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# How to find the count of each category in a data.table object column in R?

To find the count of each category in a data.table object column in R, we can follow the below steps −

First of all, create a data.table object.

Then, use summarise function of dplyr package after grouping along with n.

## Example

#### Create the data.table object

Let’s create a data.table object as shown below −

library(data.table) factor<-sample(c("very low","low","medium","high","very high"),25,replace=TRUE) response<-rnorm(25) DT<-data.table(factor,response) DT

## Output

On executing, the above script generates the below output(this output will vary on your system due to randomization) −

factor response 1: very high -0.14064701 2: high -0.36029663 3: low -0.50825291 4: very high -2.07959316 5: high 0.25578922 6: very high 1.17946264 7: low 1.32803179 8: medium -0.23736325 9: medium -0.07440274 10: very low 0.32669673 11: very low 0.54953485 12: high -0.93197732 13: very high -0.77787846 14: very low 0.63808636 15: very high 0.76008767 16: very high -0.38712279 17: very high -0.64259955 18: high 0.30249791 19: high 0.16984229 20: very low -0.24732679 21: high -0.47456705 22: low 0.08789350 23: low 0.32541943 24: medium -0.27170782 25: high -0.09860207 factor response

**Find the count of each category in data.table object**

Using summarise function of dplyr package after grouping along with n to find the count of each category in factor column of data.table object DT −

library(data.table) factor<-sample(c("very low","low","medium","high","very high"),25,replace=TRUE) response<-rnorm(25) DT<-data.table(factor,response) library(dplyr) DT %>% group_by(factor) %>% summarise(count=n())

## Output

# A tibble: 5 x 2 factor count <chr> <int> 1 high 7 2 low 4 3 medium 3 4 very high 7 5 very low 4

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