How to use Summary Function in R?

In this article, we will discuss the Summary Function in R Programming Language.

Summary function is used to return the following from the given data.

• Min: The minimum value in the given data
• 1st Qu: The value of the 1st quartile (25th percentile) in the given data
• Median: The median value in the given data
• 3rd Qu: The value of the 3rd quartile (75th percentile) in the given data
• Max: The maximum value in the given data

Syntax:

summary(data)

Where, data can be a vector, dataframe, etc.

Example 1: Using summary() with Vector

Here we are going to create a vector with some elements and get the summary statistics.

R

# create a vector with 10 elements
data = c(1: 5, 56, 43, 56, 78, 51)

# display
print(data)

# get summary
print(summary(data))

Output:

Example 2: Using summary() with DataFrame

Here we are going to get the summary of all columns in the dataframe.

R

# create a dataframe with 3 columns
data = data.frame(col1=c(1: 5, 56, 43, 56, 78, 51),
                  col2=c(100: 104, 56, 43, 56, 78, 51),
                  col3=c(1: 5, 34, 56, 78, 76, 79))

# display
print(data)

# get summary
print(summary(data))

Output:

Example 3: Using summary() with Specific DataFrame Columns

Here we can get summary of particular columns of the dataframe.

Syntax:

summary(dataframe)

R

# create a dataframe with 3 columns
data = data.frame(col1=c(1: 5, 56, 43, 56, 78, 51),
                  col2=c(100: 104, 56, 43, 56, 78, 51),
                  col3=c(1: 5, 34, 56, 78, 76, 79))

# display
print(data)

# get summary of column 1 and column 3
print(summary(data[c('col1', 'col3')]))

Output:

Example 4: Using summary() with Regression Model

Here we can also calculate summary() for linear regression model. We can create an linear regression model for dataframe columns using lm() function.

Syntax:

summary(lm(column1~column2, dataframe))

R

# create a dataframe with 3 columns
data = data.frame(col1=c(1: 5, 56, 43, 56, 78, 51),
                  col2=c(100: 104, 56, 43, 56, 78, 51))

# create the model for regression with 2 columns
reg = lm(col1~col2, data)

# get summary of the model
summary(reg)

Output:

Example 5: Using summary() with ANOVA Model

Here aov() is used to create anova model which stands for analysis of variance.

Syntax:

summary(aov(col1 ~ col2, data))

Example:

R

# create a dataframe with 3 columns
data = data.frame(col1=c(1: 5, 56, 43, 56, 78, 51),
                  col2=c(100: 104, 56, 43, 56, 78, 51))

# create the model for anova model with 2 columns
reg = aov(col1 ~ col2, data)

# get summary of the model
summary(reg)

Output: