Dataset Used in This Lab (download from course website framingham_1000.rdata

Transcription

1 Introduction to R and R- Studio Sring 2019 Lab #1 Some Basics Before you begin: If you have not already installed R and RStudio, lease see Windows Users: htt://eole.umass.edu/bie540w/df/how%20to%20install%20r%20and%20r%20studio%20windows%20users%20fall% df MAC Users htt://eole.umass.edu/bie540w/df/how%20to%20install%20r%20and%20r%20studio%20mac%20users%20fall% d f Goals Page 1. The R Studio Environment 2. How to Work with Packages 3. Suggested Practices for Your R Studio Sessions 4. Oening and Saving R Data 5. Illustration: Data Descrition 6. Illustration: gglot2 for Grahs Dataset Used in This Lab (download from course website htts://eole.umass.edu/~bie640w/) framingham_1000.rdata Lab 01.docx Page 1 of 10

2 1. The R Studio Environment Source: htts://ages.stolaf.edu/boehm/files/2015/02/rstudioinfofor272.df Bottom Left: Console Window Here you tye code directly. R then executes it. The romt is indicated by a > HACK: To retrieve a revious command (handy for editing!): UP- arrow HACK: To clear contents of the console window: <control- L> To Left: R Scrit and R Markdown (if installed) Window Use FILE > NEW FILE > your choice to access R Scrit or R Markdown HACK: Use R scrit to create and save files of R commands (more on this later) HACK: Use R Markdown to create archives of R sessions (R commands + outut) HACK: In R Scrit, to execute a command (good for troubleshooting): <control- ENTER> Ti: Different R Scrit files can be saved in different tabs HACK: Create R Scrit files that you save as boilers for future work To Right: Worksace Window Here you see all your stuff, called objects datasets, variables, etc HACK: To view a sreadsheet version of your data: CLICK on the name in the worksace Bottom Right: Plot/Hel Window A lot of stuff here: lots, hel w ackages, imorting from your comuter, other hel Be sure to toggle about to see what s here! Lab 01.docx Page 2 of 10

3 2. How to Work With Packages Introduction Many ackages came re- installed so you already have them, eg: base and stats In much of your work, you will want to use commands in ackages which you must download Working with Packages Requires TWO stes Ste 1 (Download and install, one time): You must install the ackage. Examle: install.ackages( foreign ) HACK: Don t forget the eriod in install.ackages HACK: The name of the ackage MUST be enclosed in double quotes HACK: Always install ackages in the console window HACK: Never install a ackage within a R Markdown file (more on this later) Ste 2 (Use, every session): You must attach the ackage to your session: library(foreign) ackages came re- installed so you already have them, eg: base and stats Some Useful hel commands related to ackages To see what ackages you have installed now, from console: library() To see what ackages are attached to your session, from console: search() To get location of library containing ackages, from console:.libpaths() To get hel, from console: hel(ackage= foreign ) NOTE: The hel will aear in the hel/lot window at bottom right How to Ugrade a Package Ti: Be sure to visit htts:// ackages- guide To see what ackages are old and need udating: old.ackages() To udate ALL ackages: udate.ackages() To udate JUST ONE ackage is a 2 ste rocedure: STEP 1: Remove the old ackage. Examle: udate.ackages( violot ) STEP 2: Re- install the same ackage. Examle: install.ackages( violot ) Suggested Habit When Using Packages for all Us Beginners (Document! Document! Document!) Introduction: This ti is suggested because, sometimes, different ackages share a command name. So you might want to be sure that the command you want is the one that will actually execute and not roduce an error message Ti: When using a command in a ackage, reface the command with the ackage name and :: Examle My data frame is framingham In it I have a variable female I want to label this variable 0/1 female I will use the command label that is available in ackage Hmisc. library(hmisc) Hmisc::label(framingham$female) <- "female01" Lab 01.docx Page 3 of 10

4 3. Suggested Practices for Your R Studio Sessions At the start of your R Studio Session Clear the worksace by issuing the following from the console: rm(list=ls()) Check your working directory: getwd() Change your working directory to one that you will remember. If you want your working directory to be your deskto (change yellow highlight): MAC Users: setwd( /Users/cbigelow/Deskto/ ) WINDOWS 7 and Vista Users: setwd( c:/users/cbigelow/deskto/ ) WINDOWS 2000, 2003 and XP Users: setwd( c:/documents and settings/cbigelow/deskto/ ) OR: setwd( c:/docume~1/cbigelow/deskto/ ) Create boilers! In articular, learn how to create and save R Scrit Use FILE > NEW FILE > your choice to access R Scrit In each R Studio session, you will be doing various things and troubleshooting as you go along. Once you have R code that runs successfully, save it in one or more R scrit files that you can use as boilers later. Archive your work: In articular, learn How to Use R Markdown Use FILE > NEW FILE > your choice to access R Markdown We will learn how to work with R Markdown files in another lab But for now, consider writing out an analysis lan of each R session (modular is good!) Then create an R Markdown file of your work. Lab 01.docx Page 4 of 10

5 4. Oening and Saving R Data BEFORE YOU BEGIN: The following assumes that your working directory is your deskto R Data (.RData) Place the R data set on your deskto (e.g: blood_storage.rdata) Set the working directory to your deskto, e.g: setwd("/users/cbigelow/deskto/") LOAD your Rdata: load(file= ). Examle: load(file= blood_storage.rdata ) HACK: Take care to enclose name of data set in quotes SAVE your Rdata (you will need to suly the correct object name): save(object, file= ). Examle: save(bloodfinal, file= bloodfinal.rdata ) HACK: The name of the.rdata does NOT have to match the name of your worksace R object. Lab 01.docx Page 5 of 10

