# Takes a subsetted list of functions from Hadley Advanced R
# Assigns each randomly to a student in the class
# 19 February 2017
# NJG
# Ensure that the same random number sequence is used by everyone.
set.seed(100)
# The Hadley R functions:
firstToLearn <- c("str", "?")
operators <- c("%in%", "match", "=", "<-", "<<-", "$", "[",
"[[", "head", "tail", "subset", "with", "assign", "get")
comparisons <- c("all.equal", "identical", "!=", "==", ">", ">=", "<", "<=", "is.na", "complete.cases", "is.finite")
basicMath <- c("*", "+", "-", "/", "^", "%%", "%/%", "abs", "sign", "acos", "asin", "atan", "atan2", "sin", "cos", "tan", "ceiling", "floor", "round", "trunc", "signif", "exp", "log", "log10", "log2", "sqrt", "max", "min", "prod", "sum", "cummax", "cummin", "cumprod", "cumsum", "diff", "pmax", "pmin", "range", "mean", "median", "cor", "sd", "var", "rle")
logicalSets <- c("&", "|", "!", "xor", "all", "any", "intersect", "union", "setdiff", "setequal", "which")
vectorsMatrices <- c("c", "matrix", "length", "dim", "ncol", "nrow", "cbind", "rbind", "names", "colnames", "rownames", "t", "diag", "sweep", "as.matrix", "data.matrix")
makingVectors <- c("c", "rep", "rep_len", "seq", "seq_len", "seq_along", "rev", "sample", "choose", "factorial", "combn", "is.character", "is.numeric", "is.logical", "as.character", "as.numeric", "as.logical")
listsDataFrames <- c("list", "unlist", "data.frame", "as.data.frame", "split", "expand.grid")
output <- c("print", "cat", "message", "warning", "dput", "format", "sink", "capture.output", "sprintf")
readingWritingData <- c("data", "count.fields", "read.csv", "write.csv", "read.delim", "write.delim", "read.fwf", "readLines", "writeLines", "readRDS", "saveRDS", "load", "save")
# Combine all of the function lists and randomize the order:
RFunctions <- c(firstToLearn, operators, comparisons, basicMath, logicalSets, vectorsMatrices, makingVectors, listsDataFrames, output, readingWritingData)
RFunctions <- sample(RFunctions)
# Create class list
classNames <- c("Alger", "Ashlock", "Burnham", "Clark", "Kazenal", "Keller", "Looi", "Makhukov", "Mickuki", "Nevins", "Southgate")
# Assign functions
functionAssignments <- rep_len(classNames, length.out=length(RFunctions))
# Bind the two columns into a data frame
functionsFinal <- data.frame(functionAssignments,RFunctions)
splitDF<- split(functionsFinal, functionsFinal$functionAssignments)
splitDF$Ashlock## functionAssignments RFunctions
## 2 Ashlock acos
## 13 Ashlock load
## 24 Ashlock rbind
## 35 Ashlock all
## 46 Ashlock exp
## 57 Ashlock head
## 68 Ashlock %/%
## 79 Ashlock setdiff
## 90 Ashlock atan2
## 101 Ashlock assign
## 112 Ashlock data
## 123 Ashlock rep
## 134 Ashlock =acosThe acos function calculates the arc-cosine for a given argument, x. The arccosine is the inverse cosine function of x, when -1<x<1.
#acos function
z<- c(.2,.3,.4,.5)
acos(z)## [1] 1.369438 1.266104 1.159279 1.047198load#example
save.image(file= "homework_6.RData") #save your workspace
#To load this make sure you are in the current working directory
#in which you saved this workspace then run the following code
load(file= "homework_6.RData")
#the default settings are to load the file in the global environment and to have verbose = False. In order to debug...
load(file= "homework_6.Rdata",verbose= TRUE)## Loading objects:
## readingWritingData
## splitDF
## output
## makingVectors
## vectorsMatrices
## z
## operators
## comparisons
## .Random.seed
## classNames
## RFunctions
## basicMath
## listsDataFrames
## logicalSets
## firstToLearn
## functionAssignments
## functionsFinalrbind#example
m<- rbind(1,1:7)
m## [,1] [,2] [,3] [,4] [,5] [,6] [,7]
## [1,] 1 1 1 1 1 1 1
## [2,] 1 2 3 4 5 6 7m <- rbind(m, 8:14)
m ## [,1] [,2] [,3] [,4] [,5] [,6] [,7]
## [1,] 1 1 1 1 1 1 1
## [2,] 1 2 3 4 5 6 7
## [3,] 8 9 10 11 12 13 14#deparse.level argument
dd<- 10
rbind(1:4, c=2, "a++"=10, deparse.level =0) #this names the rows of the middle two arguments## [,1] [,2] [,3] [,4]
## 1 2 3 4
## c 2 2 2 2
## a++ 10 10 10 10rbind(1:4, c=2, "a++"=10, dd, deparse.level=1) #this names the last three arguments (this is the default setting)## [,1] [,2] [,3] [,4]
## 1 2 3 4
## c 2 2 2 2
## a++ 10 10 10 10
## dd 10 10 10 10rbind(1:4, c=2, "a++" =10, dd, deparse.level=2) #takes the names from each element## [,1] [,2] [,3] [,4]
## 1:4 1 2 3 4
## c 2 2 2 2
## a++ 10 10 10 10
## dd 10 10 10 10readRDSThis function is used to write a single R object to a file, and to restore that object. Arguments: - object: R object to be written to a file
- file: a connection or the name of the file where the R object is saved to or read from
- ascii: A logical. If TRUE or NA, an ASCII representation is written. The default for this argument is FALSE. This results in a binary representation.
