Groupby sum in R can be accomplished by aggregate() or group_by() function of dplyr package. Groupby sum of multiple column and single column in R is accomplished by multiple ways some among them are group_by() function of dplyr package in R and aggregate() function in R. Let’s see how to

- Groupby sum of single column in R
- Groupby sum of multiple columns
- Groupby sum using aggregate() function
- Groupby sum using group_by() function.

Groupby sum and its functionality has been pictographically represented as shown below

First let’s create a dataframe

df1= data.frame(Name=c('James','Paul','Richards','Marico','Samantha','Ravi','Raghu','Richards','George','Ema','Samantha','Catherine'), State=c('Alaska','California','Texas','North Carolina','California','Texas','Alaska','Texas','North Carolina','Alaska','California','Texas'), Sales=c(14,24,31,12,13,7,9,31,18,16,18,14)) df1

df1 will be

#### Groupby using aggregate() syntax:

**aggregate(x, by, FUN, …, simplify = TRUE, drop = TRUE)**

X | an R object, mostly a dataframe |

by | a list of grouping elements, by which the subsets are grouped by |

FUN | a function to compute the summary statistics |

simplify | a logical indicating whether results should be simplified to a vector or matrix if possible |

drop | a logical indicating whether to drop unused combinations of grouping values. |

**Groupby sum of single column in R**

#### Method 1 : using Aggregate ()

Aggregate function along with parameter by – by which it is to be grouped and function sum is mentioned as shown below

# Groupby sum of single column aggregate(df1$Sales, by=list(df1$State), FUN=sum)

so the grouped dataframe will be

**Method 2: groupby using dplyr**

group_by() function takes “state” column as argument summarise() uses sum() function to find sum of sales.

library(dplyr) df1 %>% group_by(State) %>% summarise(sum_sales = sum(Sales))

so the grouped dataframe with sum of sales calculated will be

**Groupby sum of multiple column in R:**

**Method 1:**

Aggregate function which is grouped by state and name, along with function sum is mentioned as shown below

# Groupby sum of multiple columns aggregate(df1$Sales, by=list(df1$State,df1$Name), FUN=sum)

so the grouped dataframe will be

**Method 2: groupby using dplyr**

group_by() function takes “State” and “Name” column as argument and groups by these two columns and summarise() uses sum() function to find sum of a sales.

library(dplyr) df1 %>% group_by(State,Name) %>% summarise(sum_sales = sum(Sales))

so the grouped dataframe by “State” and “Name” column with aggregated sum of sales will be

For further understanding of group_by() function in R using dplyr one can refer the dplyr documentation.