Insightful Analytics
Krunal Lathiya 
The names() function in R gets or sets the names of objects such as vectors, lists, or data frames. If you are using it to fetch the name, it will return a character vector containing the names assigned to its elements or columns. Syntax names(obj) # To get names names(obj) <- value # To set names Parameters Name Value … 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
When you convert a list to a matrix, you are essentially taking the elements of a list and rearranging them into a two-dimensional structure with rows and columns. To convert a list to the matrix in R, use the matrix() function and pass the unlist() function as an argument. The unlist() function flattens a list into a … Read more
Dimensions are the structure of the data. A matrix has two dimensions: a row and a column, while an array can have multiple dimensions. Dimension labels are names that we can assign to a dimension. For example, for a matrix, row names are labels, and column names are also. The dimnames() function in R is … Read more
If you are working with multidimensional data in R, you should explore Arrays. Arrays are designed to store data in more than two dimensions and represent complex data structures. The as.array() function attempts to coerce the input object into an array structure. It handles various input types, including vectors, lists, data frames, etc. Syntax as.array(input_obj, … Read more
If you are working with a data frame where you need to perform mathematical operations like addition and subtraction on a column, that column is of type character, but the data is numbers. What will you do? This is where you need to convert that specific column to numeric. Here are four ways to convert … Read more
When you are working with real-time projects, you often come across raw datasets where columns have names like (“v1”, “var2”, and “cust_id”). These names seem very cryptic and are not descriptive. That’s why we must rename them to descriptive names (e.g., “age”, “income”, “customer_ID”), which makes the data much easier to understand at a glance. Here … Read more
If you want to put data validation in progress, you must identify the file type or “MIME Type” before processing. To identify the file type, we might need to check its extension. Here are two ways to get an extension of a file in R: Using the tools::file_ext() Using regular expression Method 1: Using the … Read more
The fastest and easiest way to convert a list to a data frame in R is to use the “as.data.frame()” function. This function checks whether an input object is a data frame and, if not, tries to convert it. main_list <- list( col1 = c(1, 2, 3), col2 = c(4, 5, 6), col3 = c(7, 8, … Read more
To check if a file is empty in R, you can use either the “file.info()’s size attribute” or the “file.size()” function. We must check if a file is empty to save our resources from reading or processing. It helps us put a data validation that will prevent unexpected results or errors. Based on its emptiness, … Read more
