Statology
statology.org › home › how to use summary() function in r (with examples)
How to Use summary() Function in R (With Examples)
August 18, 2021 - :86.0 Min. :24.0 1st Qu.:88.0 1st Qu.:24.0 Median :90.0 Median :28.0 Mean :91.6 Mean :26.8 3rd Qu.:95.0 3rd Qu.:28.0 Max. :99.0 Max. :30.0 · The following code shows how to use the summary() function to summarize the results of a linear regression model:
RDocumentation
rdocumentation.org › packages › base › versions › 3.6.2 › topics › summary
summary function - RDocumentation
summary is a generic function used to produce result summaries of the results of various model fitting functions. The function invokes particular methods which depend on the class of the first argument.
13:03
R Basics 20: Descriptive Statistics using the summary function ...
12:12
Gentle R #4: Basic Summary Statistics in R with R Studio - YouTube
05:51
summary Function in R (3 Examples) | Descriptive Statistics of ...
Easy Summary Tables in R with gtsummary
The Summary Function in R - YouTube
04:26
Creating rapid summary table showing mean and standard ...
How can a user get a summary in r programming?
A user gets a summary in R programming by using the summary function with a numerical vector (or a group of numerical vectors such as columns in a data frame). The summary function returns the minimum, maximum, mean, median, and 1st and 3rd quartiles for a numerical vector.
study.com
study.com › computer science courses › computer science 114: programming in r
Summary Function in R Programming | Overview & Example - Lesson ...
What does the "group_by" mean in r programming?
The group_by function in R programming specifies a data frame as having one primary variable act as an organizing variable. It works together with other functions (such as summarize) to re-organize data frames and to calculate statistics based on the variable specified by group_by.
study.com
study.com › computer science courses › computer science 114: programming in r
Summary Function in R Programming | Overview & Example - Lesson ...
Is it possible to "sum" all values in r programming?
One can sum a string of values in R programming using the sum function. The sum function is used on a numerical vector, which refers to a group containing only numbers. One can also use the column function to add up the numbers in a column (or all of the columns) in a data frame.
study.com
study.com › computer science courses › computer science 114: programming in r
Summary Function in R Programming | Overview & Example - Lesson ...
GeeksforGeeks
geeksforgeeks.org › r language › how-to-use-summary-function-in-r
How to use Summary Function in R? - GeeksforGeeks
July 23, 2025 - In this article, we will explore the summary() function in the R programming language. Here we are going to create a vector with some elements and get the summary statistics using the summary() function. ... Here we are going to get the summary of all columns in the dataframe. ... 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)) print(data) print(summary(data))
CRAN
cran.r-project.org › web › packages › vtable › vignettes › sumtable.html
sumtable: Summary Statistics - CRAN - R Project
However, generally you can leave ... (in RStudio) or the browser (otherwise). This will also include some additional information about your data that can’t be demonstrated in this vignette: The data argument can take any data.frame, data.table, tibble, or matrix, as long as it has a valid set of variable names stored in the colnames() attribute. By default, sumtable will include in the summary statistics table every variable in the data set that is (1) numeric, ...
Tidyverse
dplyr.tidyverse.org › reference › summarise.html
Summarise each group down to one row — summarise • dplyr
summarise() creates a new data frame. It returns one row for each combination of grouping variables; if there are no grouping variables, the output will have a single row summarising all observations in the input.
Datanovia
datanovia.com › home › lessons › compute summary statistics in r
Compute Summary Statistics in R - Datanovia.com
December 3, 2019 - Compute summary statistics for ungrouped data, as well as, for data that are grouped by one or multiple variables. R functions: summarise() and group_by().
Rfaqs
rfaqs.com › r-language-basics › summary-function-in-r
Mastering summary() Function in R: Easy Data Insights 2025
March 11, 2025 - $ vs : num 0 0 1 1 0 1 0 1 1 1 ... $ am : num 1 1 1 0 0 0 0 0 0 0 ... $ gear: num 4 4 4 3 3 3 3 4 4 4 ... $ carb: num 4 4 1 1 2 1 4 2 2 4 ... summary(mtcars) Use summary() for Data Cleaning Look for missing values (NA) in the summary output. This can help you identify columns that require imputation or removal.
Study.com
study.com › computer science courses › computer science 114: programming in r
Summary Function in R Programming | Overview & Example - Lesson | Study.com
July 27, 2020 - The summary function in R returns the results of basic statistical calculations (minimum, 1st quartile, median, mean, 3rd quartile, and maximum) for a numerical vector. The general way to write the R summary function is summary(x, na.rm=FALSE/TRUE).
ETH Zurich
stat.ethz.ch › R-manual › R-devel › library › base › html › summary.html
R: Object Summaries
The form of the value returned by summary depends on the class of its argument.
Csu-r
csu-r.github.io › Module1 › summary-statistics.html
5.3 Summary Statistics | R Module 1
Reading and writing data is useful, but the power of R is doing interesting things with the data! Let’s perform a few operations with the Olympic athletes data to demonstrate some important functions for data analysis. As we’ve seen, the summary function automatically performs some summary statistics on each column of a data frame.