- version: This argument will only be relevant with versions newer than the default version (2).
- compress: A logical stating whether or not you want your saved object to be compressed. The default for this argument is TRUE.
- refhook: This is a hook function for handling reference objects. The default for this argument is NULL.
#example
##save a single object to file
copepod<-10
saveRDS(object=copepod, file="copepod.rds")
##restore it under a different name
copepod2 <- readRDS(file="copepod.rds")
identical(copepod, copepod2)## [1] TRUE<<-This function assigns a value to a variable. The arguments used are the variable and a value to be assigned to x. The difference between this function and the <- function is that <<- will search through parent environments of a package you are working in for the variable you have called. If it finds the variable in the parent environment, it will assign the value for the variable in the parent environment to the variable in your global environment. If it does not find the variable, then assignment takes place in the global environment.
#example
outer_func <- function(){
inner_func <- function(){
a <<- 30
print(a)
}
inner_func()
print(a)
}
outer_func()## [1] 30
## [1] 30print(a)## [1] 30read.csvThis function reads in a file that is in table format, and creates a data frame from it. Default settings: read.csv(file, header = TRUE, sep = “,”, quote = “"”, dec = “.”, fill = TRUE, comment.char = “”, …)
Arguments: - file: this is the file you want to be read from
- header: This is a logical value stating whether or not the file you are reading in contains the header names in the first line
- sep: This describes how your characters are separated the default is space, but you can also use “,”
- quote:This argument denotes how your character strings are delimited. The default is to delimit strings by double quotes but you can also delimit strings by single quotes. If you want to disable quotes you can use quote = “”
- dec: The character used in the file for decimal points
- fill: a logical. If TRUE, then if your rows have unequeal length, blank fields are added.
- comment.char: A character vector of length one containing a single character or empty string. The default is to use “” . This turns off the interpretation of comments.
#example
read.csv(file="OASV2_BodyLengthMeasurements_Oct2016.csv", header = FALSE, sep =",", quote="\"", dec=".", fill=TRUE, comment.char="")## V1
## 1 #/////////////////////////////////////
## 2 # -----START OF METADATA -----
## 3 # ------------------------------------------------
## 4 # TITLE: OASV2 Strongylocentrotus purpuratus Plutei Body Lengths
## 5 # DATE: October 2016
## 6 # AUTHOR: Lauren Ashlock
## 7 # ------------------------------------------------
## 8 # AUTHOR EMAIL: Lauren.Ashlock@uvm.edu
## 9 # AUTHOR ADDRESS: 109 Carrigan Drive; Marsh Life Sci Bldg; Rm. 324; Burlington; VT 05405"
## 10 # AUTHOR WEBSITE: TBD
## 11 # ------------------------------------------------
## 12 # OWNERSHIP: Dr. Melissa Pespeni; University of Vermont"
## 13 # COLLABORATORS: April Makukhov; Heidi Hargarten; Kate Huber; Melissa Pespeni"
## 14 # FUNDING SOURCES: NSF DGE-1451866 for ADM; University of Vermont"
## 15 # REPOSITORY: One or more lines for GitHub; Dryad; or permanent web repositories where data set can be accessed"
## 16 # CITATIONS: One or more lines for publications that cite or use these data
## 17 # ------------------------------------------------
## 18 # SAMPLING LOCATIONS: Adult purple urchins were collected from San Diego; CA and were spawned in the Pespeni marine lab (14 females & 11 males) to make these larvae"
## 19 # SAMPLING TIMES: These data are from 7-Day old plutei purple urchin larvae
## 20 # VARIABLE DESCRIPTION: ID = individual larval ID; pH = mean pH treatment; condition = static or variable pH treatment; vessel_ID = vessel replicate that larvae came from; Body_Length = entire length of each pluteus larvae (in um)"
## 21 # MISSING DATA: One or more lines for each variable describing the source of NA values throughout
## 22 # ------------------------------------------------
## 23 # DATA TRACK CHANGES LOG (use this section to record any changes to the data set after it is created)
## 24 # DATE: # CHANGES:
## 25 # DATE: # CHANGES:
## 26 # DATE: # CHANGES:
## 27 #DATE: #CHANGES:
## 28 # ------------------------------------------------
## 29 # ----- END OF METADATA -----
## 30 #/////////////////////////////////////
## 31 #
## 32 #
## 33 # ----- START OF DATA -----
## 34 #
## 35 ID
## 36 L1
## 37 L2
## 38 L3
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## 624 # ----- END OF DATA -----
