What is the summary() Function in R

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The summary() function in R is “used to produce result summaries of the results of various model fitting functions“. It is done by grouping observations by using categorical values at first, using the groupby() function.

The summary() function returns the following statistics.

  1. Minimum value
  2. The first quartile (25th percentile)
  3. Median (50th percentile)
  4. Mean
  5. Third quartile (75th percentile)
  6. Maximum value

Syntax

summary(data, maxsum)

Parameters

data: It is an R object for which you want a summary.

maxsum: An integer suggests how many levels should be shown for factors.

Return Value

The summary() function returns the value that depends on the class of its argument.

Example 1: Using summary() with data frame

To get the summary of a “data frame” in R, you can use the “summary()” function.

df <- data.frame(
  service_id = c(1:5),
  service_name = c("Netflix", "Disney+", "HBOMAX", "Hulu", "Peacock"),
  service_price = c(18, 10, 15, 7, 12),
  stringsAsFactors = FALSE
)

cat("The summary() of data frame is", "\n")
summary(df)

Output

The summary() of data frame is
service_id   service_name      service_price
Min. :1       Length:5           Min. : 7.0
1st Qu.:2     Class :character   1st Qu.:10.0
Median :3     Mode :character    Median :12.0
Mean :3                          Mean :12.4
3rd Qu.:4                        3rd Qu.:15.0
Max. :5                          Max. :18.0

Example 2: Using summary() with list

To get the summary of the list in R, you can use the “summary()” function.

vec <- 1:5
list <- list(vec)
cat("The summary() of list is", "\n")
summary(vec)

Output

The summary() of list is
Min. 1st Qu. Median Mean  3rd Qu. Max.
 1      2      3     3     4       5

Example 3: Using summary() with an array

To get the summary of an “array” in R, use the “summary()” function.

rv <- c(19, 21)
rv2 <- c(46, 4)
arr <- array(c(rv, rv2), dim = c(2, 2, 2))

cat("The summary() of array is", "\n")

summary(arr)

Output

The summary() of array is
 Min.  1st Qu. Median  Mean   3rd Qu.  Max.
 4.00  15.25   20.00   22.50  27.25   46.00

Example 4: Using summary() with matrix

To get a summary of a “matrix” in R, use the “summary()” function.

rv <- c(11, 18, 19, 21)
mtrx <- matrix(rv, nrow = 2, ncol = 2)

cat("The summary() of matrix is", "\n")

summary(mtrx)

Output

The summary() of matrix is
    V1               V2
Min. :11.00       Min. :19.0
1st Qu.:12.75     1st Qu.:19.5
Median :14.50     Median :20.0
Mean :14.50       Mean :20.0
3rd Qu.:16.25     3rd Qu.:20.5
Max. :18.00       Max. :21.0

Example 5: Using summary() with vector

vec <- 1:5
vec

cat("The summary() of vector is", "\n")

summary(vec)

Output

[1] 1 2 3 4 5
The summary() of vector is
Min. 1st Quantile  Median  Mean  3rd Quantile   Max.
1       2             3      3         4         5

As you can see from the output, a vector’s summary() returns descriptive statistics such as the minimum, the 1st quantile, the median, the mean, the 3rd quantile, and the maximum value of our input data.

Example 6: Using summary() with Linear Regression Model

Linear regression attempts to model the relationship between two variables by fitting a linear equation to observed data. One variable is considered an explanatory variable, and the other is a dependent variable.

A widespread application of the summary functions is the computation of summary statistics of statistical models. For example, let’s see the following code.

set.seed(93274)
l_x <- rnorm(1000)
l_y <- rnorm(1000) + l_x

mod <- lm(l_y ~ l_x)

summary(mod)

Output

Call:
lm(formula = l_y ~ l_x)

Residuals:
 Min 1Q Median 3Q Max
-3.7337 -0.6964 -0.0047 0.7333 3.3489

Coefficients:
 Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.02159 0.03292 -0.656 0.512
l_x 1.00156 0.03262 30.707 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.041 on 998 degrees of freedom
Multiple R-squared: 0.4858, Adjusted R-squared: 0.4853
F-statistic: 942.9 on 1 and 998 DF, p-value: < 2.2e-16

We applied the summary() function to this model object to print summary statistics for this model.

That’s it.

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