Group by Mzximum In R programming, the `group_by()`

function is used to group data based on one or more variables.

The `max()`

function, on the other hand, returns the maximum value in a vector or array.

In this article, we will learn how to use the `group_by()`

and `max()`

functions together in R to find the maximum value for each group.

Let’s consider a simple dataset containing sales data for different products in different stores.

# Sample dataset for demonstration purposes only. You can replace this with your dataset.

Product <- c("A", "B", "C", "A", "B", "C", "A", "B", "C") Store <- c("S1", "S1", "S2", "S1", "S3", "S3", "S2", "S3", "S3") Sales <- c(10,20,30,25,15,35,28,32,37)

#Create a data frame from the above variables

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sales_data <- data.frame(Product, Store, Sales)

Now, let’s see how we can use the `group_by()` and `max()` functions together in R to find the maximum sales for each product in each store.

First, we need to load the `dplyr` package, which provides the `group_by()` function. You can install this package using the following command: `install.packages(“dplyr”)`.

Once installed, load the package using `library(dplyr)`. Now, let’s proceed with our analysis.

# Loading the dplyr package and using it for further analysis.

library(dplyr) # Grouping the sales_data data frame by Product and Store variables

sales_max <- sales_data %>% group_by(Product, Store) %>% summarize(Max_Sales = max(Sales))

# Printing the result

print(sales_max)

Output:

```
# A tibble: 6 x 3
# Groups: Product, Store [6]
Product Store Max_Sales
<chr> <chr> <dbl>
1 A S1 25
2 A S2 28
3 B S1 20
4 B S3 32
5 C S2 30
6 C S3 37
```

In the above example, we first load the `dplyr`

package and then use the `group_by()`

function to group the `sales_data`

data frame based on the `Product`

and `Store`

variables.

We then use the `summarize()`

function to calculate the maximum sales for each group and store it in a new variable called `Max_Sales`

. Finally, we print the result using the `print()`

function.

In conclusion, the `group_by()`

and `max()`

functions can be used together in R to find the maximum value for each group.

This is a powerful feature of R’s `dplyr`

package that can be used to analyze and summarize data in various ways.

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