groupedstats | Grouped statistical analysis in a tidy way | Analytics library

by IndrajeetPatil R Version: 2.1.0 License: GPL-3.0

X-Ray Key Features Code Snippets(3)Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | groupedstats Summary

groupedstats is a R library typically used in Analytics applications. groupedstats has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

groupedstats package provides a collection of functions to run statistical operations on multiple variables across multiple grouping variables in a dataframe. This is a common situation, as illustrated by few example cases-.

Support

Quality

Security

License

Reuse

Support

groupedstats has a low active ecosystem.

It has 46 star(s) with 10 fork(s). There are 3 watchers for this library.

It had no major release in the last 12 months.

There are 1 open issues and 13 have been closed. On average issues are closed in 77 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of groupedstats is 2.1.0

Quality

groupedstats has no bugs reported.

Security

groupedstats has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

groupedstats is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

groupedstats releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of groupedstats

Get all kandi verified functions for this library.

groupedstats Key Features

No Key Features are available at this moment for groupedstats.

groupedstats Examples and Code Snippets

Usage,grouped_wilcox

Lines of Code : 194

License : Strong Copyleft (GPL-3.0)

Copy

# for reproducibility
set.seed(123)
options(tibble.width = Inf) # show me all columns

groupedstats::grouped_wilcox(
  data = iris_long,
  dep.vars = value, # dependent variable
  indep.vars = part, # independent variable
  grouping.vars = c(Species,

Usage,grouped_summary

Lines of Code : 193

License : Strong Copyleft (GPL-3.0)

Copy

# for reproducibility
set.seed(123)
library(datasets)
options(tibble.width = Inf) # show me all columns

# note that this dataset has NAs
groupedstats::grouped_summary(
  data = ggplot2::msleep,
  grouping.vars = vore,
  measures = sleep_total:awake,

Usage,grouped_slr

Lines of Code : 76

License : Strong Copyleft (GPL-3.0)

Copy

# for reproducibility
set.seed(123)
library(gapminder)
options(tibble.width = Inf) # show me all columns

groupedstats::grouped_slr(
  data = gapminder::gapminder,
  dep.vars = c(lifeExp, pop),
  indep.vars = c(gdpPercap, gdpPercap),
  grouping.vars

Community Discussions

Trending Discussions on groupedstats

reexporting datasets in r packages

converting call to equation in r markdown

setting list element names based on argument to `pmap`

QUESTION

reexporting datasets in r packages

Asked 2020-Feb-04 at 21:37

In R packages, there is a possibility of reexporting functions. This makes it easy to recycle the same function without having to repeat the code across different packages.

For example, devtools::session_info function is a reexport of sessioninfo::session_info:

...

ANSWER

Answered 2020-Feb-04 at 21:37

Data is searched for in a loaded package in a different fashion from the namespace for functions, so it's not technically an export. But you can re-export another package's dataset, which will operate in the same way with one exception: it will not be found using the data() function, which just searches the data/ directory for data objects. The example below:

will work as if it were a "lazy loaded" dataset, e.g. myiris if your package is attached, or using yourpackage::myiris;

will not work with data(myiris, package = "yourpackage").

Source https://stackoverflow.com/questions/52690307

QUESTION

converting call to equation in r markdown

Asked 2019-Jun-13 at 16:16

I have written the ggstatsplot package to carry out some statistical analysis. The package functions (in the development version) can either return a plot or a call that contains statistical details displayed in the subtitle of the plot.

Here is an example of a plot as a return:

...

ANSWER

Answered 2019-Jun-13 at 16:16

It is pretty easy to convert your example to Markdown code. This is nowhere near general, but it is kind of obvious how to extend it to handle other expressions.

The idea is to evaluate the plotmath expression to form a string that is Markdown. For example, use this function:

Source https://stackoverflow.com/questions/56568767

QUESTION

setting list element names based on argument to `pmap`

Asked 2018-Nov-02 at 06:46

I am trying to figure out if I can use the list of arguments provided to purrr::pmap() to also name the elements of the output list from this function using purrr::set_names().

For example, here is a simple example where I am using pmap to create summary for some variables from different dataframes across grouping variables.

...

ANSWER

Answered 2018-Nov-02 at 06:46

From tidyverse package, you can also use lst function. lst is used for creating list. It is like tibble function to create tibble but for creating list. One of the difference with base list() is that it automatically names the list. It is in dplyr, exported from tibble.

For the example, I also replace base alist by rlang::exprs as it is equivalent. Indeed, both are ok.

Source https://stackoverflow.com/questions/53092549

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install groupedstats

To get the latest, stable CRAN release:. You can get the development version of the package from GitHub. To see what new changes (and bug fixes) have been made to the package since the last release on CRAN, you can check the detailed log of changes here: https://indrajeetpatil.github.io/groupedstats/news/index.html. If you are in hurry and want to reduce the time of installation, prefer-. If time is not a constraint-.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: