R / PythonWhy and How to Get Started

What do you use?

• Use SPSS, Stata, or SAS

• with the GUI/menus

• with syntax

• Use Excel

• for data management

• for data analysis

• Use Matlab, R, or Python

Python

• General programming language• Create applications, run websites, interface with systems

• Has all the elements of other languages

• Created by groups of computer scientists• Runs fast and stable for production workflows

• Simplest of languages, one best way to do any action

R

• Statistical Language• Built to do math and work with datasets

• Can utilize some tools from other languages

• Created by statisticians • Fast and intuitive to do analysis, slower to process

• Many statisticians have increased it's capabilities

Both

• Use Scripting• The code/syntax is intended to be saved in a script file

• The code can be re-played to reproduce the output

• Open Source & Extensible• Anybody can create new add-ins ("packages")

• People can NOT change the original without permission

• Free to use

As originally built, you:

Type instructions at a prompt…

R Console

Python Shell

…and get output like this

R - Regression

Python - Frequency Table

IDEs

• Script Window

• Console

• Help

• History

• Files

• Plots

• Environment / Variable explorer

• Run current selection

Script

Script

Console

Console

Spyder (Python)

RStudio (R)

So, why all the buzz?

• Free software that can do everything SPSS, Stata, SAS, and Excel can do.

• Massive improvements in ease of use through packages with convenience functions.

What to Install

• R• Install R from CRAN

• Install RStudio

• Python• Install Anaconda

All of these are cross-platform with regular installers

No Installation Needed

• RStudio Cloud (beta)• https://rstudio.cloud/

• Python Anywhere• https://www.pythonanywhere.com/

• Both require free accounts.

Old and New

• R is an implementation of S (created in 1976) and was first released in 1995 with v1.0 in 2000.Hadley Wickham's dplyr package was introduced in 2014.The RStudio IDE was released in 2011 with v1.0 in 2016.

• Python was created in 1990. The interactive shell was released in 2001. The data management package Pandas was first released by Wes McKinney in 2008; v1.0 was released in 2020.The Spyder IDE was released in 2009.

Misconceptions

• Python is better than R• Python can do a wider variety of computer tasks than R.

Python has Breadth, R has Depth in Data/Statistics

• The languages themselves are not what people are judging, they are judging the entire ecosystem.

• Python is easier than R• Python is the simplest of the programming languages.

R is not a programming language.

• Since R was made by Statisticians, it does some things different than other general programming languages.

Demonstration

• Python

• R

Functions & PackagesThe building blocks of computer languages

Have you used Functions?

word(stuff)

Have you used Functions?

word(stuff)

=AVERAGE(V1:V5)

COMPUTE average = MEAN(v1, v2, v3, v4, v5).

egen average = rowmean(v1 v2 v3 v4 v5)

average = mean(of v1-v5);

Creating a Scale Index

ncc_score = (ncc1 + ncc2 + ncc3 + ncc4 + ncc5) / 5

ncc_score = SUM(ncc1, ncc2, ncc3, ncc4, ncc5) / 5

ncc_score = MEAN(ncc1, ncc2, ncc3, ncc4, ncc5)

ncc_score = SCALE(ncc)

ncc_score = SCALE(ncc, "sum")

"Convenience Function"

Added "Argument"

Function Names and Arguments

Functions & Objects

Packages

• Package: A group of functions installed together

• Packages may have functions with the same name!

• Install: Copy instructions to your computer

• Load/Attach/Import: Put instructions in memory

Media Literacy -> Package Literacy

• Who wrote it?

• How long has it been around?

• How many other people use it?

• Where is the code?

• How good is the documentation?

• What kind of testing has been done?

• Does it give the same results?

• What do other people say about it?

Is R / Python for You

Check in with yourself:

• Do functions and arguments make sense?

• Can you be detail oriented?

• Can you keep track of things that change?

• Are you good at thinking systematically?

It's okay if you answered "no". You can still use R.

If Not Yet

• Practice with functions in software you know.

• Use Jamovi (R) and have it show the syntax.

• Practice reading syntax and identifying functions and objects.

Which to Pick

• Start with whichever one…

• … the people around you use

• … has the functions you need

• … looks easier to read for you

• Use R if you mostly work with data tables and do statistics

• Tends to get new statistical procedures first

• Easier to read and understand

• Use Python if you often do non-statistical programming

• More and better non-tabular text-processing tools

• Better integrates with applications

R + Python

• Use R in Python (r2py)

• Use Python in R (reticulate)

• Use R or Python in SPSS, Stata, and SAS

• Some features in R get "ported" to Python

• Some features in Python get "ported" to R

• Use SQL in R or Python

Where to Start?

• Data Management• Many, many, functions

• Python: pandas

• R: tidyverse, data.table, or sqldf

• Statistical Analysis• Formula Notation

• Python: statsmodels

• R: base R, afex/car (ANOVA), lme4 (Mixed Models), etc.

• Graphing• Python: seaborn (uses matplotlib)

• R: ggplot2, ggformula, or lattice

Interpreting Tutorials

Recognizing Packages

In R: • library(package)

• require(package)

• package::function()

In Python:

• import package as nickname

• nickname.stuff

What to Look For

Functions & Methods:

Objects:

Learning Packages & Functions

Built-In Datasets

R

• data() #see all the datasets included

• data(name) # make it available

Python

• Some options, but none great

• Just use R's• https://vincentarelbundock.github.io/Rdatasets/

• Both allow URLs in read_csv

Creating Data

Use VectorsIt is very common to use vectors as variables without

making them into a dataframe.

A <- c(1,2,3,4,5)B <- c(7:20, 200)t.test(A,B)

group <- 1:2value <- rnorm(20)data <- data.frame(group, value)t.test(value ~ group, data=data)

Jupyter Notebookextension is .ipynb

Our InfoGuides

• https://infoguides.gmu.edu/learn_r

• https://infoguides.gmu.edu/learn_python

• DataCamp

• Carpentries

• CodeSchool

• Coursera

Jamovijamovi.org

Syntax Mode

# Descriptives

jmv::descriptives(data = data,vars = "fate")

Comments

Packages

Functions

Data Specification

Values

Arguments