Danieldsjoberg
danieldsjoberg.com › gtsummary › reference › tbl_summary.html
Summary table — tbl_summary • gtsummary
Named lists are also accepted to change the default formatting for a single statistic, e.g. list(sd = label_style_number(digits=1)). There are four summary types.
Danieldsjoberg
danieldsjoberg.com › gtsummary
Presentation-Ready Data Summary and Analytic Result Tables • gtsummary
Use tbl_summary() to summarize a data frame.
Modelsummary
modelsummary.com › vignettes › datasummary.html
Data Summaries – modelsummary: Data and Model Summaries in R
To summarize the numeric variables in the dataset, we type: ... The expressions “balance table” or “Table 1” refer to a type of table which is often printed in the opening pages of a scientific peer-reviewed article. Typically, this table includes basic descriptive statistics about different subsets of the study population.
R Project
search.r-project.org › CRAN › refmans › gtsummary › html › tbl_summary.html
R: Summary table
Named lists are also accepted to change the default formatting for a single statistic, e.g. list(sd = label_style_number(digits=1)). There are four summary types.
Tidyverse
dplyr.tidyverse.org › reference › summarise.html
Summarise each group down to one row — summarise • dplyr
This was the only supported option before version 1.0.0. ... When .groups is not specified, it is set to "drop_last" for a grouped data frame, and "keep" for a rowwise data frame. In addition, a message informs you of how the result will be grouped unless the result is ungrouped, the option "dplyr.summarise...
Danieldsjoberg
danieldsjoberg.com › gtsummary › articles › tbl_summary.html
tbl_summary() tutorial • gtsummary
head(trial) #> # A tibble: 6 × 8 #> trt age marker stage grade response death ttdeath #> <chr> <dbl> <dbl> <fct> <fct> <int> <int> <dbl> #> 1 Drug A 23 0.16 T1 II 0 0 24 #> 2 Drug B 9 1.11 T2 I 1 0 24 #> 3 Drug A 31 0.277 T1 II 0 0 24 #> 4 Drug A NA 2.07 T3 III 1 1 17.6 #> 5 Drug A 51 2.77 T4 III 1 1 16.4 #> 6 Drug B 39 0.613 T4 I 0 1 15.6 · The default output from tbl_summary() is meant to be publication ready.
Datanovia
datanovia.com › home › lessons › compute summary statistics in r
Compute Summary Statistics in R - Datanovia.com
December 3, 2019 - In this tutorial, we describe how to easily compute statistical summaries using the R functions summarise() and group_by() [in dplyr package].
R-bloggers
r-bloggers.com › r bloggers › r tutorial series: summary and descriptive statistics
R Tutorial Series: Summary and Descriptive Statistics | R-bloggers
May 11, 2011 - Posted on November 1, 2009 by John M. Quick in R bloggers | 0 Comments · [This article was first published on R Tutorial Series, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. ... Summary (or descriptive) statistics are the first figures used to represent nearly every dataset.
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 - :1.8000 · Evidently there were three drugs: a placebo, something called “anxifree” and something called “joyzepam”; and there were 6 people administered each drug. There were 9 people treated using cognitive behavioural therapy (CBT) and 9 people who received no psychological treatment. And we can see from looking at the summary of the mood.gain variable that most people did show a mood gain (mean =.88), though without knowing what the scale is here it’s hard to say much more than that.
Introduction to R
intro2r.com › summarising-data-frames.html
3.5 Summarising data frames | An Introduction to R
A really useful starting point is to produce some simple summary statistics of all of the variables in our flowers data frame using the summary() function. summary(flowers) ## treat nitrogen block height weight leafarea shootarea flowers ## Length:96 low :32 Min. :1.0 Min.
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 - #define data frame df <- data.frame(team=c('A', 'B', 'C', 'D', 'E'), points=c(99, 90, 86, 88, 95), assists=c(33, 28, 31, 39, 34), rebounds=c(30, 28, 24, 24, 28)) #summarize every column in data frame summary(df) team points assists rebounds Length:5 Min. :86.0 Min. :28 Min. :24.0 Class :character 1st Qu.:88.0 1st Qu.:31 1st Qu.:24.0 Mode :character Median :90.0 Median :33 Median :28.0 Mean :91.6 Mean :33 Mean :26.8 3rd Qu.:95.0 3rd Qu.:34 3rd Qu.:28.0 Max.
Ufl
users.phhp.ufl.edu › rlp176 › Courses › PHC6089 › R_notes › DataSummarization.html
Chapter 6 Data Summarization | R Lecture Notes
# A tibble: 17 × 2 YEAR year_avg <dbl> <dbl> 1 1999 14.6 2 2000 12.5 3 2001 9.84 4 2002 9.60 5 2003 7.49 6 2004 8.2 7 2005 7.27 8 2006 7.37 9 2007 6.68 10 2008 5.95 11 2009 5.84 12 2010 5.6 13 2011 5.15 14 2012 4.72 15 2013 3.76 16 2014 2.93 17 2015 2.86 · We can also use the pipe to pipe sub_yts into group_by and then into summarize.
CRAN
cran.r-project.org › web › packages › vtable › vignettes › sumtable.html
sumtable: Summary Statistics - CRAN - R Project
Cols 1 and 2 are count and percentage. ## Beware combining factors with a custom summ unless factor.numeric = TRUE. sumtable() allows for the calculation of summary statistics by group. group is a character variable containing the column name in data that you want to calculate summary statistics separately for.
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.
Data Science Dojo
discuss.datasciencedojo.com › python
How to get summary statistics of a Pandas Dataframe in Python? - Python - Data Science Dojo Discussions
March 24, 2023 - In Pandas, is there a method to get summary statistics for all dataframe columns at once, or should I do it individually for each column? Having an overall data insight through collective statistics before detailed analysis is often beneficial. You can use the following sample dataframe that ...
Top answer 1 of 15
151
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))
Pandas
pandas.pydata.org › docs › reference › api › pandas.DataFrame.describe.html
pandas.DataFrame.describe — pandas 3.0.1 documentation
} ... ) >>> df.describe() numeric count 3.0 mean 2.0 std 1.0 min 1.0 25% 1.5 50% 2.0 75% 2.5 max 3.0
Pandas
pandas.pydata.org › docs › getting_started › intro_tutorials › 06_calculate_statistics.html
How to calculate summary statistics — pandas 3.0.2 documentation
More information is provided in the user guide Categorical data section. What is the mean ticket fare price for each of the sex and cabin class combinations? In [11]: titanic.groupby(["Sex", "Pclass"])["Fare"].mean() Out[11]: Sex Pclass female 1 106.125798 2 21.970121 3 16.118810 male 1 67.226127 2 19.741782 3 12.661633 Name: Fare, dtype: float64
GitHub
github.com › dcomtois › summarytools › blob › master › R › dfSummary.R
summarytools/R/dfSummary.R at master · dcomtois/summarytools
#' @seealso \code{\link{label}}, \code{\link{print.summarytools}} #' · #' @keywords univar attribute classes category · #' @author Dominic Comtois, \email{dominic.comtois@@gmail.com} #' @importFrom dplyr n_distinct group_keys · #' @importFrom tibble as_tibble · #' @importFrom stats start end · #' @importFrom grDevices dev.list dev.off · #' @export · dfSummary <- function(x, round.digits = 1, varnumbers = st_options("dfSummary.varnumbers"), class = st_options("dfSummary.class"),
Author dcomtois