# vectors can only contain objects of the same class
my_vec <- c(1, 4, 42, 17)
class(my_vec)[1] "numeric"# if you enter any items from a different class, everything will be coerced
my_vec2 <- c("word", 14, 8.2)
class(my_vec2)[1] "character"4 Lab 2: Data structures
For today’s lab, we are going over some of the most common types of data structures that you will encounter when working with data in R. There are many, many other types of data structures, many of which are highly specific to certain disciplines or within different coding and/or analysis worlds. For example, in evolution researchers frequently work with phylogenetic trees which are stored in specific formats to use with phylogenetic tree packages like ape, for example saved as nexus files. In ecology, many people work with spatial data that is often stored in raster files (e.g., .tiff) or in shapefiles (e.g., .shp, .kml). We won’t go into every possible type of data storage format in this class because it would be nigh on infinite, but just be aware that there are always ways to read different types of data into R which you will just have to Google.
We are going to start with the basics, which are data structures created within the R environment, before we move on to reading in from external files.
4.1 Vectors
Vectors are one-dimensional objects that consist of items of the same type. We can create them in R using the c function, which stands for ‘combine’. You will use this function so frequently in R that you will forget it is a function because it is incredibly useful any time you need to manually create data, combine objects into a vector, set up objects in your environment, etc.
By default, vectors in R are treated as columns. Why? Because in typical data storage practices, columns include all the values for one variable, while rows contain all the variables for one observation. So we would expect all the values in a column to likely be of the same object type because they are measuring the same thing, but not necessarily in a row. But, we can transpose a column vector into a row vector in R with the function t.
trans_vec <- t(my_vec)
trans_vec [,1] [,2] [,3] [,4]
[1,] 1 4 42 17# note that now there are dimensions that appear, i.e. we can see column numbers across the top
# whereas when we print a column vector, it just displays objects in order4.2 Matrices
A matrix is a 2-dimensional array with rows and columns. Think of it sort of like a spreadsheet, where each row represents one observation, and each column represents one variable that we have measured. We can create matrices in R by combining multiple vectors. If we have our variables stored as vectors, we could cbind them together, which stands for column bind.
var1 <- c(1, 0, 1, 0, 0)
var2 <- c(4.2, 2.2, 2.8, 1.7, 9.0)
mat <- cbind(var1, var2)
mat var1 var2
[1,] 1 4.2
[2,] 0 2.2
[3,] 1 2.8
[4,] 0 1.7
[5,] 0 9.0Alternatively, perhaps we have our data stored in rows for each observation. Note: this is not good data storage practice! But, sometimes it is inevitable because we don’t always make the best choices, and that’s okay.
obs1 <- c(1, 4.2)
obs2 <- c(0, 2.2)
obs3 <- c(1, 2.8)
mat2 <- rbind(obs1, obs2, obs3)
mat2 [,1] [,2]
obs1 1 4.2
obs2 0 2.2
obs3 1 2.8There is another function which will create a matrix for us out of data, rather than us having to specify the rows and columns.
# ick, it feels unnatural to enter data this way, and it should!
mydat <- c(1, 4.2, 0, 2.2, 1, 2.8)
# look at some of the options here when we create a matrix
# what happens if we mix up the number of rows or number of columns?
# or set byrow to F?
mat3 <- matrix(data=mydat, nrow=3, ncol=2, byrow=T)
# be careful with matrix if you're creating data structures from scratch!
# but, I use it all the time to set up placeholder matrices, e.g.
placeholder <- matrix(data=NA, nrow=10, ncol=20)Sometimes, but not always, matrices have identical upper and lower triangles. Think about a correlation matrix, for example. Because the variables along the rows and columns are identical, you have a square matrix, meaning that the number of rows and the number of columns are identical. The correlation between x and y is going to be the same as the correlation between y and x. So the two triangles are mirror images of each other. Because we often run into things like correlation or covariance matrices, it is worth knowing how to subset them.
Lab activity: fruit similarity.
# upper triangle returns TRUE/FALSE as to whether a cell in a matrix is part of the upper triangle
sqmat <- matrix(data=seq(1, 100, 1), ncol=10)
upper.tri(sqmat) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] FALSE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
[2,] FALSE FALSE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
[3,] FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
[4,] FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE TRUE
[5,] FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE
[6,] FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE
[7,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE
[8,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE
[9,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE
[10,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE# it can be useful for subsetting, over overriding
sqmat[upper.tri(sqmat)] [1] 11 21 22 31 32 33 41 42 43 44 51 52 53 54 55 61 62 63 64 65 66 71 72 73 74
[26] 75 76 77 81 82 83 84 85 86 87 88 91 92 93 94 95 96 97 98 99sqmat[upper.tri(sqmat)] <- NA
print(sqmat) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 NA NA NA NA NA NA NA NA NA
[2,] 2 12 NA NA NA NA NA NA NA NA
[3,] 3 13 23 NA NA NA NA NA NA NA
[4,] 4 14 24 34 NA NA NA NA NA NA
[5,] 5 15 25 35 45 NA NA NA NA NA
[6,] 6 16 26 36 46 56 NA NA NA NA
[7,] 7 17 27 37 47 57 67 NA NA NA
[8,] 8 18 28 38 48 58 68 78 NA NA
[9,] 9 19 29 39 49 59 69 79 89 NA
[10,] 10 20 30 40 50 60 70 80 90 100# lower.tri() does the same thing, but for the lower triangle
# we can also pull out the diagonal. this is often useful because e.g. in a correlation matrix, the diagonal is typically 1 because each item is perfectly correlated with itself
diag(sqmat) [1] 1 12 23 34 45 56 67 78 89 100sqmat[diag(sqmat)] <- 1
sqmat [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 NA NA NA NA NA NA NA NA NA
[2,] 2 1 NA NA NA NA NA NA NA NA
[3,] 3 13 1 NA NA NA NA NA NA NA
[4,] 4 14 24 1 NA NA NA NA NA NA
[5,] 5 15 25 35 1 NA NA NA NA NA
[6,] 6 16 26 36 46 1 NA NA NA NA
[7,] 7 17 27 37 47 57 1 NA NA NA
[8,] 8 18 28 38 48 58 68 1 NA NA
[9,] 9 19 29 39 49 59 69 79 1 NA
[10,] 10 20 30 40 50 60 70 80 90 14.3 Indexing
Lab activity practicing entering data from a birding trip some great women of American history took to Ireland into a matrix. Why? Because this gives us something tangible to look at as we interact with data in R to ground it in the real world, and also we will expand on it when we get to arrays below. Instructions: take three great women from american history, four locations in Ireland, and one deck of birds.
When working with matrices, it is common to use notation to identify which elements of a matrix you are referring to. Conventionally, we use \(i\) to indicate row indices, and \(j\) to indicate column indices (because \(i\) stands for index, I think). We use capital letters to indicate different matrices. For today, we will call the front table matrix \(A\) and the back table matrix \(B\). What card is \(A_{14}\)? \(B_{22}\)? What about \(A_{.2}\)?
We can also run these commands in R to inspect the data. Let’s create a matrix representing the data for each table, respectively.
A <- matrix(nrow=3, ncol=4)4.4 Interacting with data
4.4.1 Data structure
It is a good idea to inspect your data before working with it, whether you have created it or read it in from somewhere else. There are a couple base R functions that can be useful for that.
# look at the structure of your data, tells you class of each vector
str(A) logi [1:3, 1:4] NA NA NA NA NA NA ...# get a summary by variable
summary(A) V1 V2 V3 V4
Mode:logical Mode:logical Mode:logical Mode:logical
NA's:3 NA's:3 NA's:3 NA's:3 # look at the first few rows of data
head(A) # default is six [,1] [,2] [,3] [,4]
[1,] NA NA NA NA
[2,] NA NA NA NA
[3,] NA NA NA NA# lok at the last few rows of data
tail(A) # default is six [,1] [,2] [,3] [,4]
[1,] NA NA NA NA
[2,] NA NA NA NA
[3,] NA NA NA NA# we can subset our data using the square brackets []
A[1,4][1] NAIt can also be a good idea to visualize your data to make sure it is what you expect. More on this towards the end of lab.
4.5 Data.frames
Data frames are similar to matrices in that they are 2-dimensional data structures. A matrix is limited to one type of data. If we put both character and numeric data in a matrix, the data will be coerced to whatever can represent both of them, kind of like when we combine objects of different classes in a vector. A data frame, on the other hand, can contain different types of data in different columns. So more similar to a spreadsheet where we expect to have a mix of perhaps strings and numbers.
Adat <- as.data.frame(A)
Adat V1 V2 V3 V4
1 NA NA NA NA
2 NA NA NA NA
3 NA NA NA NA# we can also create a data.frame from scratch
women <- c("Addams", "Tubman", "Earhart")
suit <- c("club", "spade", "spade")
numb <- c(2, 9, 5)
mydat <- data.frame(women, suit, numb)
# we can also change the column names when we create a data.frame
mydat2 <- data.frame(people=women, suits=suit, value=numb)
mydat2 people suits value
1 Addams club 2
2 Tubman spade 9
3 Earhart spade 54.6 Reading data
Pretty much all the time we are working with data in R, we are reading in external data and not creating it from scratch because it is quite tedious otherwise. There are many different ways to import data depending on the type of file you are reading.
Future proofing your data files: When you can use .csv, it is highly, highly recommended because it is future proofed meaning it can be opened by any text editor (unlike e.g. .xlsx). There are of course other options for reading in things like tab-delimited files with
read.delim()or Excel spreadsheets withreadxl::read.xlsx()and so on, but a simple .csv is the way to go when possible.
First, we should read in the data into our environment. Then, it is generally a good idea to explore your data to see what you are working with. The function head will show you, by default, the first six elements of an object (in this case, the first six rows because our object is of the class data.frame). The function colnames will give you the column names (rownames will give you the names of rows). It is also a good idea to look at the structure of your data with the str function which gives you a quick overview of what is contained in the object. For example, with this data, it will tell us we have 2501 observations (i.e. rows of data) of 19 variables (i.e. our columns). It will also tell us all the column names, what type of data are contained in the column (e.g. year is an integer, species is a character, etc.), and give a preview of the first few items in each column.
Today we are going to use data from Macri et al. (2024) because they have archived three different types of files in their Dryad repository, which is good practice for us! We will download three of their files: “Dataset_Macri_et_al_One_earth.xlsx”, “LearningScore_Data.csv”, and “README_Macri_et_al.txt”.
First, we will use read.csv to load the learning score data. Note: if you run read.csv without saving it to an object name, it will quite literally just read it to you in the console. If you read in a very, very large file this way, it can sometimes lead to your R environment crashing! And you won’t have any data to work with. We have to save it to an object to have it be available in our R environment.
learning <- read.csv("~/Downloads/LearningScore_Data.csv")
str(learning)'data.frame': 652 obs. of 1 variable:
$ Bee.Moment.Year.Plot.Score: chr "1;pre;1;A;0" "2;pre;1;A;3" "3;pre;1;A;2" "4;pre;1;A;2" ...head(learning) # interesting! this is not what we expected Bee.Moment.Year.Plot.Score
1 1;pre;1;A;0
2 2;pre;1;A;3
3 3;pre;1;A;2
4 4;pre;1;A;2
5 5;pre;1;A;3
6 6;pre;1;A;3# perhaps this is not actually a comma-separated values spreadsheet
# could be tab-delimited? let's use a more flexible file reading function
learningT <- read.delim("~/Downloads/LearningScore_Data.csv")
str(learningT) # nope'data.frame': 652 obs. of 1 variable:
$ Bee.Moment.Year.Plot.Score: chr "1;pre;1;A;0" "2;pre;1;A;3" "3;pre;1;A;2" "4;pre;1;A;2" ...head(learningT) Bee.Moment.Year.Plot.Score
1 1;pre;1;A;0
2 2;pre;1;A;3
3 3;pre;1;A;2
4 4;pre;1;A;2
5 5;pre;1;A;3
6 6;pre;1;A;3# ah, what about semicolons?
learning2 <- read.delim("~/Downloads/LearningScore_Data.csv", sep=";")
str(learning2)'data.frame': 652 obs. of 5 variables:
$ Bee : int 1 2 3 4 5 6 7 8 9 10 ...
$ Moment: chr "pre" "pre" "pre" "pre" ...
$ Year : int 1 1 1 1 1 1 1 1 1 1 ...
$ Plot : chr "A" "A" "A" "A" ...
$ Score : int 0 3 2 2 3 3 3 0 1 3 ...head(learning2) Bee Moment Year Plot Score
1 1 pre 1 A 0
2 2 pre 1 A 3
3 3 pre 1 A 2
4 4 pre 1 A 2
5 5 pre 1 A 3
6 6 pre 1 A 3# this is why it is good to look at your data after you read it in! Let’s now also read in the .xlsx spreadsheet. First, we will install the readxl package, or load the library if it is already installed.
