To find the count of unique group combinations in an R data frame, we can use count function of dplyr package along with ungroup function.For Example, if we have a data frame called df that contains three grouping columns say G1, G2, and G3 then we can count the unique group combinations in df by using the below given command −count(df,G1,G2,G3)%%ungroup()Example 1Following snippet creates a sample data frame −Grp1

To find the cumulative sums 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 cumulative sums if some columns are categorical.ExampleCreate the data frameLet’s create a data frame as shown below −Gender

To multiply vector values in sequence with data frame columns in R, we can follow the below steps −First of all, create a data frame.Then, create a vector.After that, use t function for transpose and multiplication sign * to multiply vector values in sequence with data frame columns.Example 1Create the data frameLet’s create a data frame as shown below −x1

To create a column of exponent 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 exponent 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 create a column of log with base 10 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 log with base 10 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

If we have multiple matrices and we want to combine the rows of those matrices alternately then we would first need to find the order of the matrices with order function along with sequence and sapply function after reading the matrices with list after that the values will be combined with rbind function.Check out the Example given below to understand how it can be done.ExampleFollowing snippet creates a sample matrix −M1

To replace all values in an R data frame if they are greater than a certain value, we can use apply function with ifelse function.For Example, if we have a data frame called df and we want to replace all values in df with 5 if they are greater than 10 then we can use the command given below −df[]

The error hist.default, 'x' must be numeric occurs when we pass a non-numerical column or vector to the hist function. If we have a non-numerical column in a data frame or a non-numerical vector and we want to create the histogram of that data can be created with the help of barplot and table function.Check out the below given Exampleto understand how it can be done.ExampleFollowing snippet creates a sample data frame −x

To create a column of log with base 2 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 log with base 2 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 create a column of natural log 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 natural log 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