Insightful Analytics
Krunal Lathiya 
Finding the minimum value by group means getting the smallest value within each group in our data frame. For example, if I have a column that I defined as a “group” and another column called “value” that contains different numeric values, then I will extract the minimum value from the value column for each distinct … 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, you need to 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 … Read more
The dplyr summarise()(or summarize()) function aggregates data into a single summary value for each group or entire dataset if ungrouped. It collapses multiple rows into a concise statistical summary, such as mean, sum, count, etc. Developers often use summarize() with group_by(), which splits the data into groups based on one or more categorical variables (Columns you … 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 a number of rows conditionally in a data frame using base R functions, dplyr methods, … 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), and 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: … 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
What does it mean when we say “mean by group”? It means grouping the data based on the values of single or multiple columns and then calculating the mean (average) of those values, but doing so separately for each group. Here are three ways to calculate the mean by group for single or multiple columns … Read more
Whether you want to summarize the categorical data, identify patterns and trends, or calculate percentages and proportions, you must quickly analyze how many observations fall into each category. For that, you can create a count column that tells the number of observations that fall in each variable. To count the number of rows by group … Read more
The group_by() function from the dplyr package allows us to group data frames by one or more variables (columns), enabling subsequent operations to be performed on these groups. For example, we need to calculate the total sales by each category or count the number of items per category. You cannot use the group_by() function alone … Read more