# install.packages("readxl")
library(readxl)
# by default, it will read the first sheet
alldat <- readxl::read_xlsx("~/Downloads/Dataset_Macri_et_al_One_earth.xlsx")
head(alldat)# A tibble: 6 × 7
Moment Year Plot Hive Total Pollen Nectar
<chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl>
1 pre 1 B 1 2 0 2
2 pre 1 B 2 25 3 22
3 pre 1 B 3 5 0 5
4 pre 1 B 4 12 5 7
5 pre 1 B 5 31 10 21
6 pre 1 B 6 16 3 13str(alldat)tibble [600 × 7] (S3: tbl_df/tbl/data.frame)
$ Moment: chr [1:600] "pre" "pre" "pre" "pre" ...
$ Year : num [1:600] 1 1 1 1 1 1 1 1 1 1 ...
$ Plot : chr [1:600] "B" "B" "B" "B" ...
$ Hive : num [1:600] 1 2 3 4 5 6 7 8 9 10 ...
$ Total : num [1:600] 2 25 5 12 31 16 36 4 46 44 ...
$ Pollen: num [1:600] 0 3 0 5 10 3 19 0 15 14 ...
$ Nectar: num [1:600] 2 22 5 7 21 13 17 4 31 30 ...# note that now we have a tibble instead of a data.frame
# they are basically the same structure, but a tibble is the tidyverse equivalent
# tibbles have some defaults baked in for how many rows print at a time, and other more relaxed rules
# but, i can't stand them, so i almost always coerce to a data.frame
alldat <- as.data.frame(alldat)
head(alldat) Moment Year Plot Hive Total Pollen Nectar
1 pre 1 B 1 2 0 2
2 pre 1 B 2 25 3 22
3 pre 1 B 3 5 0 5
4 pre 1 B 4 12 5 7
5 pre 1 B 5 31 10 21
6 pre 1 B 6 16 3 13str(alldat)'data.frame': 600 obs. of 7 variables:
$ Moment: chr "pre" "pre" "pre" "pre" ...
$ Year : num 1 1 1 1 1 1 1 1 1 1 ...
$ Plot : chr "B" "B" "B" "B" ...
$ Hive : num 1 2 3 4 5 6 7 8 9 10 ...
$ Total : num 2 25 5 12 31 16 36 4 46 44 ...
$ Pollen: num 0 3 0 5 10 3 19 0 15 14 ...
$ Nectar: num 2 22 5 7 21 13 17 4 31 30 ...# if we want to read a different tab from the spreadsheet, we need to specify which sheet
# if we aren't sure what the order is, we can check
# return the names, and order, of sheets in the file
readxl::excel_sheets("~/Downloads/Dataset_Macri_et_al_One_earth.xlsx")[1] "Colony activity" "Nectar Recruitment" "Pollen recruitment"
[4] "Pollen traps" "Gustatory resp." "Learning score"
[7] "Gene expression" "Pesticide analysis" "PCA" gustat <- readxl::read_xlsx("~/Downloads/Dataset_Macri_et_al_One_earth.xlsx", sheet=5)
# alternatively
gustat <- readxl::read_xlsx("~/Downloads/Dataset_Macri_et_al_One_earth.xlsx", sheet="Gustatory resp.")
head(gustat)# A tibble: 6 × 7
Bee Year Moment Plot Concentration Response Total
<dbl> <dbl> <chr> <chr> <dbl> <dbl> <dbl>
1 1 1 pre A 0.1 0 12
2 2 1 pre A 0.1 0 12
3 3 1 pre A 0.1 1 12
4 4 1 pre A 0.1 0 12
5 5 1 pre A 0.1 0 12
6 6 1 pre A 0.1 1 12str(gustat)tibble [1,609 × 7] (S3: tbl_df/tbl/data.frame)
$ Bee : num [1:1609] 1 2 3 4 5 6 7 8 9 10 ...
$ Year : num [1:1609] 1 1 1 1 1 1 1 1 1 1 ...
$ Moment : chr [1:1609] "pre" "pre" "pre" "pre" ...
$ Plot : chr [1:1609] "A" "A" "A" "A" ...
$ Concentration: num [1:1609] 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 ...
$ Response : num [1:1609] 0 0 1 0 0 1 0 1 1 0 ...
$ Total : num [1:1609] 12 12 12 12 12 12 12 12 12 12 ...# convert to a data.frame just because we (okay I - you do whatever you want) don't like tidyverse
gustat <- as.data.frame(gustat)Finally, we can read plain text files into R. This can be useful if you’re doing e.g. text mining.
readme <- readLines("~/Downloads/README_Macri_et_al.txt")
head(readme)[1] "README: Behavioral abilities and gene expression associated with social responsiveness in honeybees: Open Source Data"
[2] "We have submitted our raw data related to colony activity (ColonyActivity_Data.csv) and collection of pollen (PollenTraps_Data.csv), gustatory responsiveness (GustatoryResp_Data.csv) and learning abilities (LearningScore_Data.csv), and gene expression (GeneExpression_Data.csv)."
[3] "Descriptions:"
[4] "ColonyActivity_Data"
[5] "•\tMoment: Pesticide application moment"
[6] "•\tYear: Sampling year" If you are working with large, like really large datasets which several people in the class have indicated interest in, you may also want to look into the R package data.table and specifically the fread() function which reads in big data files fast. Really useful if you’ve got like 12 million observations of butterflies or something like that where other functions fail. Also, it is worth reiterating that there are a bajillion and one ways to read data into R - the functions we’ve looked at today are just some of the most basic ones. There are tons and tons of packages dedicated to reading in data, including other packages for reading from Excel, specialized data structures, etc.
4.7 Dimensionality and arrays
4.7.1 Great women of American history go birding.
Data can have more than two dimensions (whoa!). In fact, you can have \(n-\)dimensional data structures which have as many dimensions as you want! If they consist of one data type, we can represent them in an array, which is sort of like a matrix with extra slices in it. Let’s assume that our great women of American history go on a birding trip to Ireland every year, because why not. It’s a nice annual tradition. If we represent one annual trip as a matrix, we can add more matrices for the other years and sort of stack them together. Now we have an array \(A_{ijk}\) where \(k\) represents each time step. So we could subset to the \(i\)th observer, at the \(j\)th site on the \(k\)th visit. Let’s say they go three years in a row. What are the dimensions of the array?
# set up an empty placeholder array (note: you don't always have to do this, i just am not sure yet which cards we will flip in the lab activity)
birding <- array(dim=c(3,4,3))
birding, , 1
[,1] [,2] [,3] [,4]
[1,] NA NA NA NA
[2,] NA NA NA NA
[3,] NA NA NA NA
, , 2
[,1] [,2] [,3] [,4]
[1,] NA NA NA NA
[2,] NA NA NA NA
[3,] NA NA NA NA
, , 3
[,1] [,2] [,3] [,4]
[1,] NA NA NA NA
[2,] NA NA NA NA
[3,] NA NA NA NA# inspect the dimensions of an object
dim(birding)[1] 3 4 34.8 Lists
Lists are some of the most chaotic data structures. The elements contained in a list are R objects, but they can be whatever you want. You could have a list that has vectors in it, of all sorts of different types, or data.frames, or data.frames and vectors, or matrices, or a list of lists. Lists are basically the wild west of data structures because anything goes. It also makes them a huge pain to work with unless you remember exactly what the structure is and why you’re using it. It also means they are extremely flexible and can be super handy. I use them all the time when I want to do something mildly chaotic with lots of different types of data, or data of the same type with different dimensions.
people <- c("Bethune", "Cady Stanton", "Roosevelt")
numbers <- rbinom(n = 1491, size=4, prob=0.2)
mat <- matrix(rbinom(n = 10000, size=14, prob=0.7), ncol=100, nrow=100)
words <- readLines("~/Downloads/README_Macri_et_al.txt")
chaos_list <- list(people, numbers, words, mat)
print(chaos_list)[[1]]
[1] "Bethune" "Cady Stanton" "Roosevelt"
[[2]]
[1] 2 0 1 3 1 2 0 1 2 0 2 0 2 2 0 1 1 0 2 0 1 2 0 0 1 0 0 2 0 1 2 2 0 0 2 1 0
[38] 0 2 0 0 0 0 0 1 3 1 2 0 0 1 0 0 0 1 1 0 0 0 0 1 0 0 1 2 0 0 0 0 1 1 0 0 1
[75] 0 1 1 1 0 0 2 1 1 2 0 0 0 0 1 0 1 1 0 0 0 2 0 2 2 0 0 0 1 0 0 2 0 0 2 1 0
[112] 1 1 0 2 1 1 0 2 1 0 1 0 0 0 1 2 0 1 1 2 1 1 1 2 1 0 1 1 0 0 1 2 2 1 1 2 1
[149] 2 1 0 0 0 1 1 1 1 0 1 0 0 1 0 0 0 3 2 2 1 0 2 2 1 1 0 0 1 2 1 1 1 2 2 1 0
[186] 2 2 2 0 0 2 1 1 2 1 1 1 1 1 1 1 0 0 0 0 1 0 1 2 0 1 0 1 1 1 2 2 1 1 1 0 2
[223] 2 1 0 1 0 0 1 1 1 0 1 0 1 0 0 2 1 3 2 1 0 1 0 1 1 1 0 1 1 3 2 0 2 1 0 0 0
[260] 2 1 1 1 0 0 0 0 0 1 1 1 1 2 1 0 2 2 0 0 1 0 0 0 1 1 1 1 0 1 1 2 1 2 1 1 0
[297] 3 1 2 1 1 0 0 2 1 0 0 1 1 0 1 2 1 3 1 0 0 0 0 0 1 2 1 2 2 1 1 1 0 1 0 1 0
[334] 2 0 0 0 0 1 2 1 0 2 0 0 0 0 1 1 1 1 2 1 1 0 1 2 1 0 0 0 0 2 1 0 0 1 1 2 0
[371] 0 1 2 2 1 0 1 0 0 2 0 1 0 1 1 1 2 1 1 0 1 0 1 0 0 3 1 2 1 0 0 1 0 0 1 1 1
[408] 1 0 2 0 1 1 4 1 0 1 1 1 0 1 2 1 2 0 1 0 2 0 0 0 1 1 0 1 2 0 1 0 2 0 2 1 0
[445] 2 0 0 0 1 2 2 2 0 1 0 1 0 2 1 0 0 1 1 0 1 0 0 0 2 1 0 1 1 1 1 3 0 1 1 0 1
[482] 1 1 1 0 0 1 1 2 1 0 0 0 0 0 2 0 0 1 1 0 2 0 0 0 0 0 2 2 1 1 1 2 0 0 1 3 0
[519] 2 1 1 1 3 0 1 1 1 0 0 0 3 1 0 1 2 1 0 1 1 2 1 2 0 0 1 1 0 0 0 0 0 0 0 2 1
[556] 1 1 0 1 0 0 0 2 2 0 0 0 2 1 0 1 1 1 2 3 1 0 1 0 1 1 2 1 0 0 0 1 0 2 0 0 1
[593] 1 0 0 1 0 1 1 0 1 1 0 0 1 0 2 1 1 3 3 1 0 0 2 1 1 1 1 0 0 0 1 1 2 1 1 0 1
[630] 0 0 2 1 2 1 0 0 1 1 1 0 0 2 1 0 1 0 2 2 1 0 0 1 1 0 2 1 2 1 0 1 3 0 0 0 1
[667] 2 0 1 0 1 0 0 0 1 0 2 1 2 0 2 1 0 1 0 0 1 1 0 2 1 2 0 1 0 1 0 1 0 0 0 1 1
[704] 0 1 0 0 1 2 2 2 1 0 1 1 2 1 1 2 1 1 1 1 1 1 0 0 1 0 1 0 0 0 1 1 3 0 1 1 1
[741] 1 0 1 0 2 1 1 0 1 1 0 0 0 0 0 0 0 2 0 0 1 0 0 0 2 0 0 0 1 2 0 1 0 1 1 0 2
[778] 1 1 1 1 2 0 1 1 1 1 2 0 0 1 0 1 0 1 2 0 3 0 0 0 1 1 1 0 0 1 0 0 0 1 2 0 0
[815] 2 1 0 1 0 0 1 2 0 0 2 0 0 2 0 0 1 0 3 1 0 1 1 2 0 2 0 0 0 0 1 3 2 2 2 1 1
[852] 1 1 1 2 1 0 0 2 1 0 1 2 1 0 2 2 0 0 1 1 1 1 1 0 1 1 0 0 1 1 2 1 0 1 0 2 2
[889] 1 1 0 0 1 0 1 1 0 1 2 0 2 0 1 2 0 1 0 1 1 1 1 2 0 1 1 1 3 2 0 0 1 0 1 1 1
[926] 0 1 0 2 1 1 2 3 1 0 1 0 1 3 2 0 0 2 3 1 0 2 1 0 2 0 1 1 2 2 2 0 1 1 0 0 0
[963] 0 0 0 0 0 0 1 0 1 1 2 2 1 1 0 0 0 0 1 0 2 0 2 2 0 1 2 1 1 1 0 1 2 0 0 0 0
[1000] 1 1 1 0 2 0 1 0 1 0 1 1 2 0 1 1 2 1 1 0 2 1 1 1 1 1 0 0 1 0 1 1 1 0 1 1 0
[1037] 3 1 0 1 0 0 2 0 0 0 1 0 3 1 1 0 0 0 1 0 1 2 2 0 0 0 1 1 3 3 0 2 0 1 0 0 0
[1074] 0 1 1 2 2 1 0 2 0 1 0 0 2 1 0 0 0 0 3 1 2 2 1 2 1 1 1 0 0 1 0 2 2 1 0 0 1
[1111] 2 0 1 1 1 1 1 1 2 3 1 1 3 1 1 0 1 2 0 0 1 0 2 1 0 1 0 1 0 1 1 1 1 0 2 2 1
[1148] 2 1 0 2 2 1 0 0 1 0 0 0 1 1 3 0 1 1 1 1 0 2 1 1 2 0 0 1 0 2 0 0 0 0 0 2 1
[1185] 1 1 1 1 1 2 0 1 1 1 2 1 0 0 1 0 1 1 1 1 0 1 0 0 1 0 0 0 0 1 2 1 0 0 1 0 0
[1222] 1 0 1 0 2 1 0 1 0 1 0 1 1 1 0 1 0 2 0 0 1 2 2 2 2 0 2 0 1 0 0 1 2 0 0 0 1
[1259] 0 0 0 1 2 0 1 0 0 2 1 0 0 0 0 0 1 2 1 1 0 1 3 2 0 0 0 0 3 1 1 2 0 2 2 2 0
[1296] 0 2 1 0 0 0 2 0 0 0 0 2 2 0 1 0 0 0 2 1 1 0 0 1 0 0 3 2 0 0 1 1 3 1 2 0 0
[1333] 1 1 0 1 2 0 1 1 1 1 1 0 0 1 0 1 0 1 1 1 1 2 1 0 0 0 2 0 2 0 0 1 0 1 0 1 0
[1370] 0 0 1 0 0 2 0 0 2 1 0 2 0 2 1 1 1 0 2 2 1 0 0 1 1 1 1 1 1 0 1 2 1 1 0 0 0
[1407] 1 1 0 0 0 1 1 1 3 1 0 0 2 0 0 1 2 3 1 4 0 0 1 0 1 2 0 0 2 2 1 1 1 1 2 2 1
[1444] 0 0 1 3 0 1 2 2 0 1 1 1 2 1 2 0 1 0 1 0 0 2 2 1 1 0 0 0 1 0 1 1 1 0 0 0 0
[1481] 0 0 0 2 0 1 1 1 0 0 1
[[3]]
[1] "README: Behavioral abilities and gene expression associated with social responsiveness in honeybees: Open Source Data"
[2] "We have submitted our raw data related to colony activity (ColonyActivity_Data.csv) and collection of pollen (PollenTraps_Data.csv), gustatory responsiveness (GustatoryResp_Data.csv) and learning abilities (LearningScore_Data.csv), and gene expression (GeneExpression_Data.csv)."
