R Advanced

Transposing means switching rows to columns and columns to rows. It is a common operation in the matrix. However, data frames are a bit different because they can have different data types in different columns, whereas the matrix has the same type for each column. So, transposing a data frame is different from transposing a matrix. … Read more

We can perform a targeted analysis to identify patterns and trends. To isolate the data pertinent to our analysis, we must filter rows based on conditions from a data frame. Conditions help us uncover patterns and trends within our data. Here are the two most prominent ways to select rows by single or multiple conditions … Read more

Whether you want to add new data to your existing datasets or create new variables based on existing ones, you need to add columns to the existing Data Frame. Let’s understand how this works behind the scenes. In the Data Frame, each column represents a vector. To add a column, we just need to assign … Read more

The square root of a number is a value that is multiplied by itself, giving the original number. For example, the square root of 16 is 4 because if you multiply 4 by 4, it will give us 16, so the original number is 4. To calculate the square root of a number, vector, matrix, … Read more

Duplicate rows refer to all the values across all columns that are the same in two or more rows. To avoid redundant data, we must remove duplicates from a data frame. For example, if the same row appears three times in a data frame, we must remove two rows because they are duplicates of one … Read more

A vector is a data structure that holds the same type of data. When working with real-time data, it may contain missing data, and it can be represented by NA (not available). For a proper data analysis, we need to exclude NA values from the vector. Now, you may have one question in your mind. … Read more

No matter how much technology has improved over the years for storing and sharing data, one format is still widely used in the industry: Excelsheet, which has file extensions like “.xls” or “.xlsx.“ Here are three ways to import Excel files in R: Using the readxl package (Efficient way) Using xlsx package RStudio’s Import Dataset tool For this tutorial’s … Read more

Most real-world data resides in external sources, including CSVs, Excels, Texts, or Databases. To bring back the data from these external sources, we need a bridge or function that we can use to analyze these data into our R ecosystem and further manipulate it to get the required results. That’s where a base function like … Read more

When you are working with large datasets, you often come across names that are in inconsistent formats or capitalization. To solve this problem, we need to standardize the format to improve data quality and consistency. One way to standardize is by converting the first letter of each word to uppercase. The most efficient way to … Read more

In the real world, data is not static. You need to keep updating it or adding new data to an existing data set. As new data becomes available, you need to add it to the existing data frame to maintain an up-to-date record. Here are four ways to append rows to a data frame in R: … Read more