R Advanced

The most common and efficient way to find the minimum value by group is to use the dplyr package. It provides group_by(), summarise(), and filter() methods to extract the smallest value based on our requirement. Finding the minimum value by group means getting the smallest value within each group in our data frame. For example, … Read more

If you want to find the maximum value within a specific subset of your data, you must find the maximum value within each group. First, group your data based on the values of one or more categorical variables (columns). The second step is identifying the maximum value of a specific numeric variable (numeric column) for … Read more

Counting conditionally in the data frame means counting the number of rows that meet specific conditions defined by the user. It is the process of determining the number of rows based on certain conditions evaluated to TRUE. You can count several rows conditionally in a data frame using base R functions, dplyr methods, or data.table … Read more

What do you mean by counting unique values by group? Well, it means you divide the dataset into subsets based on the values of one or more categorical variables (columns). Within each subset, you determine the number of distinct (unique) values in a specific column. Here are three ways to count unique values by group: Using … Read more

To calculate the percentage by the group in R, you need to combine various dplyr functions such as  group_by(), summarise(), mutate(), and ungroup(). Percentage by group means calculating the percentage of a variable within each group defined by another variable in a dataset. Here is the core concept behind it: First, you must divide your data … Read more

In R, you can calculate the sum by group using the base aggregate(), dplyr’s group_by() with summarise(), or the data table package. What do we mean when we say sum by group? Well, it means dividing the dataset into meaningful groups based on categorical variables and then calculating the summation of the values within each … Read more

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