frameExampleCreate the data frameLet’s create a data frame as shown below −v1