Insightful Analytics
Krunal Lathiya 
Transposing means switching rows to columns and columns to rows. It is a common operation in the matrix. The above figure shows that column names from the original data frame have become row names, and the first column values of the original data frame have become column names. Everything has been switched. Here are two … Read more
Here are the two most prominent ways to select rows by single or multiple conditions in R: Subsetting with [ ] Using dplyr::filter() 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. Method 1: Subsetting … Read more
Before executing an operation on an object, it is advisable to check its length, as this helps prevent potential errors. Some operations require an object to be of the same length. It ensures that an object has the expected number of elements. The length() function is used to set or get the length of vectors … Read more
Rounding is a process of approximating a number to a shorter, simpler, and more interpretable value while retaining its closeness to the original value. For example, if you are working in the finance division, you often publish a research report on the economy, where numbers in reports often round to 2 decimal points. Here are … Read more
Here are the five ways to add single or multiple columns to a data frame in R: Using $ operator Using square ([ ]) notation Using cbind() Using tidyverse::add_column() Using dplyr::mutate() 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 … 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
For string operations like comparing strings, data standardization, formatting output, or input validation, we may want to convert the input to uppercase (or lowercase, depending on the situation) to ensure consistency and prevent errors caused by inconsistent capitalization. The toupper() function converts a string to an upper case. It accepts an input string and converts … 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
