To create a frequency table in R, you can use two different methods: the table() function and the dplyr package.

In this article, we will explore how to create frequency tables in R using these methods with examples.

Method 1: Use table() Function

The table() function in R is used to create a frequency table. Here’s the syntax:

table(vector)

The following example shows how to create a frequency table using the table() function:

Create Frequency Table Using table() Function

Let’s see how we can use the table() function to create a frequency table in R:

# Create data frame
df <- data.frame(Machine_name=c("A","B","C","D","E","F","G","H","A","B","A","C","D","B","E","H"),
                 Pressure=c(12.39,11.25,12.15,13.48,13.78,9.63,12.21,12.58,9.6,8.85,7.89,8.50,12.36,11.45,9.47,8.12),
                 Status=c("OK","Suspect","OK","OK","Suspect","Suspect","Suspect","OK","OK","OK","OK","OK","Suspect","Suspect","Suspect","OK"))

# Create frequency table
f <- table(df$Status)

# Show frequency table
print(f)

Output: 👇️

OK Suspect 
 9       7

Here the output shows the frequency table for the Status column of the data frame.

Method 2: Use dplyr Package

The dplyr package in R provides a powerful set of tools for data manipulation, including creating frequency tables. Here’s the syntax:

library(dplyr)

result <- df %>%
  group_by(column_name) %>%
  summarise(count = n())

The following example shows how to create a frequency table using the dplyr package:

Create Frequency Table Using dplyr Package

Let’s see how we can use the dplyr package in R to create a frequency table:

# Load dplyr package
library(dplyr)

# Create data frame
df <- data.frame(Machine_name=c("A","B","C","D","E","F","G","H","A","B","A","C","D","B","E","H"),
                 Pressure=c(12.39,11.25,12.15,13.48,13.78,9.63,12.21,12.58,9.6,8.85,7.89,8.50,12.36,11.45,9.47,8.12),
                 Status=c("OK","Suspect","OK","OK","Suspect","Suspect","Suspect","OK","OK","OK","OK","OK","Suspect","Suspect","Suspect","OK"))

# Create frequency table
freq_table <- df %>%
  group_by(Status) %>%
  summarise(count = n())

# Display frequency table
print(freq_table)

Output: 👇️

# A tibble: 2 × 2
  Status  count
  <chr>   <int>
1 OK          9
2 Suspect     7

In this example, the dplyr package is used to group the data by the Status column and then summarize the count of each unique value.