To convert a data frame into two column data frame with values and column name as variable in R, we can follow the below steps −First of all, create a data frame.Then, use stack function to convert data frame.ExampleCreate the data frameLet’s create a data frame as shown below −x

To extract number from string if string is in different format than normal in R data frame, we can follow the below steps −First of all, create a data frame.Then, use gsub function along with as.numeric function to extract the number.ExampleCreate the data frameLet’s create a data frame as shown below −x

To extract number from string in R data frame, we can follow the below steps −First of all, create a data frame.Then, use gsub function to extract number from string.ExampleCreate the data frameLet’s create a data frame as shown below −x

To remove repeated numbers in sequence in R data frame column, we can follow the below steps −First of all, create a data frame.Then, use diff function and subsetting with single square brackets to remove repeated numbers in sequence.Example 1Create the data frameLet’s create a data frame as shown below −x

To split a factor variable into n number of variables equal to factor size with full length in R data frame, we can follow the below steps −First of all, create a data frame.Then, use mtabulate function of qdapTools package to split the factor variable.ExampleCreate the data frameLet’s create a data frame as shown below −factor

To find the column means by factor levels, we can use summarise function along with mean function after creating the group of factor levels with group_by function.For example, if we have a data frame called df that contains a factor column say F and a numerical column say Num then we can find the mean of Num column by factor levels by using the below given command −df%>%group_by(F)%>%summarise(Average=mean(Num))Example 1Following snippet creates a sample data frame −grp

To replace total string if partial string matches with another string in R data frame column, we can follow the below steps −First of all, create a data frame with string column.Then, use gsub function to replace total string if partial string matches with another string.ExampleCreate the data frameLet’s create a data frame as shown below −String

To find the number of common words between two string vectors, we would first need to split both the vectors using unlist and strsplit function and then we can apply length function along with intersect function.Check out the below examples to understand how it can be done.Example 1Following snippet creates a vector −x1

Most of the times in data analysis, the first name and last name of people are joined together or we can say they are stored in a single space hence we need to separate them to make the data easily readable. To create separate columns for first and last name in R, we can use extract function of tidyr package.Check out the below given examples to understand how it can be done.Example 1Following snippet creates a sample data frame −Names

To change the row order in an R data frame, we can use single square brackets and provide the row order at first place.For example, if we have a data frame called df that contains 10 rows then we can change the row order by using the command given below −df[c(6:8,2,5,9,10,1,3:4),]Check out the below examples to understand how it works.Example 1Following snippet creates a sample data frame −x1