# Groupby minimum in R

Groupby minimum in R can be accomplished by aggregate() or group_by() function of dplyr package. Groupby minimum 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 min of single column in R
• Groupby min of multiple columns in R
• Groupby minimum using aggregate() function
• Groupby minimum using group_by() function.

Groupby minimum in R 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'),
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.

#### Method 1:

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

```# Groupby min of single column

aggregate(df1\$Sales, by=list(df1\$State), FUN=min)
```

so the grouped dataframe will be #### Method 2: groupby using dplyr

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

```library(dplyr)
df1 %>% group_by(State) %>% summarise(Min_sales = min(Sales))
```

so the grouped dataframe with minimum of sales calculated will be #### Method 1:

Aggregate function which is grouped by “State” and “Name”, along with function min is mentioned as shown below

```# Groupby min of multiple columns

aggregate(df1\$Sales, by=list(df1\$State,df1\$Name), FUN=min)
```

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 min() function to find minimum of a sales.

```library(dplyr)
df1 %>% group_by(State,Name) %>% summarise(Min_sales = min(Sales))
```

so the grouped dataframe will be For further understanding of group_by() function in R using dplyr one can refer the dplyr documentation