## V2 V3 V4 V5
## 1
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
## 12
## 13
## 14
## 15
## 16
## 17
## 18
## 19
## 20
## 21
## 22
## 23
## 24
## 25
## 26
## 27
## 28
## 29
## 30
## 31
## 32
## 33
## 34
## 35 pH Condition Vessel_ID Body_Length
## 36 7 static V02 184.434
## 37 7 static V02 227.423
## 38 7 static V02 152.984
## 39 7 static V02 174.072
## 40 7 static V02 164.587
## 41 7 static V02 177.44
## 42 7 static V02 184.284
## 43 7 static V02 190.382
## 44 7 static V02 167.177
## 45 7 static V02 196.431
## 46 7 static V02 141.305
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## 48 7 static V02 173.201
## 49 7 static V02 247.204
## 50 7 static V02 200.108
## 51 7 static V02 167.894
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## 55 7 static V02 163.32
## 56 7 static V02 161.875
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## 59 7 static V02 168.377
## 60 7 static V02 186.294
## 61 7 static V02 180.735
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## 63 7 static V02 171.061
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## 69 7 static V02 205.216
## 70 7 static V02 182.279
## 71 7 static V02 171.876
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## 75 7 static V02 176.94
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## 88 7 static V02 164.412
## 89 7 static V02 162.468
## 90 7 static V02 207.327
## 91 7 static V03 133.759
## 92 7 static V03 166.735
## 93 7 static V03 152.68
## 94 7 static V03 183.841
## 95 7 static V03 151.029
## 96 7 static V03 153.309
## 97 7 static V03 187.556
## 98 7 static V04 164.839
## 99 7 static V04 146.893
## 100 7 static V04 177.346
## 101 7 static V04 134.758
## 102 7 variable V08 224.959
## 103 7 variable V08 189.505
## 104 7 variable V08 248.575
## 105 7 variable V08 195.785
## 106 7 variable V08 243.962
## 107 7 variable V08 198.694
## 108 7 variable V08 134.414
## 109 7 variable V08 227.699
## 110 7 variable V08 186.73
## 111 7 variable V08 242.976
## 112 7 variable V08 211.569
## 113 7 variable V08 208.585
## 114 7 variable V08 222.883
## 115 7 variable V08 192.219
## 116 7 variable V08 200.749
## 117 7 variable V08 248.632
## 118 7 variable V08 222.58
## 119 7 variable V08 215.421
## 120 7 variable V08 201.573
## 121 7 variable V08 192.157
## 122 7 variable V10 212.19
## 123 7 variable V10 231.445
## 124 7 variable V10 195.253
## 125 7 variable V10 201.933
## 126 7 variable V10 216.574
## 127 7 variable V10 197.75
## 128 7 variable V10 210.983
## 129 7 variable V10 219.36
## 130 7 variable V10 194.151
## 131 7 variable V10 223.56
## 132 7 variable V10 185.429
## 133 7 variable V10 206.685
## 134 7 variable V10 223.514
## 135 7 variable V10 164.642
## 136 7 variable V10 218.886
## 137 7 variable V10 202.007
## 138 7 variable V10 208.009
## 139 7 variable V10 175.262
## 140 7 variable V10 199.123
## 141 7 variable V11 216.473
## 142 7 variable V11 196.642
## 143 7 variable V11 222.867
## 144 7 variable V11 238.211
## 145 7 variable V11 232.595
## 146 7 variable V11 214.897
## 147 7 variable V11 266.076
## 148 7 variable V11 192.708
## 149 7 variable V11 212.937
## 150 7 variable V11 198.78
## 151 7 variable V11 167.19
## 152 7 variable V11 217.889
## 153 7 variable V11 198.773
## 154 7 variable V11 175.46
## 155 7 variable V11 209.244
## 156 7 variable V11 224.552
## 157 7 variable V11 223.394
## 158 7 variable V11 162.466
## 159 7 variable V11 241.49
## 160 7 variable V12 187.396
## 161 7 variable V12 229.073
## 162 7 variable V12 148.226
## 163 7 variable V12 191.922
## 164 7 variable V12 223.213
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## 624signThis function returns a vector with signs of the corresponding elements of a variable. The output gives you 1 for positive values, 0, or -1 for negative values. The only argument for this function is a numeric vector
MyVec <- c(0, 2, 5, 7, -1, -4, -7, 0, 5, -4)
sign(MyVec)## [1] 0 1 1 1 -1 -1 -1 0 1 -1