A Simple Introduction to R for Market Researchers
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The document provides an introductory overview of R, a free and open-source statistical programming language, as well as RStudio, its primary integrated development environment. It includes basic commands, data structures, and libraries, highlighting their application in market research with examples using built-in datasets like 'mtcars' and 'iris'. The session is hosted by Ray Poynter from Potentiate, and emphasizes the learning resources available for mastering R.
![Commands and R – Hello World
> print("Hello World")
[1] "Hello World"
>
> print("Hello World", quote=FALSE)
[1] Hello World
>
> myText <- "Hello World"
> print(myText)
[1] "Hello World"
>
> myText
[1] "Hello World"
>](https://image.slidesharecdn.com/newmr-introductiontor-raypoynteroct2019-191004180101/85/A-Simple-Introduction-to-R-for-Market-Researchers-5-320.jpg)
![Commands and R – Variables
> a <- 2
> b <- 4
> print(a * b)
[1] 8
>
> c <- a * b
> c
[1] 8
>
> c <- "Hello World"
> c
[1] "Hello World"
>](https://image.slidesharecdn.com/newmr-introductiontor-raypoynteroct2019-191004180101/85/A-Simple-Introduction-to-R-for-Market-Researchers-6-320.jpg)
![Commands and R – Vectors
> x <- c(1,2,3,4)
> x
[1] 1 2 3 4
> y <- 2 * x
> y
[1] 2 4 6 8
> z <- c("One","Two","Three")
> z
[1] "One" "Two" "Three"](https://image.slidesharecdn.com/newmr-introductiontor-raypoynteroct2019-191004180101/85/A-Simple-Introduction-to-R-for-Market-Researchers-7-320.jpg)
![Principal Components and Charting Example
> head(pca_mod,2)
$sdev
[1] 2.0562689 0.4926162 0.2796596 0.1543862
$rotation
PC1 PC2 PC3 PC4
Sepal.Length 0.36138659 -0.65658877 0.58202985 0.3154872
Sepal.Width -0.08452251 -0.73016143 -0.59791083 -0.3197231
Petal.Length 0.85667061 0.17337266 -0.07623608 -0.4798390
Petal.Width 0.35828920 0.07548102 -0.54583143 0.7536574](https://image.slidesharecdn.com/newmr-introductiontor-raypoynteroct2019-191004180101/85/A-Simple-Introduction-to-R-for-Market-Researchers-20-320.jpg)
A Simple Introduction to R for Market Researchers
- 1. A simple introduction to R for market researchers October 2019 Webinar Friday 4 October Live broadcast 10am New York (3pm London) Ray Poynter Chief Research Officer, Potentiate
- 2. What is R? • An open-source, free statistical language • The core language is expanded by an enormous collection of libraries • Available for Windows, Mac and UNIX • Find out about R (& download it) from: - https://www.r-project.org/ • Learning R • Books • Articles • Videos • E-learning, e.g. DataCamp, Udemy & Coursera
- 3. What is RStudio? • There are other choices, but nearly everybody I know is using RStudio to work with R • It is an IDE (Integrated Development Environment) • Editor • A tidy place to run R, to see the variables, and keep things tidy • There are open-source and commercial options (free and not-free) • Find out more and download it from https://rstudio.com/
- 4. Commands and R Commands are entered in the Console window
- 5. Commands and R – Hello World > print("Hello World") [1] "Hello World" > > print("Hello World", quote=FALSE) [1] Hello World > > myText <- "Hello World" > print(myText) [1] "Hello World" > > myText [1] "Hello World" >
- 6. Commands and R – Variables > a <- 2 > b <- 4 > print(a * b) [1] 8 > > c <- a * b > c [1] 8 > > c <- "Hello World" > c [1] "Hello World" >
- 7. Commands and R – Vectors > x <- c(1,2,3,4) > x [1] 1 2 3 4 > y <- 2 * x > y [1] 2 4 6 8 > z <- c("One","Two","Three") > z [1] "One" "Two" "Three"
- 8. Commands and R – Data sets R has lots of built in data sets. For example, mtcars > str(mtcars) 'data.frame': 32 obs. of 11 variables: $ mpg :Class 'labelled' num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ... .. .. LABEL: Miles/(US) gallon $ cyl :Class 'labelled' num 6 6 4 6 8 6 8 4 4 6 ... .. .. LABEL: Number of cylinders And 9 more variables
- 9. mtcars Use help (or ?) to understand an included data set > ?mtcars mtcars {datasets} R Documentation Motor Trend Car Road Tests Description The data was extracted from the 1974 Motor Trend US magazine, and comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles (1973–74 models). Usage Mtcars Format A data frame with 32 observations on 11 (numeric) variables.