6 5. ILLUSTRATION: Data Descrition BEFORE YOU BEGIN: The following assumes that your working directory is your deskto BEFORE YOU BEGIN: How R kees track of dataset names and variable names. R does this with a two level name: dataframe$variablename. Examle: framingham$sb dataframe = framingham Variable name = sb Download framingham_1000.rdata from the course website. Place on deskto. Launch R Studio. Set working directory (yours will be slightly different). Load data setwd("/users/cbigelow/deskto/") load(file= framingham_1000.rdata ) Create an R object (this will be a dataframe) called framingham so save having to tye Framingham_1000 # framingham <- framingham_1000 One Time Install Packages (Remove leading comment indicator # ) at the console window: # install.ackages( stargazer ) # install.ackages( summarytools ) Attach to your R Studio Session, the ackages you will be using here library(stargazer) library(summarytools) Lab 01.docx Page 6 of 10

7 Data Descrition: Quick look for ALL variables Method I (no ackage needed) summary(framingham) summary(framingham) ## sex sb scl age ## Men :443 Min. : 80.0 Min. :115.0 Min. :30.00 ## Women:557 1st Qu.: st Qu.: st Qu.:38.75 ## Median :128.0 Median :225.0 Median :45.00 ## Mean :132.3 Mean :227.8 Mean :45.92 ## 3rd Qu.: rd Qu.: rd Qu.:53.00 ## Max. :270.0 Max. :493.0 Max. :66.00 ## NA's :4 ## bmi id ln_bmi ln_sb ## Min. :16.40 Min. : 1 Min. :2.797 Min. :4.382 ## 1st Qu.: st Qu.:1246 1st Qu.: st Qu.:4.754 ## Median :25.10 Median :2488 Median :3.223 Median :4.852 ## Mean :25.57 Mean :2410 Mean :3.230 Mean :4.872 ## 3rd Qu.: rd Qu.:3605 3rd Qu.: rd Qu.:4.970 ## Max. :43.40 Max. :4697 Max. :3.770 Max. :5.598 ## NA's :2 NA's :2 ## ln_scl ## Min. :4.745 ## 1st Qu.:5.283 ## Median :5.416 ## Mean :5.410 ## 3rd Qu.:5.541 ## Max. :6.201 ## NA's :4 Data Descrition: Quick look for ALL variables Method II (uses ackage stargazer, command stargazer) library(stargazer) stargazer::stargazer(framingham, tye="text", median=true) library(stargazer) stargazer::stargazer(framingham, tye="text", median=true) ## ## ========================================================= ## Statistic N Mean St. Dev. Min Median Max ## ## sb 1, ## scl ## age 1, ## bmi ## id 1,000 2, , , ,697 ## ln_bmi ## ln_sb 1, ## ln_scl ## Lab 01.docx Page 7 of 10

8 Data Descrition: CONTINUOUS variable detail (uses ackage summarytools, command descr) library(summarytools) summarytools::descr(framingham$sb, stats = c("n.valid","mean", "sd", "min","q1", "med", "q3", "max","cv"), transose = TRUE) summarytools::descr(framingham$sb, stats = c("n.valid","mean", "sd", "min","q1", "med", "q3", "max","cv"), transose = TRUE) ## Descritive Statistics ## framingham$sb ## N: 1000 ## ## N.Valid Mean Std.Dev Min Q1 Median Q3 Max CV ## ## sb Data Descrition: DISCRETE variable detail (uses ackage summarytools, command freq) library(summarytools) summarytools::freq(framingham$sex) summarytools::freq(framingham$sex) ## Frequencies ## framingham$sex ## Tye: Factor (unordered) ## ## Freq % Valid % Valid Cum. % Total % Total Cum. ## ## Men ## Women ## <NA> ## Total Lab 01.docx Page 8 of 10

9 6. ILLUSTRATION: gglot2 for grahs I highly encourage you to learn gglot2 (layer by layer) One Time Install Packages (Remove leading comment indicator # ) at the console window: # install.ackages( gglot2 ) Attach to your R Studio Session, the ackage you will be using here library(gglot2) BEFORE YOU BEGIN Learning gglot2 layer by layer : Key: Because I make lots of mistakes, I build my lots layer by layer. To do this, I create a layer and assign it to an object that I call. Then I ask R to show me. If I m lucky it works. If not, I get an error message. But it s just one layer to correct, not so hard to do. Once I ve done all the layers and they all work, then I get rid of all the intermediate dislays of layer by later. Last but not least, if I m really hay with what I ve just develoed, I ll save it in one of my R Scrit boilers> See below and you ll see what I mean cb. GRAPH: Histogram with Overlay Normal (uses ackage gglot2, command gglot w lots of extras ) # gglot(dataframe, aes(x=variablename)) + stuff below <- gglot2::gglot(framingham, aes(x=sb)) <- + geom_histogram(binwidth=5, colour="blue", aes(y=..density..)) <- + stat_function(fun=dnorm, color="red", args=list(mean=mean(framingham$sb),sd=sd(framingham$sb))) <- + ggtitle("systolic Blood Pressure (sb)") <- + xlab("systolic Blood Pressure (mm Hg)") + ylab("density") <- + theme_bw() <- + theme(axis.text = element_text(size = 10), axis.title = element_text(size = 10), lot.title = element_text(size = 12)) Lab 01.docx Page 9 of 10

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