# How do I count the number of occurrences in a column in R?

Groupby count in R can be accomplished by aggregate() or group_by() function of dplyr package. Groupby count of multiple column and single column in R is accomplished by multiple w

Groupby count in R can be accomplished by aggregate() or group_by() function of dplyr package. Groupby count 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 count the number of occurrences within a group using aggregate() function in R. Lets see how to

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

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

First lets create a dataframedf1= 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)**Xan R object, Mostly a dataframebya list of grouping elements, by which the subsets are grouped byFUNa function to compute the summary statisticssimplifya logical indicating whether results should be simplified to a vector or matrix if possibledropa logical indicating whether to drop unused combinations of grouping values.

**Groupby count of single column in R**

**Method 1:**

Aggregate function along with parameter by by which it is to be grouped and function length, is mentioned as shown below# Groupby count of single column aggregate(df1$Sales, by=list(df1$State), FUN=length)

so the grouped dataframe will be

**Method 2: groupby using dplyr**

group_by() function takes state column as argument summarise() uses n() function to find count of sales.library(dplyr) df1 %>% group_by(State) %>% summarise(count_sales = n())

so the grouped dataframe will be

**Groupby count of multiple column in R**

**Method 1:**

aggregate() function which is grouped by State and Name, along with function length is mentioned as shown below# Groupby count of multiple columns aggregate(df1$Sales, by=list(df1$State,df1$Name), FUN=length)

so the grouped dataframe will be

**Method 2: groupby using dplyr**

group_by() function along with n() is used to count the number of occurrences of the group in R. group_by() function takes State and Name column as argument and groups by these two columns and summarise() uses n() function to find count of a sales.library(dplyr) df1 %>% group_by(State,Name) %>% summarise(count_sales = n())

so the grouped dataframe by State and Name column with aggregated count of sales will be

For further understanding of group by count() function in R using dplyr one can refer the dplyr documentation

**Related Topics:**

- Groupby maximum in R
- Groupby minimum in R
- Groupby mean in R
- Groupby sum in R
- Row wise Standard deviation row Standard deviation in R dataframe
- Row wise Variance row Variance in R dataframe
- Row wise median row median in R dataframe
- Row wise maximum row max in R dataframe
- Row wise minimum row min in R dataframe

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