Package 'Statsomat'

Title: Shiny Apps for Automated Data Analysis and Automated Interpretation
Description: Shiny apps for automated data analysis, annotated outputs and human-readable interpretation in natural language. Designed especially for learners and applied researchers. Currently available methods: EDA, EDA with Python, Correlation Analysis, Principal Components Analysis, Confirmatory Factor Analysis.
Authors: Denise Welsch [aut, cre] , Berit Hunsdieck [ctb], Omar Alhelal [ctb]
Maintainer: Denise Welsch <[email protected]>
License: AGPL
Version: 1.1.0
Built: 2025-02-09 04:16:53 UTC
Source: https://github.com/cran/Statsomat

Help Index

Confirmatory Factor Analysis

Description

A Shiny app for automated Confirmatory Factor Analysis (CFA) based on the R package lavaan. Single-group, first-order CFA for datasets up to 5000 observations, 25 (approximately) continuous variables and 5000 KB. An interpretation in natural language and the R Code to reproduce the results is included in the report. Run the app locally by calling the function or launch it directly in the web from https://statsomat.shinyapps.io/Confirmatory-Factor-Analysis. Follow the Instructions described in the GUI to use the app and generate a report. Check also the GitHub repository https://github.com/Statsomat/CFA.

Usage

cfa()

Value

Shiny app opens in viewer or browser.

Examples

## Not run: 
library(Statsomat)
cfa()

## End(Not run)

Correlation Analysis

Description

A Shiny app for automated Correlation Analysis for (approximately) continuous variables. An interpretation in plain English and the R Code to reproduce the results is included in the report. Run the app locally by calling the function or launch it directly in the web from https://statsomat.shinyapps.io/Correlations. Follow the Instructions described in the GUI to use the app and generate a report. Check also the GitHub repository https://github.com/Statsomat/CORRANA.

Usage

corrana()

Value

Shiny app opens in viewer or browser.

Examples

## Not run: 
library(Statsomat)
corrana()

## End(Not run)

Exploratory Data Analysis with Python

Description

A Shiny app for automated Exploratory Data Analysis with Python, based on the R interface to Python reticulate. Run the app locally by calling the function or launch it directly in the web from https://statsomat.shinyapps.io/edapy. Follow the Instructions in the GUI of the app to generate a PDF report or Python code to reproduce numerical and graphical results. Check also the GitHub repository of the app for more details https://github.com/Statsomat/edapy. System Requirements: Python >=3. Imports numpy, pandas, seaborn, matplotlib, scipy, statsmodels, tabulate, sys, warnings.

Usage

edapy()

Value

Shiny app opens in viewer or browser.

Examples

## Not run: 
library(Statsomat)
edapy()

## End(Not run)

Exploratory Data Analysis with R

Description

A Shiny app for automated Exploratory Data Analysis with R. Run the app locally by calling the function or launch it directly in the web from https://statsomat.shinyapps.io/Descriptive_statistics/. Follow the Instructions described in the GUI to use the app and generate a report. Check also the GitHub repository https://github.com/Statsomat/edar.

Usage

edar()

Value

Shiny app opens in viewer or browser.

Examples

## Not run: 
library(Statsomat)
edar()

## End(Not run)

Principal Components Analysis

Description

A Shiny app for automated Principal Components Analysis (PCA) based on the R package factominer. An interpretation in plain English and the R Code to reproduce the results is included in the report. Follow the Instructions on the webpage of the app https://statsomat.shinyapps.io/Principal-components-analysis/ to generate the report. Check also the GitHub repository https://github.com/Statsomat/PCA.

Usage

pca()

Value

Shiny app opens in viewer or browser.

Examples

## Not run: 
library(Statsomat)
pca()

## End(Not run)