[3] "Descriptions:"
[4] "ColonyActivity_Data"
[5] "•\tMoment: Pesticide application moment"
[6] "•\tYear: Sampling year"
[7] "•\tPlot: Name of the plot where apiary is located"
[8] "•\tHive: Number of the hives studied"
[9] "•\tTotal: Total number of bees entering the hive per minute"
[10] "•\tPollen: Number of bees entering the hive with pollen loads per minute"
[11] "•\tNectar: Number of bees entering the hive without pollen loads per minute"
[12] ""
[13] "PollenTraps_Data"
[14] "•\tMoment: Pesticide application moment"
[15] "•\tYear: Sampling year"
[16] "•\tPlot: Name of the plot where apiary is located"
[17] "•\tHive: Number of the hives studied"
[18] "•\tPollen weight: Weight of pollen collected in the trap (g)"
[19] "•\tCrop: Weight of pollen collected from the crop (g)"
[20] "•\tWild flora: Weight of pollen collected from the wild flora (g)"
[21] "•\tTime: Trap set duration (min), used as an offset "
[22] ""
[23] "GustatoryResp_Data"
[24] "•\tMoment: Pesticide application moment"
[25] "•\tYear: Sampling year"
[26] "•\tPlot: Name of the plot where apiary is located"
[27] "•\tBee: Number of the individual forager bee evaluated"
[28] "•\tConcentration: Sucrose solution concentration (%)"
[29] "•\tResponse: individual proboscis extension response (PER) of the bee to the stimulus (response=1; not response=0)"
[30] "•\tTotal: total number of forager bees evaluated"
[31] ""
[32] "LearningScore_Data"
[33] "•\tMoment: Pesticide application moment"
[34] "•\tYear: Sampling year"
[35] "•\tPlot: Name of the plot where apiary is located"
[36] "•\tBee: Number of the individual forager bee evaluated"
[37] "•\tScore: Sum of PERs throughout the procedure was obtained for each bee"
[38] ""
[39] "GeneExpression_Data"
[40] "•\tMoment: Pesticide application moment"
[41] "•\tYear: Sampling year"
[42] "•\tPlot: Name of the plot where apiary is located"
[43] "•\tHive: Number of the hives studied"
[44] "•\tSyx7: Relative expression of Syntaxin7"
[45] "•\tSyx1a: Relative expression of Syntaxin1a"
[46] "•\tAchE: Relative expression of Acetylcholinesterase"
[47] "•\tPelle: Relative expression of Pelle"
[48] "•\tBrahma: Relative expression of Brahma"
[49] "•\tEnolase: Relative expression of Enolase"
[50] ""
[51] ""
[52] "Methods"
[53] "Colony activity"
[54] "We evaluated as a colony activity indicator, the number of incoming bees (incoming rate) at the entrance of the hives at each sampling moment. In each apiary, we randomly chose eight hives. The same eight hives were measured in the two sampling moments. We counted the arrivals in the hives chosen for 1 min, twice a day for three consecutive days, once in the morning and once in the afternoon. According to the presence or absence of pollen loads on their hind legs, incoming bees were recorded as pollen or non-pollen (nectar) bees, respectively. Plot, Moment and year were taken as fixed variables, while hive was taken as a random variable in a Negative binomial model."
[55] "Pollen traps"
[56] "Pollen traps were placed in three randomly selected hives (different from the eight hives used for colony activity) for about 6 h and for three consecutive days. The weight of pollen loads collected in each pollen trap was measured. Color-classified pollen loads of each trap were weighed separately. Then, pollen grains were identified under the microscope to the lowest taxonomic level possible using a palynological database. Once color-classified pollen loads were identified, the total weight and the weight of pollen collected from the crop and the surrounding wild flora were calculated. Plot, Moment and year were taken as fixed variables, while hive was taken as a random variable in a Normal model. To analyze the proportion of pollen collected from the crop and wild flora, a Non-parametrical model was used."
[57] "Gustatory responsiveness"
[58] "To evaluate gustatory responsiveness at the apiary level, we captured incoming honeybees at the hive entrances from different colonies and for three consecutive days. This methodology was carried out in the three apiaries and both sampling moments, before and after crop flowering and pesticide application, and in two years. Each forager bee was exposed to a sucrose solution of a specific concentration chosen in a pseudorandomized way (0.1%, 0.3%, 1%, 3%, 10%, 30%, or 50% w/w). At the end of the experiment, a gustatory response proportion was obtained for each concentration of sucrose solution, based on the number of responsive bees over the total evaluated bees. As we obtained a response ratio for each sucrose solution concentration, the statistics analyses were independent among the different solution concentrations tested. Plot, Moment and year were taken as fixed variables in a Binomial model."
[59] "Learning score "
[60] "To evaluate the association between a pure odor with a sucrose reward via classical olfactory conditioning by using the proboscis extension response procedure, we captured incoming honeybees at the hive entrances from different colonies and for three consecutive days. This methodology was carried out in the three apiaries and both sampling moments, before and after crop flowering and pesticide application, and in two years. At the end of the experiment, a score defined as the sum of PERs throughout the procedure was obtained for each bee (learning score). Plot, Moment and year were taken as fixed variables in a Poisson model. As we obtained a score of responses for each forager bee evaluated, individual bees were not taken as a random variable."
[61] "Gene expression"
[62] "The expression of genes associated with social responsiveness in honeybees was measured to assess the impact of pesticide application and the changes in the food resources’ availability at the molecular level. In each apiary, we randomly chose four hives, and 10 brains of forager bees were pooled. Thus, we utilized four biological replicates per apiary. Plot, Moment and year were taken as fixed variables, while hive was taken as a random variable in a Gamma model."
[[4]]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 5 12 9 9 9 10 11 12 10 8 12 13 11
[2,] 12 10 9 8 6 12 10 10 9 11 11 10 9
[3,] 9 6 9 7 11 9 8 10 9 9 10 10 11
[4,] 7 4 12 12 8 8 8 10 8 10 11 9 6
[5,] 11 12 8 10 9 13 8 9 9 11 5 12 10
[6,] 11 12 11 9 9 10 11 11 10 11 10 9 6
[7,] 8 9 12 11 8 8 11 10 11 10 10 9 6
[8,] 10 7 12 10 11 10 12 11 10 7 10 10 9
[9,] 9 7 12 11 8 8 10 8 13 8 9 9 10
[10,] 11 8 9 9 10 10 10 10 9 8 12 11 9
[11,] 12 13 11 10 8 9 9 12 6 5 5 11 10
[12,] 9 13 8 6 7 9 9 9 12 7 10 9 10
[13,] 11 10 11 9 8 11 8 9 8 10 13 10 9
[14,] 11 9 10 12 12 13 8 8 10 10 9 11 10
[15,] 9 6 9 10 10 10 12 12 9 9 14 13 12
[16,] 10 8 9 10 7 12 9 9 10 10 6 8 13
[17,] 11 11 8 9 9 11 11 11 9 8 9 8 6
[18,] 11 13 9 14 12 9 11 8 11 7 7 11 7
[19,] 10 7 11 9 12 10 11 9 7 11 11 10 11
[20,] 11 10 8 10 9 12 9 8 7 11 11 9 11
[21,] 9 12 6 11 8 10 11 13 12 10 9 6 10
[22,] 12 11 11 11 9 9 9 11 11 11 11 13 11
[23,] 9 5 9 12 13 11 9 10 9 9 11 10 9
[24,] 9 9 13 9 11 8 9 12 12 11 11 13 10
[25,] 7 10 9 7 8 10 8 11 9 10 10 5 9
[26,] 11 10 10 10 7 8 11 8 9 11 9 9 8
[27,] 9 12 8 7 10 12 12 9 10 13 11 11 9
