Programming Articles - Page 866 of 3363

To create a boxplot of single column in R data frame with column name, we can follow the below steps −First of all, create a data frame with single numerical column and create the boxplot for that column using boxplot function.Then, create the same boxplot with show.names argument set to TRUE.ExampleCreate the boxplotUsing boxplot function to create a boxplot for single column of a data frame as shown below −x

To find the percentage of values that lie within a range in single column R matrix, we can follow the below steps −First of all, create a matrix.Then, use sum function along with extreme values for range and length function to find the percentage of values that lie within that range.ExampleCreate the data frameLet’s create a data frame as shown below −M

To create a column of product in data frames stored in R list, we can follow the below steps −First of all, create a list of data frames.Then, use lapply function to create a column of product in data frames stored in the list.ExampleCreate the list of data framesUsing data.frame function to create data frames and list function to create the list of those data frames −df1

To combine two rows in R data frame by addition, we can follow the below steps −First of all, create a data frame.Then, using plus sign (+) to add two rows and store the addition in one of the rows.After that, remove the row that is not required by subsetting with single square brackets.ExampleCreate the data frameLet’s create a data frame as shown below −x

To replace NAs with 0 in an R list that contains data.table objects, we can follow the below steps −First of all, create a list of data.table objects that contain some NAs.Then, use lapply function and is.na function to replace NAs with 0 in the list.ExampleCreate the listLet’s create a list as shown below −library(data.table) DT1

To remove hash 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 hash at last position in every value.Then, use gsub function to remove hash at last position from every value in the column.ExampleCreate the data frameLet’s create a data frame as shown below −x

To find the count of each category in an R data frame column, we can follow the below steps −First of all, create a data frame.Then, use summarise function of dplyr package after grouping along with n.ExampleCreate the data frameLet’s create a data frame as shown below −Grp

To find the number of zeros in each row of a data.table object in R, we can follow the below steps −First of all, create a data.table object.Then, use rowSums function to find the number of zeros 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) x

To find the percentage of each category in an R data frame column, we can follow the below steps −First of all, create a data frame.Then, use summarise function of dplyr package after grouping along with n and nrow.ExampleCreate the data frameLet’s create a data frame as shown below −Group

To create pivot table with sum for data stored in data.table object in R, we can follow the below steps −First of all, create a data.table object with two categorical and one numerical column.Then, use dcast function from reshape2 package to create pivot table for the data stored in data.table object.ExampleCreate the data.table objectLet’s create a data.table object as shown below −library(data.table) Factor