How to use Describe() function with dataframe In R Language

Method 2: Using Describe() with fast parameter

In this method to create a summary table, the user needs to import and install the psych package in the current working R console and then call the describe() function of this package. This function should be passed with the name of the given data frame as the parameter to get the summary table in return for the data passed as its parameter in the R programming language.

Syntax to install and import the psych package in R console:

install.package("psych")
library("psych")

describe function:

This function provides the ones most useful for scale construction and item analysis in classic psychometrics.

Syntax:

describe(dataframe)

Parameters:

dataframe: is the input dataframe

Example:

In this example, we will be simply using the describe() function to get the summary of the given data frame with 5 rows and 4 columns in R language.

R

# load the library 
library(psych)  
  
# create dataframe 
data=data.frame(id=c(1,2,3,4,5), 
                subjects=c("java","java","python","python","R"), 
                marks=c(90,89,77,89,89), 
                percentage=c(78,89,66,78,90)) 
  
# get the summary table 
describe(data)

Output:

How to Create Summary Tables in R?

In this article, we will discuss how to create summary tables in R Programming Language.

The summary table contains the following information:

vars: represents the column number
n: represents the number of valid cases
mean: represents the mean value
median: represents the median value
trimmed: represents the trimmed mean
mad: represents the median absolute deviation
min: represents the minimum value
max: represents the maximum value
range: represents the range of values
skew: represents the skewness
kurtosis: represents the kurtosis
se: represents the standard error

Initial Data frame:

Let’s create a dataframe with 5 rows and 4 columns.

R

# create dataframe 
data = data.frame(id=c(1, 2, 3, 4, 5),  
                  subjects=c("java", "java", "python",  
                             "python", "R"),  
                  marks=c(90, 89, 77, 89, 89), 
                  percentage=c(78, 89, 66, 78, 90)) 
  
# display 
data 