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

To find the number of columns where all row values are equal in R data frame, we can follow the below steps −First of all, create a data frame.Then, use sum function along with length and apply function to find the number of columns where all row values are equal.Example 1Create the data frameLet’s create a data frame as shown below −x

To create histogram with varying binwidth using ggplot2 in R, we can follow the below steps −First of all, create a data frame.Then, use geom_histogram function with breaks argument having varying differences.ExampleCreate the data frameLet’s create a data frame as shown below −x