Insightful Analytics
Krunal Lathiya 
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
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
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