- 10. Commands and R – Data Frames Data Frame – a compound structure, where the rows can be different sorts of items. > head(mtcars,4) mpg cyl disp hp drat wt qsec vs am gear carb Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
- 11. Commands and R – Frames and Vectors We can address vectors from inside a data frame using $ > summary(mtcars$mpg) Min. 1st Qu. Median Mean 3rd Qu. Max. 10.40 15.43 19.20 20.09 22.80 33.90 >
- 12. Commands and R – simple chart > hist(mtcars$mpg)
- 13. Commands and R - libraries The real power of R comes from the installed libraries > install.packages("ggplot2") trying URL 'https://cran.rstudio.com/bin/macosx/el-capitan/contrib/3.6/ggplot2_3.2.1.tgz' Content type 'application/x-gzip' length 3973186 bytes (3.8 MB) ================================================== downloaded 3.8 MB The downloaded binary packages are in /var/folders/wp/n9tjrcps0990gpznfmpqff2h0000gn/T//RtmpXDhlrV/downloaded_packages > library(ggplot2) > > ggplot(mtcars, aes(x=hp, y=mpg)) + geom_point(aes(shape=factor(cyl), colour=factor(cyl))) + xlab("Performance (horse power)") + ylab("Fuel consumption (mpg)")+ ggtitle("More cylinders are associated with fewer miles per gallon") + scale_shape_discrete(name="Cylinders") + scale_colour_discrete(name="Cylinders")
- 14. ggplot2 example
- 15. Scripts and R Scripts are the best way to use R • You create a record of what you did • You can tweak the code • You can audit the code • You can re-use the code for other projects • Comment your code to make it readable
- 16. Scripts and R Console From the Script 1. Run the whole script 2. Select and run a section 3. Run a single line The code and the results appear in the Console
- 17. Scripts and Charting Example Plots go in the plot window and can be exported
- 18. Tables and R
- 19. The Iris Data Set > data(iris) > ?iris Edgar Anderson's Iris Data Description This famous (Fisher's or Anderson's) iris data set gives the measurements in centimeters of the variables sepal length and width and petal length and width, respectively, for 50 flowers from each of 3 species of iris. The species are Iris setosa, versicolor, and virginica. iris is a data frame with 150 cases (rows) and 5 variables (columns) named Sepal.Length, Sepal.Width, Petal.Length, Petal.Width, and Species.
- 20. Principal Components and Charting Example > head(pca_mod,2) $sdev [1] 2.0562689 0.4926162 0.2796596 0.1543862 $rotation PC1 PC2 PC3 PC4 Sepal.Length 0.36138659 -0.65658877 0.58202985 0.3154872 Sepal.Width -0.08452251 -0.73016143 -0.59791083 -0.3197231 Petal.Length 0.85667061 0.17337266 -0.07623608 -0.4798390 Petal.Width 0.35828920 0.07548102 -0.54583143 0.7536574
- 21. Principal Components and Charting Example
- 22. Principal Components and Charting Example
- 23. Text tools This example uses ‘The Wonderdul Wizard of Oz, by L. Frank Baum downloaded from Project Gutenberg http://www.gutenberg.org/ebooks/55
- 24. Tidy the text
- 25. Bar chart of common words
- 26. Word cloud
- 27. Digging deeper
- 28. Overview • Free and open-source • Massive collection of libraries • Stats • Text analytics • AI tools • Graphics • Relatively steep learning curve • More about finding the story than telling the story • Lots of resources for learning about R • Books, videos, courses, papers etc
- 29. Q & A Ray Poynter Chief Research Officer Potentiate October 2019