[28,] 10 11 10 14 8 11 10 8 10 9 12 7 7
[29,] 11 10 5 9 11 9 7 8 10 9 11 8 10
[30,] 12 12 10 10 11 13 9 9 8 8 7 7 11
[31,] 10 11 10 11 10 8 7 8 10 9 13 8 7
[32,] 8 13 12 9 8 12 10 9 7 7 8 10 11
[33,] 10 11 11 10 9 11 8 9 12 12 8 7 9
[34,] 9 12 9 10 11 12 10 11 12 9 9 9 11
[35,] 12 11 11 13 9 11 9 10 10 10 11 11 10
[36,] 10 9 10 10 11 9 13 9 10 7 11 11 8
[37,] 7 8 9 12 11 9 12 9 10 9 10 9 8
[38,] 12 10 10 9 8 5 10 12 9 11 10 12 11
[39,] 10 13 12 9 9 11 8 8 9 12 8 12 10
[40,] 11 12 7 5 12 11 9 10 9 12 9 10 8
[41,] 7 11 13 12 10 10 9 12 10 7 10 10 8
[42,] 10 8 14 11 7 8 11 14 10 13 10 11 11
[43,] 10 11 10 8 12 10 8 11 10 13 6 11 13
[44,] 10 11 13 12 7 11 12 7 9 10 10 11 11
[45,] 11 9 11 9 11 10 9 8 8 8 10 9 10
[46,] 11 12 11 11 10 8 10 9 11 8 10 6 12
[47,] 9 8 8 9 9 10 10 10 12 11 11 10 9
[48,] 8 10 8 8 13 11 11 10 11 9 11 12 7
[49,] 7 11 10 11 11 10 13 7 10 11 6 11 9
[50,] 11 10 11 11 7 12 12 9 10 6 11 11 12
[51,] 6 8 11 11 9 8 12 12 11 11 11 11 12
[52,] 8 9 10 8 6 7 11 9 11 9 11 7 9
[53,] 13 11 12 10 8 7 11 9 11 9 8 12 12
[54,] 8 11 13 11 11 8 8 14 12 9 8 12 11
[55,] 8 9 12 10 9 10 13 6 9 11 10 10 10
[56,] 11 9 11 8 9 10 7 10 12 12 10 8 12
[57,] 12 10 9 11 9 8 10 12 9 11 11 13 9
[58,] 12 8 9 11 11 8 12 8 9 10 6 13 9
[59,] 9 7 9 9 10 10 6 9 10 10 12 13 10
[60,] 11 10 12 9 10 12 11 9 10 12 11 9 10
[61,] 13 9 10 8 8 8 11 9 12 13 11 11 9
[62,] 10 12 10 11 10 11 8 9 11 12 9 12 11
[63,] 12 11 8 9 6 7 11 12 13 12 10 10 11
[64,] 6 13 10 12 8 9 9 9 12 10 13 11 11
[65,] 10 12 10 12 7 11 9 9 12 9 8 11 10
[66,] 12 10 10 12 7 11 9 12 10 13 8 12 8
[67,] 10 11 12 11 7 10 8 5 12 9 10 9 10
[68,] 12 9 6 11 10 11 11 10 11 11 9 11 7
[69,] 10 12 8 11 10 7 9 13 12 10 10 9 11
[70,] 11 11 10 8 9 9 10 8 11 8 9 12 11
[71,] 11 8 10 11 9 12 11 8 9 9 9 10 9
[72,] 10 10 6 8 12 12 11 12 12 11 10 8 13
[73,] 9 12 7 14 10 11 11 8 9 8 8 11 11
[74,] 13 9 9 9 9 8 5 10 14 7 9 11 12
[75,] 10 12 10 10 10 6 10 10 9 11 12 10 10
[76,] 6 9 12 8 11 11 7 11 9 11 12 13 11
[77,] 9 13 11 11 11 7 9 12 11 9 5 11 11
[78,] 9 11 9 14 9 12 12 9 9 12 10 9 10
[79,] 7 8 11 13 12 9 12 11 9 9 11 6 11
[80,] 10 9 9 7 12 9 9 14 9 8 11 10 12
[81,] 12 6 10 6 12 10 12 10 12 12 12 9 9
[82,] 9 10 11 13 12 10 11 12 8 8 7 9 7
[83,] 13 12 11 7 8 11 11 11 10 8 11 10 11
[84,] 11 12 10 11 11 9 7 10 7 7 11 13 9
[85,] 12 12 10 10 10 11 12 9 12 9 12 8 9
[86,] 8 10 8 9 9 10 9 14 8 10 11 11 8
[87,] 11 8 12 8 10 11 9 11 10 9 11 9 8
[88,] 12 10 5 10 10 9 10 9 11 7 8 11 8
[89,] 11 11 10 8 8 10 11 12 12 7 11 9 11
[90,] 10 9 12 10 10 10 7 13 10 10 7 6 11
[91,] 10 12 10 12 10 11 10 7 10 11 7 9 9
[92,] 12 10 6 8 9 11 12 9 9 12 10 10 10
[93,] 10 11 10 10 9 7 12 10 10 9 11 10 9
[94,] 9 9 7 10 10 9 10 10 8 11 10 8 11
[95,] 11 11 10 7 10 7 9 11 13 10 11 10 10
[96,] 11 11 10 12 12 5 9 7 8 11 6 9 10
[97,] 10 10 8 12 8 8 9 11 8 9 9 10 9
[98,] 11 10 9 11 8 6 11 9 13 8 10 10 9
[99,] 10 11 10 10 8 11 7 11 8 6 9 12 9
[100,] 11 12 7 12 9 5 12 9 10 9 11 9 8
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 10 9 9 5 9 11 10 10 12 9 10 9
[2,] 9 10 12 10 11 9 8 7 11 10 11 6
[3,] 11 10 7 11 7 9 10 9 9 8 7 11
[4,] 10 7 10 9 12 8 12 11 12 8 12 11
[5,] 10 4 12 7 7 7 12 12 7 9 12 8
[6,] 6 8 11 9 10 13 12 7 11 11 9 11
[7,] 11 9 9 8 10 11 11 8 10 5 9 11
[8,] 11 9 11 10 9 11 12 12 12 13 10 11
[9,] 12 12 11 12 11 9 9 10 6 11 8 10
[10,] 9 9 9 12 10 8 12 13 8 10 8 7
[11,] 9 9 10 11 10 13 10 8 6 8 8 10
[12,] 9 10 12 9 11 8 8 7 10 11 10 9
[13,] 8 8 11 9 10 8 12 11 11 11 12 13
[14,] 4 10 12 9 12 10 10 9 11 10 13 10
[15,] 12 10 9 11 9 10 11 9 10 9 9 7
[16,] 9 9 9 11 11 10 8 9 11 10 10 8
[17,] 7 9 9 9 9 10 11 11 9 7 8 12
[18,] 6 10 8 9 7 13 9 10 11 10 9 9
[19,] 7 8 11 11 9 12 11 10 10 5 8 9
[20,] 10 10 10 9 10 10 8 10 10 6 10 11
[21,] 9 11 8 9 10 10 10 7 10 10 9 11
[22,] 12 10 10 10 9 9 10 9 9 9 9 11
[23,] 11 8 13 9 9 8 9 14 9 11 9 10
[24,] 8 8 12 7 9 9 11 13 7 12 10 13
[25,] 9 9 10 10 9 9 8 9 13 9 11 10
[26,] 9 9 11 6 10 8 7 9 9 7 10 11
[27,] 10 8 11 9 10 10 6 11 9 12 7 10
[28,] 9 8 10 11 13 10 9 8 10 9 10 7
[29,] 10 10 10 12 12 9 11 10 10 6 11 11
[30,] 12 7 11 11 9 12 8 9 9 10 11 9
[31,] 10 10 11 13 8 9 11 12 10 8 11 7
[32,] 6 7 10 8 8 9 11 11 8 12 11 9
[33,] 12 12 8 12 12 7 8 10 8 12 9 8
[34,] 10 7 9 10 13 11 8 9 9 12 9 12
[35,] 12 9 8 10 8 11 10 11 11 8 8 10
[36,] 9 11 10 11 7 8 7 9 12 12 9 8
[37,] 12 12 10 8 11 8 11 12 7 10 14 8
[38,] 8 10 12 11 10 10 7 14 10 9 8 10
[39,] 11 10 9 11 13 9 11 11 10 10 8 10
[40,] 6 11 12 11 7 9 10 9 12 9 9 9
[41,] 11 11 12 9 9 8 6 14 5 9 11 10
[42,] 10 9 9 8 10 8 10 12 8 8 12 7
[43,] 9 11 12 8 10 11 11 11 8 9 10 11
[44,] 9 11 9 8 10 8 9 12 8 8 11 7
[45,] 10 8 10 9 9 11 10 10 8 11 10 10
[46,] 11 11 11 11 10 10 10 10 12 7 12 10
[47,] 11 8 10 9 4 11 11 9 11 11 12 10
[48,] 11 11 13 6 9 9 9 6 12 10 9 11
[49,] 12 8 10 8 10 9 10 11 11 8 9 11
[50,] 10 9 10 8 6 12 10 7 11 8 12 12
[51,] 11 11 11 11 7 8 11 11 12 11 9 9
[52,] 8 8 9 9 10 11 13 11 9 9 9 9
[53,] 12 12 11 12 8 12 11 12 11 11 7 10
[54,] 10 11 11 9 11 11 9 11 10 11 12 11
[55,] 9 10 9 11 7 10 13 10 10 9 11 8
[56,] 10 12 10 9 9 9 9 7 10 11 8 9
[57,] 9 7 11 9 11 12 11 11 11 11 10 9
[58,] 6 7 8 5 7 12 11 12 9 11 11 9
[59,] 10 10 10 7 10 12 8 9 8 9 11 10
[60,] 11 12 9 8 8 11 11 9 9 11 13 10
[61,] 10 8 9 10 8 11 12 5 11 12 13 11
[62,] 10 9 9 11 12 12 9 12 8 11 11 12
[63,] 13 10 12 9 11 7 7 12 7 10 10 9
[64,] 10 11 11 7 8 8 9 9 8 8 11 8
[65,] 11 10 9 10 8 8 12 11 11 12 11 10
[66,] 10 10 12 12 6 9 11 10 14 6 9 10
[67,] 10 10 9 10 9 7 9 7 8 8 10 9
[68,] 7 11 12 11 8 11 10 11 11 7 13 8
[69,] 9 9 11 14 8 13 12 11 9 10 8 10
[70,] 12 9 9 11 9 7 9 10 10 9 12 12
[71,] 8 11 13 10 11 9 10 11 12 11 10 12
[72,] 13 9 10 7 9 12 7 10 6 10 11 11
[73,] 12 13 9 10 10 14 7 10 8 7 12 11
[74,] 10 12 7 12 13 11 11 10 11 12 12 9
[75,] 13 11 12 11 9 9 7 12 11 13 8 11
[76,] 12 7 10 10 10 10 9 7 9 12 9 12
[77,] 7 8 12 12 10 11 11 11 8 9 13 11
[78,] 9 11 10 12 11 10 7 12 10 12 10 6
[79,] 9 10 11 10 11 11 11 9 11 8 10 9
[80,] 8 9 10 10 8 7 10 9 12 10 10 10
[81,] 8 11 11 11 10 7 8 11 8 9 10 8
[82,] 10 12 7 9 6 7 10 10 10 13 8 10
[83,] 11 9 12 7 10 8 8 9 8 10 6 10
[84,] 8 11 9 9 5 10 10 7 10 12 7 10
[85,] 10 10 11 10 10 8 10 7 9 6 11 10
[86,] 5 11 11 9 8 11 9 8 8 11 8 12
[87,] 9 8 12 12 6 7 10 10 9 6 7 11
[88,] 10 10 11 11 9 9 9 11 12 10 11 9
[89,] 9 9 9 9 11 10 9 9 10 11 11 10
[90,] 12 9 8 10 11 9 11 9 9 11 11 12
[91,] 7 11 7 10 10 8 13 9 10 10 12 10
[92,] 9 12 10 10 10 12 7 13 12 7 10 9
[93,] 10 11 10 10 10 11 11 9 9 11 11 10
[94,] 9 9 5 9 10 9 11 11 8 12 12 10
[95,] 10 10 9 9 12 12 10 9 8 8 10 10
[96,] 11 10 7 12 8 10 7 12 10 10 10 12
[97,] 8 9 11 8 12 9 7 12 12 8 13 10
[98,] 10 9 10 11 11 11 9 12 9 10 7 12
[99,] 8 9 9 10 7 9 12 9 10 12 5 10
[100,] 10 11 7 12 11 10 11 10 9 11 13 12
[,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37]
[1,] 12 7 8 12 9 12 11 12 8 8 5 12
[2,] 12 9 12 10 9 13 10 9 9 8 9 7
[3,] 9 7 12 8 10 10 10 12 9 12 10 8
[4,] 11 9 10 11 8 10 12 8 7 8 11 5
[5,] 10 9 10 9 7 11 12 7 11 11 9 11
[6,] 9 10 6 10 10 12 13 11 7 11 9 11
[7,] 10 10 9 10 11 11 10 7 11 7 13 12
[8,] 7 11 10 10 7 10 13 9 12 10 8 10
[9,] 11 9 8 11 10 8 12 7 7 9 10 12
[10,] 5 11 11 10 9 8 12 12 10 8 12 9
[11,] 11 10 11 13 12 10 11 12 11 11 9 9
[12,] 11 12 11 12 10 12 11 10 11 9 10 10
