This process is iterated until the last element. In case the compared element is smaller than our selected minimum, the second element becomes the minimum. In the next step, the selected minimum number is compared with the next element or number. For example, in a row of numbers arranged in a random sequence starting element or number is selected as a minimum. In the selection sorting algorithm, the smallest element from the array of the unsorted list is selected and placed at the start of the unsorted list at every iteration. In this type of sorting the smallest element from the unsorted list is pushed to the start of the list. The selection sorting function is a widely used sorting algorithm used in the R language. If the sorted element is greater than the key element, the places are swapped, and the key element is the first element. The sorted element is then compared with the key. In this algorithm first element is assumed to be sorted and the second element is stored separately as a key element. In insertion sort algorithm, sorted and unsorted elements are compared, and the unsorted element is placed in a suitable place after each iteration. The process is repeated until the last element. In bubble sort pairs are formed for elements available in variable and elements are compared against each other, when one element is greater than another they swapped. It can be either ascending or in descending order. In this algorithm, two values are compared side by side and elements swaps their position when the criteria are met. To illustrate the different types of sorting, a sample of 10 random numbers from an array is used. Below are the different types of sorting function. R is equipped with multiple algorithms for performing sorting on the data. This package is very easy to use and reliable with accurate instructions available. In R, an alternate way to sort the data is by using dplyr package. In the below example I have used the mtcars dataset which is available in R studio. In a few cases, we might need to sort the data with multiple criteria, this can be achieved in R with the help of using variable names or index numbers. Keeping in mind index values begin a “0”. For example in place of age the index reference of the data frame would be “1”.
The Order function is used to refer to the column index rather than the name of the column. Alternately, the descending argument can be used in this position. Please note negative sign is used in front of the Age column (-df$Age) in order to sort the Age in descending order. Variables can be easily sorted in either ascending or descending order however, the order function will sort the variable in ascending by default. Sorting data frames can be accomplished with the help of order () function. To overcome this limitation Order () function is used.Ī basic sorting example using sort() function The major limitation of the sort function is that it cannot be used to sort a data frame. The sort function is used in arranging numeric or character vector in the desired order. Here x refers to the vector and decreasing has to be replaced to TRUE when the sorting has to be done in descending order. Let’s take an example of the mark’s column of all the students in a classroom. By default, the value is organized in ascending order. Sort function in R is used to sort a vector. Before removing or replacing null values, the overall impact on the data should be considered. It’s up to the analyst to decide what must be done with the missing and duplicate values.
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