In this article, we will learn about the summary() function in R and how to use this function with different types of input data. Let’s go into detail now.
What is the summary() function in R?
The summary() function is used to generate a summary of the results of statistical calculations that summarize data and model objects.
Syntax:
summary(data)
Parameter:
- data: a vector, data frame, linear regression model,…
The return value of the summary() function in R will depend on the data type being processed.
How to use this function in R?
We will give four specific examples of how to use the summary() function in R.
The input data is a vector
First, we create a numeric vector named ‘dt’ containing the first ten elements of the Fibonacci sequence:
0, 1, 1, 2, 3, 5, 8, 13, 21, 34
Finally, use the summary() function to get the vector ‘dt’ summary.
Code:
# Create a vector containing the first ten elements of the Fibonacci sequence fibo = c(0, 1, 1, 2, 3, 5, 8, 13, 21, 34) print(fibo) # Get the summary of the 'fibo' vector summaryFibo <- summary(fibo) print(summaryFibo)
Output:
[1] 0 1 1 2 3 5 8 13 21 34
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.00 1.25 4.00 8.80 11.75 34.00 The summary() function returns 6 parameters:
Min. The minimum value
1st Qu. The first quantile value
Median The median value
Mean The mean value
3rd Qu. The third quantile value
Max. The maximum value
The input data is a data frame
We have a data frame named ‘score’ that contains the names and test scores of some students in our class.
We will use the summary() function to get a summary of all the columns belonging to ‘score’.
Example:
# Create the 'score' data frame
score <-data.frame(
Name = c("Alice", "Layla", "Parker", "Loren", "Granger"),
Math = c(45, 78, 30, 69, 64),
English = c(58, 55, 62, 87, 54),
Physics = c(88, 43, 63, 51, 28)
)
# Get the summary of the 'score' data frame
summaryScore <- summary(score)
print(summaryScore)Output:
Name Math English Physics
Length:5 Min. :30.0 Min. :54.0 Min. :28.0
Class :character 1st Qu.:45.0 1st Qu.:55.0 1st Qu.:43.0
Mode :character Median :64.0 Median :58.0 Median :51.0
Mean :57.2 Mean :63.2 Mean :54.6
3rd Qu.:69.0 3rd Qu.:62.0 3rd Qu.:63.0
Max. :78.0 Max. :87.0 Max. :88.0 The input data is some columns of the data frame
With the above data frame, assuming you only want to get the summary of the Math, English, and Physics columns, you can do the following:
# Create the 'score' data frame
score <-data.frame(
Name = c("Alice", "Layla", "Parker", "Loren", "Granger"),
Math = c(45, 78, 30, 69, 64),
English = c(58, 55, 62, 87, 54),
Physics = c(88, 43, 63, 51, 28)
)
# Get the summary of some columns on the 'score' data frame
summaryScore <- summary(score[c('Math', 'English', 'Physics')])
print(summaryScore)Output:
Math English Physics
Min. :30.0 Min. :54.0 Min. :28.0
1st Qu.:45.0 1st Qu.:55.0 1st Qu.:43.0
Median :64.0 Median :58.0 Median :51.0
Mean :57.2 Mean :63.2 Mean :54.6
3rd Qu.:69.0 3rd Qu.:62.0 3rd Qu.:63.0
Max. :78.0 Max. :87.0 Max. :88.0The input data is a linear regression model
Example:
# Create a data frame dataframe <- data.frame(x = c(1, 2, 3), y = c(9, 8, 7)) # Fit a linear model result <- lm(y ~ x, dataframe) # Summary of the model's performance and coefficients summaryResult <- summary(result) print(summaryResult)
Output:
Call:
lm(formula = y ~ x, data = dataframe)
Residuals:
1 2 3
2.719e-16 -5.439e-16 2.719e-16
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.000e+01 1.018e-15 9.828e+15 <2e-16 ***
x -1.000e+00 4.710e-16 -2.123e+15 3e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 6.661e-16 on 1 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: 1
F-statistic: 4.507e+30 on 1 and 1 DF, p-value: 2.999e-16We do linear regression on the data frame using the lm() function in R.
The summary() function lets you see detailed information on the model’s performance and coefficients. Click here for details of the coefficients included in the summary.
Summary
We have learned about the summary() function in R and how to use it with different input data types. The return value of this function in R will depend on the data type being processed. We hope the information in this article will be helpful to you. Thank you for reading.
Maybe you are interested:
- The gather() function in R
- The seq Function in R: How to use seq() in R
- The attach() Function In R: How To Use attach() In R
Hello, my name’s Bruce Warren. You can call me Bruce. I’m interested in programming languages, so I am here to share my knowledge of programming languages with you, especially knowledge of C, C++, Java, JS, PHP.
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