[13,] 10 11 9 11 8 9 10 9 7 12 10 11
[14,] 11 9 9 8 12 8 10 6 11 8 13 11
[15,] 9 10 12 8 11 8 8 10 9 10 8 11
[16,] 7 11 7 9 10 9 11 8 8 7 12 6
[17,] 12 12 8 12 13 11 10 9 9 11 12 10
[18,] 12 9 13 11 10 9 10 9 8 9 9 10
[19,] 11 9 9 11 12 9 9 8 4 11 9 11
[20,] 10 8 13 9 9 9 11 9 9 11 9 13
[21,] 10 9 11 11 10 6 9 10 12 13 11 8
[22,] 11 9 10 11 8 9 9 8 10 12 9 11
[23,] 8 11 10 8 10 8 8 12 9 12 7 10
[24,] 10 7 11 10 11 8 10 10 8 9 9 9
[25,] 13 10 7 8 11 9 9 12 9 10 9 10
[26,] 10 12 9 11 10 10 10 7 11 9 10 11
[27,] 10 9 11 10 10 7 6 9 10 9 6 11
[28,] 11 10 7 7 9 11 13 8 7 9 12 11
[29,] 12 7 9 9 8 10 11 12 12 11 12 13
[30,] 10 8 11 10 9 11 10 10 8 11 7 10
[31,] 8 11 9 11 11 12 7 9 12 10 12 8
[32,] 9 9 9 12 8 7 10 12 10 12 8 9
[33,] 11 11 10 11 11 13 8 11 8 10 11 8
[34,] 8 13 4 11 8 11 10 11 9 8 9 11
[35,] 10 9 10 9 10 13 9 11 9 11 11 13
[36,] 11 10 11 10 12 8 10 11 7 11 10 11
[37,] 9 11 12 11 5 8 14 10 12 7 10 8
[38,] 9 11 9 11 12 11 10 11 12 10 11 9
[39,] 10 8 11 9 5 9 9 13 8 8 10 10
[40,] 7 8 8 12 10 9 9 8 6 9 10 10
[41,] 9 10 10 8 9 11 8 9 11 9 8 10
[42,] 10 8 10 9 10 12 8 9 11 10 10 11
[43,] 11 8 12 10 9 8 11 12 9 9 9 7
[44,] 10 8 8 6 11 11 10 8 10 8 10 7
[45,] 10 12 9 11 10 11 12 10 11 12 7 11
[46,] 11 8 10 10 5 9 11 13 10 9 8 11
[47,] 8 11 9 10 10 10 13 9 8 8 7 10
[48,] 10 10 10 12 10 8 9 10 7 9 12 10
[49,] 9 7 11 11 10 6 11 8 9 12 8 9
[50,] 11 10 10 11 12 8 6 9 10 10 9 12
[51,] 10 10 12 9 11 8 10 10 13 9 10 11
[52,] 10 9 9 11 12 10 6 10 8 7 10 11
[53,] 10 10 10 8 11 9 9 9 12 10 10 9
[54,] 13 11 7 9 10 11 8 11 13 11 8 8
[55,] 10 8 10 9 10 9 10 10 12 8 10 10
[56,] 8 10 8 11 10 11 12 5 10 10 11 12
[57,] 11 8 9 11 9 9 11 11 7 11 8 12
[58,] 13 11 9 9 6 6 10 13 8 10 10 7
[59,] 11 7 9 10 9 9 13 8 11 9 9 9
[60,] 9 10 10 11 9 11 10 11 9 11 10 7
[61,] 10 11 8 9 8 11 11 12 11 8 9 10
[62,] 11 10 12 12 10 10 10 12 7 8 12 12
[63,] 9 11 10 8 10 8 11 12 8 11 11 11
[64,] 9 13 7 11 11 9 6 11 9 12 7 10
[65,] 13 12 8 8 9 9 12 10 9 9 9 10
[66,] 9 13 11 11 9 11 10 13 9 7 10 14
[67,] 9 10 8 10 6 12 9 12 13 11 12 10
[68,] 11 9 11 8 13 6 10 6 10 11 10 11
[69,] 12 9 10 6 12 10 8 9 7 10 10 10
[70,] 11 9 10 9 8 9 11 9 11 8 11 11
[71,] 12 11 12 10 11 10 11 7 8 11 10 9
[72,] 9 6 11 8 10 11 10 11 8 9 10 11
[73,] 9 9 12 10 9 11 8 11 11 10 8 9
[74,] 8 12 11 8 12 9 11 12 11 9 8 8
[75,] 12 12 8 8 11 11 13 9 11 10 9 10
[76,] 9 4 11 9 10 10 10 10 12 11 10 10
[77,] 9 9 9 10 13 11 6 5 9 10 11 10
[78,] 8 8 10 11 8 7 7 9 10 11 9 11
[79,] 9 7 9 10 9 9 10 9 10 10 8 8
[80,] 13 11 8 13 9 10 10 8 10 13 8 8
[81,] 12 11 8 10 11 13 7 10 8 8 10 10
[82,] 9 8 9 12 10 12 10 9 6 8 11 13
[83,] 9 14 12 8 10 12 8 10 11 13 11 7
[84,] 12 8 10 8 9 8 9 8 11 13 10 10
[85,] 8 13 12 11 10 12 12 6 7 11 11 9
[86,] 8 9 10 13 12 11 10 10 9 10 12 9
[87,] 10 12 10 9 8 11 9 9 9 11 12 9
[88,] 11 8 11 10 9 11 12 10 7 7 10 11
[89,] 11 11 7 12 11 9 12 13 11 11 9 7
[90,] 6 9 8 7 9 10 11 11 10 8 13 10
[91,] 12 14 13 7 10 10 8 10 8 8 12 8
[92,] 9 11 13 9 9 7 11 8 6 9 11 7
[93,] 7 10 11 7 12 7 11 9 10 11 10 11
[94,] 11 10 9 11 10 8 10 9 11 10 10 9
[95,] 5 9 12 11 10 13 10 13 9 8 9 9
[96,] 10 8 9 11 10 8 11 10 11 8 9 10
[97,] 11 8 10 10 11 10 12 11 8 11 7 11
[98,] 11 11 11 9 12 10 11 9 8 8 9 10
[99,] 10 8 12 10 7 11 8 10 8 8 10 10
[100,] 7 9 12 11 10 10 7 12 9 10 12 6
[,38] [,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 9 10 10 10 12 10 10 9 5 9 9 11
[2,] 9 10 9 9 10 9 8 9 11 8 10 10
[3,] 9 11 12 11 8 8 9 9 11 10 9 12
[4,] 9 8 11 9 10 8 10 11 8 11 11 11
[5,] 12 11 10 8 10 11 11 11 11 9 9 8
[6,] 7 8 9 8 12 11 8 11 12 10 12 8
[7,] 10 9 12 10 10 11 8 12 10 10 10 12
[8,] 12 11 11 12 7 9 11 13 9 9 13 10
[9,] 8 8 13 11 10 8 9 6 9 8 11 11
[10,] 11 13 10 13 10 9 10 12 8 11 10 12
[11,] 12 10 9 10 7 10 11 9 13 14 8 9
[12,] 8 11 8 7 12 8 12 10 7 11 9 9
[13,] 10 11 10 7 9 10 9 11 10 12 9 9
[14,] 9 12 7 11 11 11 10 9 11 11 9 11
[15,] 8 10 11 9 10 9 9 9 11 11 10 9
[16,] 6 11 9 13 7 8 12 10 8 12 13 11
[17,] 11 6 9 10 12 10 7 8 13 13 10 13
[18,] 11 10 9 7 12 12 9 9 11 10 9 9
[19,] 13 6 11 11 10 9 8 10 10 9 9 10
[20,] 9 12 6 10 8 9 7 7 10 13 6 9
[21,] 9 10 9 11 12 9 11 5 9 8 10 12
[22,] 11 11 7 11 8 9 9 13 9 12 11 10
[23,] 8 12 9 11 13 12 12 12 12 10 9 8
[24,] 10 10 8 10 11 8 12 13 13 9 9 11
[25,] 10 9 13 9 6 11 11 10 10 7 11 11
[26,] 9 11 10 8 5 11 10 10 10 11 11 10
[27,] 8 11 11 10 10 8 10 12 8 7 11 12
[28,] 11 10 7 9 9 10 10 12 12 12 6 7
[29,] 12 9 8 10 6 10 11 7 11 10 10 9
[30,] 10 11 9 11 9 10 8 10 9 9 11 11
[31,] 14 9 9 12 13 9 9 9 7 11 9 11
[32,] 11 9 7 9 10 9 9 11 9 11 12 9
[33,] 9 10 10 10 9 10 11 10 8 9 9 10
[34,] 10 11 8 7 10 13 8 10 12 12 8 9
[35,] 11 12 12 10 13 8 11 8 9 9 11 11
[36,] 8 11 10 10 10 8 6 11 5 11 12 10
[37,] 10 12 8 10 12 8 11 9 10 10 8 11
[38,] 12 11 8 10 10 10 7 8 6 10 9 10
[39,] 13 9 11 10 7 7 9 8 11 10 9 13
[40,] 10 8 9 7 11 9 12 10 12 11 12 11
[41,] 11 8 10 8 9 13 6 8 9 12 8 5
[42,] 13 9 8 6 10 10 8 11 11 10 11 11
[43,] 11 10 9 10 11 10 10 11 9 10 8 8
[44,] 9 10 8 9 11 12 10 12 10 13 11 8
[45,] 9 10 13 11 6 12 10 9 10 9 8 13
[46,] 11 11 7 9 12 11 12 8 12 9 10 8
[47,] 10 10 11 11 8 11 12 9 11 9 9 10
[48,] 10 10 11 8 9 8 10 8 9 10 11 13
[49,] 9 9 9 9 8 8 8 12 10 10 10 11
[50,] 8 9 9 8 11 9 11 10 11 12 12 10
[51,] 8 10 11 7 9 10 8 9 9 10 13 10
[52,] 10 9 12 8 9 12 12 10 10 11 10 9
[53,] 8 9 12 9 12 8 8 9 10 10 10 11
[54,] 9 12 11 10 12 12 8 8 10 9 11 7
[55,] 5 8 10 10 9 10 7 9 9 11 12 10
[56,] 11 10 9 10 9 10 9 12 11 8 9 11
[57,] 9 7 6 8 10 6 9 9 10 9 12 10
[58,] 9 12 11 9 9 8 13 11 12 10 10 7
[59,] 7 11 10 11 12 10 8 7 11 11 11 9
[60,] 9 11 5 8 10 8 12 8 9 12 8 8
[61,] 9 9 11 10 11 11 8 12 8 13 13 8
[62,] 11 9 10 9 7 12 7 12 10 10 10 9
[63,] 9 10 14 9 8 8 10 10 9 12 6 12
[64,] 9 11 12 4 11 10 12 11 12 8 9 10
[65,] 9 9 8 12 10 12 12 12 13 10 9 13
[66,] 7 8 9 9 9 11 11 13 10 9 7 10
[67,] 10 11 6 6 9 12 6 8 8 11 7 10
[68,] 8 9 10 9 10 10 10 10 14 8 10 10
[69,] 10 9 10 11 12 9 9 10 10 10 9 11
[70,] 10 6 5 10 6 10 10 11 10 8 10 11
[71,] 8 9 10 6 10 11 13 10 10 9 13 12
[72,] 11 10 12 11 12 11 9 10 12 11 10 9
[73,] 10 11 9 6 8 8 7 10 9 10 12 11
[74,] 9 9 8 11 11 8 11 9 7 11 12 13
[75,] 11 6 8 13 12 11 9 9 12 9 8 11
[76,] 7 10 9 11 12 9 10 9 10 10 4 9
[77,] 12 11 8 11 9 12 11 10 9 8 10 11
[78,] 9 9 6 11 10 7 12 12 10 9 9 10
[79,] 9 10 12 10 9 8 9 9 12 7 8 11
[80,] 10 9 12 10 11 7 9 8 9 9 11 10
[81,] 11 11 10 9 12 8 10 9 10 11 8 11
[82,] 8 12 11 11 11 9 10 11 9 9 8 9
[83,] 9 7 9 7 9 7 10 10 8 9 11 10
[84,] 12 9 9 11 10 11 9 7 7 11 11 11
[85,] 13 8 7 8 9 10 12 11 10 8 9 11
[86,] 11 11 9 10 6 9 11 8 10 11 10 9
[87,] 10 8 11 13 11 8 11 10 12 9 12 11
[88,] 12 10 12 9 11 10 9 11 12 9 8 12
[89,] 12 11 12 11 9 12 12 13 12 11 11 7
[90,] 13 10 10 11 10 11 14 10 10 10 8 13
[91,] 6 11 7 9 12 9 7 11 12 7 9 10
[92,] 10 14 8 8 11 11 11 11 9 9 12 10
[93,] 10 11 9 9 9 12 11 8 11 9 8 10
[94,] 8 11 10 12 14 8 11 9 7 10 6 10
[95,] 10 12 12 9 10 10 8 11 7 11 11 12
[96,] 9 9 12 11 11 8 8 11 10 11 10 7
[97,] 9 12 10 10 10 7 11 9 10 10 9 11
[98,] 11 11 9 5 13 8 11 10 8 11 11 8
[99,] 10 6 9 9 7 12 11 10 6 8 9 12
[100,] 11 11 8 10 10 9 9 8 9 11 9 11
[,50] [,51] [,52] [,53] [,54] [,55] [,56] [,57] [,58] [,59] [,60] [,61]
[1,] 12 9 10 11 11 10 9 12 9 11 12 12
