R Advanced

Here are three ways to calculate the mean by group for single or multiple columns in the R data frame: Using base R’s aggregate() Using dplyr’s group_by() and summarize() Using data.table package What does it mean when we say “mean by group”? It means grouping the data based on the values of single or multiple … Read more

To count the number of rows by group in R, you can either use the dplyr::count(), dplyr::group_by() with tally(), or dplyr::group_by() with summarize(n = n()) functions, each suited for different use cases. By a single group Counting observations by a single group variable means grouping the dataset based on a single column. For example, you … Read more

Here are six ways to remove a single column from a data frame in R: By assigning NULL to a specific column Removing a column by subsetting Deleting by column index Using subset() Using dplyr Using data.table Here is the data frame for the practical: df <- data.frame( Title = c( “Inception”, “The Dark Knight”, … Read more

Dates in R are stored as the number of days since 1970-01-01, so converting a Date object to a Numeric gives those day counts. But what about POSIXct? Well, those are stored as seconds since the same epoch, so converting them would give a much larger number. Here are three ways to convert Date to … Read more

NA values are missing values. They are somehow absent from a data frame. Before creating a model based on a data frame, we need to clean the data frame from missing values, and it depends on different scenarios. Here are four different ways for different scenarios to remove NA values from a data frame: Use … Read more

NULL represents a null object, and sometimes, it’s logical for the project to filter it out from either a list or data frame. Here are three ways to remove NULL values from a list in R: Using Filter() with Negate() and is.null() Using sapply() or lapply() with Subsetting Using purrr::discard() (Tidyverse Approach) For example, if … Read more

The basename() is a base R function that extracts the last component (or the ‘base name’) of a file or directory path and returns the name of the file or directory. So, if you have a path like “/Users/krunallathiya/Desktop/Code/pypro/data.pdf,“ basename() would return “data.pdf.“ The opposite function of basename() is dirname(), which gives the directory part of the path. Syntax basename(path) … Read more

The best and most efficient way to remove rows from a data frame is using “negative indexing”. It is a base R approach that does not require any packages. However, there are different approaches you should be aware of, depending on the situation you are encountering. Here are five ways: Using negative indexing (For single … Read more

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