What is the method for performing row-wise calculations on data sets in R?

There are multiple ways to perform calculations across rows in a dataset using R language, here are some commonly used methods:

1. Aggregate functions can be used to perform calculations across rows on the entire dataset, such as sum, mean, max, min, etc. For example, using the sum function can calculate the total of a column in the dataset.
2. By using the apply function family, such as apply, sapply, lapply, etc., you can apply a specified function to every row or column of a dataset. For example, you can use the apply function to calculate the average of each row.
3. Using the dplyr package: The dplyr package offers a set of powerful and easy-to-use functions for performing row-wise calculations on datasets. For example, the summarise function can be used to summarize data based on specified conditions.
4. By using the data.table package, you can access a set of efficient functions for performing row-wise calculations on large datasets. For example, you can utilize the summarize function to calculate the mean for each group in the dataset.
5. Using the tidyverse package: The tidyverse package offers a consistent set of functions for data cleaning and row-wise calculations. For example, you can use the group_by and summarize functions to calculate data sets by groups.

These methods offer flexible and efficient ways to perform cross-row calculations on datasets, with the specific method chosen depending on the size of the dataset and the computational requirements.