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R Analyst – Included R packages
The R Analyst app for the Android device, iPad and iPhone includes over 150 packages that extend the R (3.1.2, for Android is 3.5.1) functionality of R Analyst in multiple directions. The attached Numbers and Excel workbooks list the included packages in several formats:
A Sorted list- generated using a simple ‘installed.packages()’ call
Package Titles and Descriptions – Extracted from the library DESCRIPTION file using the ‘installed.packages()’ command.
Tidyverse packages – Hadley Wickham et.al. have developed a comprehensive set of packages to handle data reading, manipulation, and display.
Task View packages – CRAN includes a set of Task Views. This page lists the packages under each task view. Note that not all of the included packages have been assigned Task Views
Note: Although there are many more packages (>11,000) available in CRAN, Apple does not allow packages that contain compiled code libraries (e.g. “Needs Compilation : Yes” on the DESCRIPTION file). Pure R source code can be added via iTunes sharing or 3rd party apps, or added within R itself using ‘download.file()’ and related functions. Sites such as CRANhttps://cran.r-project.org and rdrrhttps://rdrr.io offer search functions
Analyser is a broad and deep statistics, machine learning and Data Science app for on-iPad or on-iPhone analyses. For someone looking to augment or replace their laptop or desktop, it offers comprehensive app. The app includes
R 3.1.2: R is a first rate statistics and data analysis system, used by tens of thousands of statisticians and analysts. This implementation includes over 150 analysis packages, and allows you to import R source code packages for use on the iPad. It can read/write most data formats , including csv, tsv, xls, sas7bdat and sqlite databases to pass data the Python and included Statistics templates/procedures. Due to current Apple restrictions on apps, one cannot import compiled packages (e.g. packages that include C or Fortran pieces)
Python 3.5.1: Python is a powerful general purpose scripting language that has a large number of modules specifically for data analysis and machine learning, including such modules as Pandas, Numpy, Scipy, and Astropy. This distribution includes over 600 modules. Like R, you can add source code modules (“Pure Python”) to customize your analysis capabilities. As with R, you cannot add compiled packages.
Sqlite version 3: Sqlite is an embedded database package that supports multiple databases, and data tables within each database. It can use other sqlite databases (e.g. foobar.db created elsewhere), and import SAS datasets and libraries and csv files. The Sqlite engine supports encryption. These data tables can be used within all the analysis packages (R, Python, and the Statistics Procedures.) It also includes an SQL console to allow users to create new data tables or modify existing ones.
Statistics templates: As experienced analysts know, many analysis needs can be satisfied by a simple procedures. Analyser includes 14 pre-built procedures for these needs, similar to some of the base procedures in SAS or SPSS. They run from simple descriptive analyses and testing, through clustering, discrimination and multiple forms of regression (regular, nonlinear, logistic, proportional hazards and generalized linear models, as well as time series models. The results can be saved, printed, or passed to other apps or to cloud services like Dropbox.