RDocumentation
rdocumentation.org › packages › Hmisc › versions › 4.4-2 › topics › summarize
summarize function - RDocumentation
The outer quartiles are # displayed using "error bars" set.seed(111) dfr <- expand.grid(month=1:12, year=c(1997,1998), reps=1:100) attach(dfr) y <- abs(month-6.5) + 2*runif(length(month)) + year-1997 s <- summarize(y, llist(month,year), smedian.hilow, conf.int=.5) s mApply(y, llist(month,year), smedian.hilow, conf.int=.5) xYplot(Cbind(y,Lower,Upper) ~ month, groups=year, data=s, keys='lines', method='alt') # Can also do: s <- summarize(y, llist(month,year), quantile, probs=c(.5,.25,.75), stat.name=c('y','Q1','Q3')) xYplot(Cbind(y, Q1, Q3) ~ month, groups=year, data=s, keys='lines') # To displa
Danieldsjoberg
danieldsjoberg.com › gtsummary
Presentation-Ready Data Summary and Analytic Result Tables • gtsummary
Summarize data frames or tibbles easily in R. Perfect for presenting descriptive statistics, comparing group demographics (e.g creating a Table 1 for medical journals), and more.
Educative
educative.io › answers › what-is-the-summarize-method-in-r
What is the summarize() method in R?
The summary() function is used to summarize the data from a DataFrame and returns a statistical inference of the DataFrame such as mean, median, minimum, maximum, 1st and 3rd quartiles.
Statistics LibreTexts
stats.libretexts.org › bookshelves › applied statistics › learning statistics with r - a tutorial for psychology students and other beginners (navarro) › 5: descriptive statistics
5.4: Getting an Overall Summary of a Variable - Statistics LibreTexts
January 8, 2024 - The describe() function (in the psych package) is a little different, and it’s really only intended to be useful when your data are interval or ratio scale. Unlike the summary() function, it calculates the same descriptive statistics for any type of variable you give it. By default, these are: var. This is just an index: 1 for the first variable, 2 for the second variable, and so on.
Statology
statology.org › home › how to use the summarize() function in r
How to Use the summarize() Function in R
April 3, 2024 - #calculate mean of mpg column mtcars %>% summarize(mean_mpg = mean(mpg, na.rm = TRUE)) mean_mpg 1 20.09062
Top answer 1 of 15
152
1. tapply
I'll put in my two cents for tapply().
tapply(df$dt, df$group, summary)
You could write a custom function with the specific statistics you want or format the results:
tapply(df$dt, df$group,
function(x) format(summary(x), scientific = TRUE))
$A
Min. 1st Qu. Median Mean 3rd Qu. Max.
"5.900e+01" "5.975e+01" "6.100e+01" "6.100e+01" "6.225e+01" "6.300e+01"
$B
Min. 1st Qu. Median Mean 3rd Qu. Max.
"6.300e+01" "6.425e+01" "6.550e+01" "6.600e+01" "6.675e+01" "7.100e+01"
$C
Min. 1st Qu. Median Mean 3rd Qu. Max.
"6.600e+01" "6.725e+01" "6.800e+01" "6.800e+01" "6.800e+01" "7.100e+01"
$D
Min. 1st Qu. Median Mean 3rd Qu. Max.
"5.600e+01" "5.975e+01" "6.150e+01" "6.100e+01" "6.300e+01" "6.400e+01"
2. data.table
The data.table package offers a lot of helpful and fast tools for these types of operation:
library(data.table)
setDT(df)
> df[, as.list(summary(dt)), by = group]
group Min. 1st Qu. Median Mean 3rd Qu. Max.
1: A 59 59.75 61.0 61 62.25 63
2: B 63 64.25 65.5 66 66.75 71
3: C 66 67.25 68.0 68 68.00 71
4: D 56 59.75 61.5 61 63.00 64
2 of 15
71
dplyr package could be nice alternative to this problem:
library(dplyr)
df %>%
group_by(group) %>%
summarize(mean = mean(dt),
sum = sum(dt))
To get 1st quadrant and 3rd quadrant
df %>%
group_by(group) %>%
summarize(q1 = quantile(dt, 0.25),
q3 = quantile(dt, 0.75))
Learnbymarketing
learnbymarketing.com › tutorials › explaining-the-lm-summary-in-r
Explaining the lm() Summary in R – Learn by Marketing
> summary(model) Call: lm(formula = y ~ x1 + x2) Residuals: Min 1Q Median 3Q Max -1.69194 -0.61053 -0.08073 0.60553 1.61689 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.8278 1.7063 0.485 0.64058 x1 0.5299 0.1104 4.802 0.00135 ** x2 0.6443 0.4017 1.604 0.14744 --- Signif.
Ufl
users.phhp.ufl.edu › rlp176 › Courses › PHC6089 › R_notes › DataSummarization.html
Chapter 6 Data Summarization | R Lecture Notes
head(apply(avgs, 1 , mean, na.rm = T)) # row means ... 1990 1991 1992 1993 1994 1995 1996 1997 110.6440 112.7687 114.4853 116.6744 120.0931 122.7119 126.1800 131.0858 1998 1999 137.3754 146.0755 ... See more details here. These are commonly used, but we will discuss how to do all these using dplyr. The dplyr function summarize allows you to make a tibble containing your requested summary statistics.
RDocumentation
rdocumentation.org › packages › stats › versions › 3.6.2 › topics › summary.lm
summary.lm Summarizing Linear Model Fits
the above \(R^2\) statistic ‘adjusted’, penalizing for higher \(p\). cov.unscaled · a \(p \times p\) matrix of (unscaled) covariances of the \(\hat\beta_j\), \(j=1, \dots, p\). correlation · the correlation matrix corresponding to the above cov.unscaled, if correlation = TRUE is specified. symbolic.cor · (only if correlation is true.) The value of the argument symbolic.cor. na.action · from object, if present there. print.summary.lm tries to be smart about formatting the coefficients, standard errors, etc.
UCLA
math.ucla.edu › ~anderson › rw1001 › library › base › html › summary.html
R: Object Summaries
summary is a generic function used to produce result summaries of the results of various model fitting functions. The function invokes particular methods which depend on the class of the first argument. summary(object, ...) summary.default (object, ..., digits = max(3, getOption("digits") -3)) ...