[2,] 10 11 14 10 10 10 9 10 12 8 9 11
[3,] 12 10 10 12 13 13 10 10 8 9 7 7
[4,] 7 8 10 11 10 7 9 7 11 11 9 12
[5,] 9 7 10 9 8 13 9 10 9 10 12 11
[6,] 9 11 11 11 12 12 8 11 14 10 9 12
[7,] 7 12 8 10 8 7 7 11 7 12 10 10
[8,] 9 12 12 10 6 13 11 12 9 7 10 10
[9,] 10 12 11 11 9 8 8 6 8 11 12 11
[10,] 9 9 8 7 12 11 9 6 10 11 9 11
[11,] 12 8 9 11 12 11 11 12 9 11 9 11
[12,] 12 8 7 8 12 9 10 11 12 11 12 10
[13,] 9 8 13 12 8 9 12 9 8 8 11 11
[14,] 9 9 10 11 13 9 13 7 12 7 10 8
[15,] 12 9 11 9 8 10 8 9 11 10 10 10
[16,] 10 8 12 9 11 8 11 10 8 9 11 9
[17,] 7 11 11 10 10 10 10 11 11 10 8 9
[18,] 9 9 10 6 10 9 10 5 8 11 10 11
[19,] 12 10 11 9 10 11 11 8 9 10 8 11
[20,] 12 11 10 9 7 7 11 9 7 11 12 11
[21,] 9 6 12 11 11 10 11 7 10 12 7 10
[22,] 8 8 2 10 11 8 11 9 8 7 10 9
[23,] 10 10 7 10 11 10 13 11 9 9 8 7
[24,] 11 7 11 8 9 10 8 13 11 13 9 10
[25,] 8 11 7 12 7 9 9 9 12 9 10 9
[26,] 4 10 8 10 11 10 11 6 9 8 11 9
[27,] 10 11 10 10 10 10 11 10 10 9 9 9
[28,] 11 11 11 10 11 10 10 12 4 11 13 8
[29,] 10 7 8 12 10 10 10 6 9 9 11 11
[30,] 12 11 7 11 8 8 7 8 11 12 7 14
[31,] 10 11 11 9 11 9 10 9 9 9 11 11
[32,] 10 11 12 11 10 11 10 9 12 11 10 7
[33,] 12 8 12 9 12 10 12 6 9 12 9 12
[34,] 12 12 11 8 9 13 10 9 10 10 11 9
[35,] 8 9 13 8 6 10 10 11 11 9 9 10
[36,] 8 11 10 11 9 10 8 8 10 11 10 9
[37,] 13 10 10 7 8 9 9 9 12 7 8 9
[38,] 9 11 12 10 11 12 9 9 13 11 9 9
[39,] 9 8 9 11 6 8 12 7 8 8 10 9
[40,] 10 10 12 8 11 11 8 10 10 9 10 11
[41,] 12 8 11 9 8 7 10 10 8 8 10 10
[42,] 9 9 9 10 12 9 9 9 9 9 10 8
[43,] 12 10 11 14 8 11 12 13 8 7 12 8
[44,] 10 11 12 9 8 8 9 13 10 13 11 11
[45,] 10 8 11 11 10 12 10 8 9 7 12 8
[46,] 10 13 10 10 9 8 9 7 10 9 12 10
[47,] 10 8 9 11 6 8 11 8 8 12 8 8
[48,] 11 10 9 7 7 12 11 9 9 10 12 11
[49,] 9 11 5 10 8 10 7 9 9 9 8 12
[50,] 10 11 12 7 12 10 9 10 10 10 12 10
[51,] 10 9 12 9 10 11 10 13 7 9 8 11
[52,] 11 9 10 9 10 11 11 12 9 7 11 11
[53,] 13 8 8 9 11 9 12 10 7 8 12 11
[54,] 11 8 9 7 9 9 11 8 11 10 10 11
[55,] 10 10 10 12 10 12 11 11 12 11 10 11
[56,] 9 9 9 8 9 10 7 12 10 14 11 10
[57,] 7 10 11 11 10 7 11 9 9 13 13 11
[58,] 8 9 11 12 12 11 11 11 9 7 9 9
[59,] 10 11 9 11 9 8 10 11 9 12 12 11
[60,] 12 8 7 11 10 8 8 9 7 10 9 10
[61,] 11 8 12 7 11 11 11 10 10 11 12 8
[62,] 10 10 14 11 11 8 11 9 12 10 8 12
[63,] 10 9 8 9 12 9 9 11 6 10 10 11
[64,] 9 7 9 10 12 11 8 9 11 10 12 11
[65,] 8 9 14 11 9 9 10 9 8 13 9 8
[66,] 10 11 10 10 11 11 10 7 9 10 7 9
[67,] 9 10 8 8 12 9 8 12 10 13 8 8
[68,] 8 11 10 9 10 11 6 9 12 12 9 10
[69,] 9 8 9 10 10 12 10 10 11 10 11 10
[70,] 9 10 11 9 7 13 6 11 11 11 12 13
[71,] 12 10 8 6 11 11 10 12 9 11 11 12
[72,] 10 6 9 11 8 8 9 6 9 7 6 10
[73,] 11 10 12 11 11 7 9 11 11 10 13 9
[74,] 12 10 11 10 8 11 9 12 10 11 9 11
[75,] 10 9 5 6 8 12 12 8 12 10 11 11
[76,] 6 11 6 9 8 8 10 11 11 6 10 6
[77,] 8 7 9 10 11 10 10 9 10 10 10 13
[78,] 11 6 11 9 12 11 12 6 11 7 9 10
[79,] 11 9 10 11 8 9 7 11 10 12 10 8
[80,] 9 10 11 12 10 9 7 6 11 8 10 12
[81,] 12 11 9 11 8 10 9 13 7 9 9 9
[82,] 7 13 9 9 11 10 10 10 10 10 8 9
[83,] 7 11 11 12 13 10 10 11 9 10 9 6
[84,] 10 10 9 8 10 8 9 9 8 9 10 9
[85,] 9 8 12 12 10 8 11 9 7 11 10 11
[86,] 12 12 13 10 12 9 10 11 6 11 13 9
[87,] 9 9 8 10 9 8 9 9 7 9 6 11
[88,] 9 10 11 10 9 10 8 11 9 10 10 10
[89,] 10 13 8 7 6 10 7 12 11 9 12 11
[90,] 11 11 7 10 8 7 11 8 8 13 8 10
[91,] 6 9 10 11 9 12 12 12 9 13 10 12
[92,] 11 11 8 12 10 10 9 6 11 12 11 9
[93,] 12 11 10 10 10 10 9 12 9 9 12 12
[94,] 11 13 7 9 11 10 11 11 11 8 12 8
[95,] 7 9 12 9 11 10 14 11 10 10 8 10
[96,] 5 12 12 9 11 9 12 13 10 9 8 12
[97,] 12 7 11 10 10 11 10 10 11 10 8 9
[98,] 10 9 7 9 7 11 11 8 9 10 10 10
[99,] 9 9 12 14 9 10 10 11 9 14 9 10
[100,] 9 8 9 10 9 8 12 8 12 9 9 10
[,62] [,63] [,64] [,65] [,66] [,67] [,68] [,69] [,70] [,71] [,72] [,73]
[1,] 10 11 11 9 10 10 9 8 11 10 12 11
[2,] 8 7 11 11 13 10 7 7 6 12 7 10
[3,] 8 11 9 10 8 9 10 7 11 11 7 9
[4,] 8 12 10 10 7 10 9 12 10 11 11 11
[5,] 7 11 11 11 8 7 11 9 9 11 9 10
[6,] 10 9 8 10 11 11 9 10 11 7 10 9
[7,] 10 11 10 10 11 12 12 7 7 10 8 10
[8,] 11 13 7 8 12 8 8 11 11 9 9 12
[9,] 11 7 10 8 11 11 7 10 11 10 11 10
[10,] 11 6 9 7 7 10 10 9 9 9 10 11
[11,] 10 11 10 10 11 7 12 8 9 12 11 10
[12,] 10 9 7 8 12 12 10 12 11 10 9 8
[13,] 8 10 7 13 7 12 10 12 7 10 10 11
[14,] 8 7 5 12 11 9 8 8 9 8 8 9
[15,] 13 10 10 6 12 10 7 9 11 6 10 11
[16,] 10 9 11 9 12 11 12 12 8 9 13 9
[17,] 7 12 12 9 13 11 8 9 11 9 10 10
[18,] 13 10 10 9 7 9 8 13 7 7 10 12
[19,] 10 8 13 10 10 7 11 13 10 12 9 9
[20,] 12 10 11 11 10 7 10 8 11 8 11 5
[21,] 10 10 9 9 11 8 8 10 13 11 11 9
[22,] 11 9 12 8 9 11 11 10 8 10 13 10
[23,] 9 11 5 11 11 10 11 10 8 10 10 13
[24,] 12 11 10 8 11 11 10 9 13 12 10 12
[25,] 9 11 7 9 11 8 7 10 9 10 10 10
[26,] 10 9 11 10 7 11 9 8 9 10 12 11
[27,] 11 6 10 11 11 9 9 9 8 11 8 13
[28,] 11 6 9 9 8 12 11 13 8 10 9 7
[29,] 13 10 11 10 10 11 7 10 10 10 10 8
[30,] 10 9 11 9 9 7 12 10 10 12 12 10
[31,] 11 9 8 11 10 9 12 7 8 9 8 11
[32,] 10 9 9 10 5 9 11 6 10 10 8 9
[33,] 8 9 12 7 12 9 11 12 11 9 11 11
[34,] 11 11 9 8 6 13 11 8 12 10 11 10
[35,] 10 10 8 6 11 7 12 10 10 9 8 11
[36,] 11 11 10 12 11 8 12 11 11 11 14 8
[37,] 7 13 12 9 7 12 10 11 10 10 4 12
[38,] 8 14 10 7 5 9 11 9 10 11 12 11
[39,] 10 10 8 8 11 11 9 11 7 10 9 10
[40,] 7 7 8 9 11 11 6 9 9 10 12 10
[41,] 7 11 5 9 11 8 9 8 11 10 9 7
[42,] 11 10 12 9 9 10 10 10 10 10 10 11
[43,] 11 7 9 13 8 10 11 11 9 10 8 9
[44,] 9 11 11 10 9 10 10 9 9 10 10 6
[45,] 12 7 13 9 9 11 8 8 10 10 10 9
[46,] 9 12 10 9 9 10 9 13 11 9 12 8
[47,] 11 9 12 12 10 10 8 11 7 9 8 10
[48,] 10 10 8 11 8 11 10 7 13 9 9 6
[49,] 13 7 9 11 8 9 11 7 8 10 6 9
[50,] 11 10 10 8 8 12 9 12 12 12 7 10
[51,] 12 7 8 12 8 10 10 8 11 11 11 10
[52,] 7 13 8 11 11 9 9 13 5 10 12 9
[53,] 12 6 11 8 11 12 9 12 12 8 8 10
[54,] 11 11 8 5 14 11 8 9 13 10 12 9
[55,] 10 7 12 12 10 9 9 11 10 12 10 6
[56,] 9 10 10 6 10 11 10 13 11 11 7 10
[57,] 13 13 10 11 9 10 12 11 8 11 11 11
[58,] 12 11 9 12 10 9 11 9 11 9 11 8
[59,] 10 9 11 10 11 13 10 10 11 11 10 11
[60,] 9 10 8 9 10 9 11 9 12 11 10 6
[61,] 8 10 12 8 9 13 11 10 8 12 11 9
[62,] 9 10 12 9 11 9 6 9 7 8 7 10
[63,] 10 12 13 10 9 12 6 8 10 10 9 13
[64,] 8 9 9 7 8 11 11 9 9 7 10 5
[65,] 9 11 7 13 11 9 11 13 9 9 14 9
[66,] 8 13 11 10 12 10 12 11 11 11 11 10
[67,] 10 13 12 10 8 12 9 11 11 11 9 10
[68,] 11 10 8 8 10 12 8 12 8 9 10 12
[69,] 11 9 11 12 8 9 6 10 10 11 10 8
[70,] 10 10 9 11 9 10 7 11 12 10 11 11
[71,] 10 10 13 8 8 9 10 11 12 9 12 10
[72,] 10 10 7 9 8 8 12 10 8 9 10 8
[73,] 11 11 9 10 12 10 10 11 9 10 12 9
[74,] 9 10 10 10 12 11 8 13 10 9 10 9
[75,] 7 9 10 8 11 9 12 11 5 11 10 11
[76,] 10 10 10 9 9 11 11 11 9 10 12 9
[77,] 12 11 10 10 8 9 10 11 11 7 8 9
[78,] 11 10 12 9 12 10 8 11 10 8 10 12
[79,] 11 11 13 7 9 11 10 11 9 8 11 8
[80,] 12 9 9 10 8 9 12 12 10 9 10 9
[81,] 12 8 7 12 10 9 9 8 11 8 10 11
[82,] 10 8 13 13 10 10 10 9 9 11 8 11
[83,] 11 10 7 8 11 7 11 12 10 9 9 10
[84,] 11 7 11 11 10 11 13 9 12 11 10 11
[85,] 12 8 11 8 10 11 11 7 10 7 8 10
[86,] 10 11 9 11 12 12 6 12 7 9 6 12
[87,] 11 12 12 12 13 8 9 11 12 11 12 9
[88,] 10 11 9 10 10 11 11 7 7 9 9 10
[89,] 9 10 10 10 6 13 10 7 11 11 9 9
[90,] 9 8 12 10 12 9 9 10 8 11 10 9
[91,] 10 12 9 9 9 8 8 10 12 9 4 11
[92,] 9 8 10 12 11 5 13 10 9 8 7 11
[93,] 10 9 11 12 10 9 9 9 10 10 7 5
[94,] 9 11 8 10 12 8 12 11 10 10 11 10
[95,] 9 11 10 9 11 9 11 10 10 9 11 9
[96,] 9 10 9 11 13 7 12 11 9 10 11 8
[97,] 10 11 8 8 8 12 8 13 12 12 8 11
[98,] 9 9 10 8 10 7 11 9 12 8 7 10
[99,] 10 11 8 10 9 7 11 11 12 10 11 11
[100,] 10 10 11 7 12 11 13 9 10 9 7 7
[,74] [,75] [,76] [,77] [,78] [,79] [,80] [,81] [,82] [,83] [,84] [,85]
[1,] 10 9 10 12 12 11 10 9 13 11 8 8
[2,] 9 12 12 8 10 10 10 7 11 11 7 10
[3,] 7 9 11 12 9 9 11 10 11 9 13 12
[4,] 12 11 13 8 12 12 10 11 12 10 10 9
[5,] 11 10 11 10 10 11 14 12 8 9 10 10
[6,] 10 13 10 6 8 9 8 9 12 14 9 11
[7,] 12 13 11 11 8 11 11 11 9 10 13 10
[8,] 5 9 11 10 10 11 7 11 12 9 10 6
[9,] 10 10 8 12 11 8 12 10 10 8 10 10
[10,] 13 9 9 10 11 12 11 11 9 11 12 10
[11,] 9 10 9 7 10 9 8 10 10 8 8 9
[12,] 9 11 9 10 8 9 10 10 10 8 11 12
[13,] 12 10 9 10 10 11 6 10 8 10 10 8
[14,] 12 10 8 8 10 10 9 11 9 8 9 6
[15,] 10 12 10 10 11 12 10 8 10 7 11 12
[16,] 8 9 6 10 10 10 8 9 9 9 9 8
[17,] 10 7 12 10 8 10 8 12 11 10 8 7
[18,] 11 11 11 11 11 9 10 8 6 8 10 12
[19,] 8 12 10 9 7 10 10 8 13 6 11 10
[20,] 8 10 12 6 12 13 10 11 10 11 9 6
[21,] 10 10 8 12 10 7 9 10 8 9 11 13
[22,] 11 11 11 8 11 10 12 9 6 11 8 7
[23,] 12 10 10 10 9 10 11 10 12 12 10 12
[24,] 7 11 10 9 11 12 9 10 10 9 11 11
[25,] 8 7 5 11 8 11 5 10 7 6 11 11
[26,] 9 12 9 10 12 7 11 10 12 9 11 12
[27,] 11 11 10 12 9 10 7 9 9 9 12 8
[28,] 11 12 10 11 9 12 10 8 5 7 7 8
[29,] 11 8 8 9 11 7 13 10 11 9 9 10
[30,] 8 9 11 9 7 11 10 10 9 11 12 6
[31,] 11 11 8 9 8 6 11 11 10 9 12 7
[32,] 13 12 11 6 10 9 8 11 12 12 9 10
[33,] 11 10 9 11 10 9 8 14 11 12 8 11
[34,] 12 11 10 11 9 8 10 9 9 9 8 11
[35,] 7 12 11 9 11 11 6 13 12 7 11 11
[36,] 8 9 11 9 8 11 13 10 10 8 8 9
[37,] 10 8 9 12 9 10 11 10 11 12 8 10
[38,] 12 11 9 11 12 11 10 12 8 10 8 9
[39,] 12 10 11 9 10 10 8 11 14 11 9 8
[40,] 8 8 9 10 11 7 6 9 5 11 11 11
[41,] 9 9 10 10 11 12 12 7 9 9 12 8
[42,] 10 12 9 9 11 10 8 10 8 7 12 10
[43,] 10 12 11 10 12 11 10 11 8 10 10 11
[44,] 11 13 8 9 14 9 8 9 8 6 10 10
[45,] 7 7 9 10 9 9 10 9 9 8 10 9
[46,] 10 10 11 12 8 10 11 10 9 9 13 9
[47,] 10 9 8 10 9 7 11 7 8 12 11 6
[48,] 10 10 11 12 9 8 11 8 8 11 10 8
[49,] 11 9 10 9 7 10 10 11 10 9 10 10
[50,] 10 8 8 11 11 11 10 10 12 10 8 11
[51,] 8 11 12 9 11 7 12 8 8 10 10 10
[52,] 12 7 9 12 9 10 8 8 10 9 8 10
[53,] 10 7 11 11 10 12 6 13 12 12 12 13
[54,] 8 12 10 11 12 10 7 12 10 8 10 8
[55,] 8 11 10 11 9 5 7 10 10 11 11 10
[56,] 9 10 10 10 12 11 10 10 9 9 9 13
[57,] 9 9 8 8 10 11 12 13 12 9 10 9
[58,] 7 8 10 9 7 11 12 8 11 10 11 8
[59,] 11 13 7 11 12 6 11 10 11 8 8 10
[60,] 12 10 8 9 12 7 10 10 10 11 8 12
[61,] 10 10 9 13 11 7 12 11 11 8 12 9
[62,] 7 8 10 8 8 6 9 11 10 10 11 8
[63,] 9 12 9 11 7 9 12 10 11 11 9 8
[64,] 9 11 11 8 7 11 10 10 7 9 10 8
[65,] 12 8 13 9 8 9 9 9 11 8 11 9
[66,] 12 7 12 11 12 13 10 6 10 7 7 9
[67,] 9 10 11 13 10 7 12 10 8 8 7 12
[68,] 11 11 10 11 10 12 12 11 10 12 8 8
[69,] 11 11 9 10 10 10 8 11 11 11 8 12
[70,] 10 7 12 11 12 9 10 9 11 12 10 10
[71,] 9 9 8 11 11 8 12 7 10 10 8 6
[72,] 9 11 12 10 7 12 10 8 9 10 9 7
[73,] 10 10 7 7 10 11 11 11 10 8 11 8
[74,] 9 12 8 9 7 10 10 12 10 11 12 8
[75,] 7 5 6 11 11 10 8 7 7 12 12 9
[76,] 6 9 8 9 10 10 9 11 10 10 12 12
[77,] 11 10 8 10 10 10 12 12 9 10 8 10
[78,] 9 10 12 10 12 9 10 11 11 12 11 6
[79,] 8 9 12 11 9 9 10 9 8 11 11 10
[80,] 12 7 11 8 11 10 12 8 9 11 9 11
[81,] 10 8 8 11 9 10 9 8 11 12 10 9
[82,] 9 9 14 12 12 11 12 11 8 10 9 6
[83,] 10 12 8 9 9 12 9 12 10 11 9 9
[84,] 10 12 10 8 13 9 11 12 10 12 8 9
[85,] 11 7 10 11 9 13 7 8 9 11 10 5
[86,] 11 11 9 10 11 11 11 8 12 11 10 10
[87,] 10 11 9 7 7 11 10 7 8 11 10 9
[88,] 9 8 11 10 10 8 12 10 9 9 11 9
[89,] 9 12 9 11 9 8 11 10 10 12 11 11
[90,] 9 9 10 12 11 9 12 11 8 8 10 6
[91,] 11 11 9 9 10 10 12 9 9 12 10 8
[92,] 10 11 11 10 9 8 9 10 10 11 9 11
[93,] 9 12 8 11 9 9 9 13 10 11 10 9
[94,] 10 9 8 8 11 12 13 5 8 7 8 12
[95,] 10 8 11 7 9 10 11 11 10 11 10 13
[96,] 12 9 10 11 12 10 9 12 10 11 10 11
[97,] 12 7 12 12 10 11 11 9 10 12 11 7
[98,] 12 8 11 9 10 9 3 10 7 10 11 10
[99,] 8 7 13 13 8 13 9 10 7 12 7 9
[100,] 10 11 10 13 8 12 10 8 11 11 12 6
[,86] [,87] [,88] [,89] [,90] [,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 8 9 10 12 10 10 11 10 8 11 11 12
[2,] 12 11 8 11 8 12 8 9 9 11 7 9
[3,] 11 9 9 10 9 12 6 11 10 12 11 11
[4,] 11 7 9 11 11 11 11 11 6 10 12 9
[5,] 7 5 7 6 12 9 10 8 11 12 12 7
[6,] 9 7 11 10 8 13 9 10 8 8 9 11
[7,] 14 10 12 11 10 8 10 12 9 11 8 10
[8,] 11 10 11 9 9 7 8 9 9 10 10 10
[9,] 8 11 13 11 10 9 10 13 10 11 10 6
[10,] 12 9 9 12 9 10 7 11 11 4 7 10
[11,] 9 9 9 9 13 11 11 12 10 11 9 10
[12,] 11 8 8 12 13 12 9 10 10 11 10 9
[13,] 10 9 10 11 10 8 9 9 5 11 12 12
[14,] 11 8 11 6 12 9 7 9 8 9 10 11
[15,] 11 7 8 12 8 12 10 10 9 12 9 10
[16,] 11 10 10 8 8 10 10 10 9 11 10 13
[17,] 12 9 10 6 11 8 8 8 12 13 9 10
[18,] 8 9 12 10 10 8 9 9 10 10 10 10
[19,] 8 11 10 9 7 10 11 12 12 11 10 5
[20,] 8 11 7 13 11 10 8 9 11 13 14 10
[21,] 9 11 8 7 9 11 11 9 10 9 7 9
[22,] 11 11 12 7 9 11 9 9 11 11 10 12
[23,] 8 10 11 7 9 12 9 8 11 8 9 10
[24,] 10 8 11 12 9 11 8 10 8 12 10 9
[25,] 8 10 11 11 9 13 9 9 11 11 11 9
[26,] 9 10 10 10 7 7 10 10 11 8 13 8
[27,] 9 10 11 8 9 10 10 11 10 11 10 10
[28,] 11 9 10 11 10 9 10 10 10 8 11 9
[29,] 11 11 8 11 8 12 10 10 10 11 8 12
[30,] 9 8 9 11 13 9 11 8 11 9 12 11
[31,] 11 9 10 11 10 11 9 11 11 8 11 10
[32,] 8 10 8 11 9 10 13 7 9 6 12 9
[33,] 10 11 12 10 10 7 9 11 11 12 12 11
[34,] 9 12 10 8 11 11 7 10 8 13 8 9
[35,] 7 8 12 9 9 9 9 11 12 11 11 11
[36,] 11 10 9 7 10 11 10 10 11 10 9 12
[37,] 10 9 10 11 9 10 10 11 10 9 9 10
[38,] 12 11 8 10 10 9 11 10 8 11 11 8
[39,] 9 10 9 9 9 11 10 10 10 8 12 11
[40,] 9 8 13 8 6 9 11 9 8 11 9 9
[41,] 9 12 11 10 11 6 8 7 10 9 8 10
[42,] 10 8 9 11 11 11 6 12 10 10 11 10
[43,] 6 12 11 11 12 12 7 12 11 12 10 10
[44,] 11 8 10 10 8 7 8 9 11 14 10 12
[45,] 6 10 9 8 9 6 11 9 8 12 7 10
[46,] 11 7 10 10 7 10 14 10 10 13 8 10
[47,] 10 6 8 12 10 9 11 8 9 10 10 11
[48,] 11 8 13 12 12 9 13 11 10 11 8 9
[49,] 9 11 9 8 9 10 9 9 10 11 13 9
[50,] 10 10 7 10 10 7 12 10 9 9 10 8
[51,] 11 10 11 9 9 11 13 8 7 11 11 12
[52,] 10 13 10 10 9 13 10 9 12 13 11 11
[53,] 13 10 9 9 12 11 9 10 11 10 9 8
[54,] 11 7 14 10 12 12 11 7 13 5 13 11
[55,] 9 9 10 11 9 11 8 8 10 12 8 6
[56,] 11 9 8 10 11 12 11 10 13 10 9 6
[57,] 12 9 12 8 10 10 10 8 10 13 12 11
[58,] 9 10 13 8 12 9 10 10 9 12 10 11
[59,] 10 9 11 11 10 11 11 12 10 11 9 11
[60,] 12 8 10 9 8 8 11 11 7 8 11 14
[61,] 10 8 13 9 10 7 7 9 9 6 12 11
[62,] 10 11 10 11 8 13 11 11 11 8 8 11
[63,] 12 9 9 8 10 9 10 10 8 10 11 10
[64,] 9 8 9 11 6 8 7 6 7 11 11 10
[65,] 10 9 9 10 11 10 13 11 12 9 10 9
[66,] 8 8 6 5 7 8 10 12 11 7 11 10
[67,] 9 11 9 9 10 12 8 11 11 9 8 8
[68,] 8 10 10 12 8 10 11 11 9 12 12 10
[69,] 10 9 10 9 11 9 9 10 12 9 10 11
[70,] 10 12 9 11 10 9 10 8 6 13 10 11
[71,] 9 11 11 9 8 10 11 7 9 12 8 8
[72,] 11 8 11 8 11 10 9 8 11 10 10 12
[73,] 8 8 9 9 9 10 10 9 7 13 13 12
[74,] 6 11 6 6 11 11 9 12 8 9 9 6
[75,] 10 8 10 12 7 10 13 4 11 11 8 13
[76,] 9 10 8 9 10 9 10 11 9 11 12 10
[77,] 10 10 12 9 10 14 12 11 10 6 9 9
[78,] 9 10 10 12 12 11 10 11 10 9 9 9
[79,] 10 11 12 6 12 10 11 10 8 10 9 11
[80,] 11 9 12 13 9 14 8 10 7 9 9 11
[81,] 8 10 10 10 8 9 8 11 11 10 8 6
[82,] 6 8 7 5 12 12 13 11 11 8 12 8
[83,] 13 10 8 8 10 6 11 11 9 12 12 10
[84,] 10 8 8 12 10 7 11 12 9 9 13 10
[85,] 13 7 11 9 6 10 11 12 11 11 9 12
[86,] 9 11 8 10 11 8 8 8 7 7 11 11
[87,] 8 9 11 10 11 11 8 10 8 9 10 6
[88,] 8 11 9 6 12 8 12 10 6 11 10 8
[89,] 9 12 8 9 9 10 8 10 11 9 8 9
[90,] 8 10 10 12 10 12 11 11 10 8 7 11
[91,] 6 11 9 9 8 9 6 7 8 10 12 13
[92,] 12 8 9 11 10 8 7 10 9 6 12 14
[93,] 10 12 12 11 9 8 11 8 10 8 9 9
[94,] 10 6 12 8 11 14 7 9 9 10 9 10
[95,] 10 12 11 11 9 10 8 7 13 10 10 11
[96,] 12 10 5 11 10 11 8 11 8 11 8 8
[97,] 7 9 10 10 11 11 11 13 9 10 11 9
[98,] 9 11 9 12 12 9 10 12 9 9 6 9
[99,] 12 9 11 10 9 10 9 7 9 11 12 12
[100,] 9 11 9 9 9 10 12 10 7 12 11 13
[,98] [,99] [,100]
[1,] 9 11 8
[2,] 10 10 10
[3,] 11 12 9
[4,] 11 12 8
[5,] 13 10 8
[6,] 12 11 10
[7,] 10 11 12
[8,] 11 13 10
[9,] 9 10 9
[10,] 11 7 12
[11,] 10 10 12
[12,] 10 11 8
[13,] 9 11 9
[14,] 8 11 10
[15,] 10 10 8
[16,] 10 10 12
[17,] 6 11 11
[18,] 11 10 10
[19,] 11 10 11
[20,] 9 13 12
[21,] 9 7 9
[22,] 12 10 11
[23,] 10 10 10
[24,] 10 11 9
[25,] 12 9 10
[26,] 13 7 12
[27,] 11 10 10
[28,] 11 9 12
[29,] 12 9 10
[30,] 8 11 7
[31,] 7 8 9
[32,] 10 10 9
[33,] 9 11 8
[34,] 9 10 12
[35,] 9 9 10
[36,] 10 12 12
[37,] 12 11 10
[38,] 10 11 9
[39,] 11 9 13
[40,] 8 8 10
[41,] 7 7 9
[42,] 13 11 10
[43,] 8 12 8
[44,] 11 11 11
[45,] 9 10 9
[46,] 12 11 13
[47,] 9 11 13
[48,] 11 12 8
[49,] 11 10 11
[50,] 12 11 9
[51,] 11 8 10
[52,] 10 11 9
[53,] 9 12 10
[54,] 7 11 14
[55,] 10 9 10
[56,] 6 11 11
[57,] 10 13 11
[58,] 10 11 9
[59,] 11 10 7
[60,] 7 12 8
[61,] 8 12 10
[62,] 8 11 10
[63,] 12 9 9
[64,] 13 8 8
[65,] 7 12 9
[66,] 9 7 10
[67,] 11 12 8
[68,] 9 10 9
[69,] 9 7 7
[70,] 10 9 13
[71,] 8 11 9
[72,] 10 12 8
[73,] 11 11 10
[74,] 11 8 10
[75,] 5 9 11
[76,] 10 10 8
[77,] 8 12 5
[78,] 10 9 12
[79,] 8 8 10
[80,] 7 10 10
[81,] 11 11 9
[82,] 11 6 10
[83,] 10 9 10
[84,] 8 12 11
[85,] 11 9 10
[86,] 11 11 9
[87,] 7 8 10
[88,] 11 6 11
[89,] 10 10 9
[90,] 13 9 12
[91,] 7 8 11
[92,] 11 11 11
[93,] 13 9 7
[94,] 10 9 9
[95,] 6 12 8
[96,] 12 11 9
[97,] 11 11 10
[98,] 9 11 11
[99,] 8 9 9
[100,] 10 11 11# we can also give our list elements names
chaos_list <- list(women=people, binom=numbers, macri=words, binom2=mat)
# to subset a list, we can either call the list item number
# or use the names
chaos_list$women[1] "Bethune" "Cady Stanton" "Roosevelt" # note that we use two square brackets for the top-level element in a list
chaos_list[[1]] [1] "Bethune" "Cady Stanton" "Roosevelt" # and regular square brackets to subset within that
chaos_list[[1]][3][1] "Roosevelt"4.9 Vectorizing operations
Vectorizing stuff means we go across the whole of a data structure and do the same thing to every item. It is really efficient for batch operations. The main functions to do this in base R are the apply family, though tbh, I never use tapply or sapply and only ever use apply and lapply because I like data.frames and lists. do.call is also really useful for lists and worth looking into if you have some reallllly repetitive tasks to do.
lapply(chaos_list, head)$women
[1] "Bethune" "Cady Stanton" "Roosevelt"
$binom
[1] 2 0 1 3 1 2
$macri
[1] "README: Behavioral abilities and gene expression associated with social responsiveness in honeybees: Open Source Data"
[2] "We have submitted our raw data related to colony activity (ColonyActivity_Data.csv) and collection of pollen (PollenTraps_Data.csv), gustatory responsiveness (GustatoryResp_Data.csv) and learning abilities (LearningScore_Data.csv), and gene expression (GeneExpression_Data.csv)."
[3] "Descriptions:"
[4] "ColonyActivity_Data"
[5] "•\tMoment: Pesticide application moment"
[6] "•\tYear: Sampling year"
$binom2
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 5 12 9 9 9 10 11 12 10 8 12 13 11 10
[2,] 12 10 9 8 6 12 10 10 9 11 11 10 9 9
[3,] 9 6 9 7 11 9 8 10 9 9 10 10 11 11
[4,] 7 4 12 12 8 8 8 10 8 10 11 9 6 10
[5,] 11 12 8 10 9 13 8 9 9 11 5 12 10 10
[6,] 11 12 11 9 9 10 11 11 10 11 10 9 6 6
[,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26]
[1,] 9 9 5 9 11 10 10 12 9 10 9 12
[2,] 10 12 10 11 9 8 7 11 10 11 6 12
[3,] 10 7 11 7 9 10 9 9 8 7 11 9
[4,] 7 10 9 12 8 12 11 12 8 12 11 11
[5,] 4 12 7 7 7 12 12 7 9 12 8 10
[6,] 8 11 9 10 13 12 7 11 11 9 11 9
[,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37] [,38]
[1,] 7 8 12 9 12 11 12 8 8 5 12 9
[2,] 9 12 10 9 13 10 9 9 8 9 7 9
[3,] 7 12 8 10 10 10 12 9 12 10 8 9
[4,] 9 10 11 8 10 12 8 7 8 11 5 9
[5,] 9 10 9 7 11 12 7 11 11 9 11 12
[6,] 10 6 10 10 12 13 11 7 11 9 11 7
[,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46] [,47] [,48] [,49] [,50]
[1,] 10 10 10 12 10 10 9 5 9 9 11 12
[2,] 10 9 9 10 9 8 9 11 8 10 10 10
[3,] 11 12 11 8 8 9 9 11 10 9 12 12
[4,] 8 11 9 10 8 10 11 8 11 11 11 7
[5,] 11 10 8 10 11 11 11 11 9 9 8 9
[6,] 8 9 8 12 11 8 11 12 10 12 8 9
[,51] [,52] [,53] [,54] [,55] [,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] 9 10 11 11 10 9 12 9 11 12 12 10
[2,] 11 14 10 10 10 9 10 12 8 9 11 8
[3,] 10 10 12 13 13 10 10 8 9 7 7 8
[4,] 8 10 11 10 7 9 7 11 11 9 12 8
[5,] 7 10 9 8 13 9 10 9 10 12 11 7
[6,] 11 11 11 12 12 8 11 14 10 9 12 10
[,63] [,64] [,65] [,66] [,67] [,68] [,69] [,70] [,71] [,72] [,73] [,74]
[1,] 11 11 9 10 10 9 8 11 10 12 11 10
[2,] 7 11 11 13 10 7 7 6 12 7 10 9
[3,] 11 9 10 8 9 10 7 11 11 7 9 7
[4,] 12 10 10 7 10 9 12 10 11 11 11 12
[5,] 11 11 11 8 7 11 9 9 11 9 10 11
[6,] 9 8 10 11 11 9 10 11 7 10 9 10
[,75] [,76] [,77] [,78] [,79] [,80] [,81] [,82] [,83] [,84] [,85] [,86]
[1,] 9 10 12 12 11 10 9 13 11 8 8 8
[2,] 12 12 8 10 10 10 7 11 11 7 10 12
[3,] 9 11 12 9 9 11 10 11 9 13 12 11
[4,] 11 13 8 12 12 10 11 12 10 10 9 11
[5,] 10 11 10 10 11 14 12 8 9 10 10 7
[6,] 13 10 6 8 9 8 9 12 14 9 11 9
[,87] [,88] [,89] [,90] [,91] [,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 9 10 12 10 10 11 10 8 11 11 12 9
[2,] 11 8 11 8 12 8 9 9 11 7 9 10
[3,] 9 9 10 9 12 6 11 10 12 11 11 11
[4,] 7 9 11 11 11 11 11 6 10 12 9 11
[5,] 5 7 6 12 9 10 8 11 12 12 7 13
[6,] 7 11 10 8 13 9 10 8 8 9 11 12
[,99] [,100]
[1,] 11 8
[2,] 10 10
[3,] 12 9
[4,] 12 8
[5,] 10 8
[6,] 11 10apply(chaos_list$binom2, 1, FUN = max) [1] 13 14 13 13 14 14 14 13 13 13 14 13 13 13 14 13 13 14 13 14 13 13 14 13 13
[26] 13 13 14 13 14 14 13 14 13 13 14 14 14 14 13 14 14 14 14 13 14 13 13 13 12
[51] 13 13 13 14 13 14 13 13 13 14 13 14 14 13 14 14 13 14 14 13 13 13 14 14 13
[76] 13 14 14 13 14 13 14 14 13 13 14 13 12 13 14 14 14 13 14 14 13 13 13 14 13apply(chaos_list$binom2, 1, FUN = mean) [1] 9.97 9.65 9.70 9.75 9.66 9.93 9.95 10.02 9.72 9.76 9.94 9.82
[13] 9.79 9.61 9.82 9.59 9.79 9.65 9.73 9.74 9.63 9.89 9.91 10.09
[25] 9.40 9.56 9.74 9.66 9.81 9.75 9.76 9.59 10.06 9.92 9.98 9.88
[37] 9.81 9.99 9.74 9.38 9.31 9.88 10.08 9.79 9.56 10.05 9.56 9.83
[49] 9.48 9.94 9.97 9.76 10.13 10.13 9.71 9.85 10.09 9.73 9.92 9.70
[61] 10.00 9.95 9.86 9.40 10.09 9.83 9.60 9.95 9.88 9.88 9.92 9.63
[73] 9.92 9.89 9.75 9.59 9.87 9.92 9.69 9.80 9.69 9.75 9.76 9.80
[85] 9.80 9.84 9.61 9.70 10.00 9.87 9.65 9.84 9.87 9.69 9.97 9.86
[97] 9.95 9.60 9.63 9.87rowMeans(chaos_list$binom2) [1] 9.97 9.65 9.70 9.75 9.66 9.93 9.95 10.02 9.72 9.76 9.94 9.82
[13] 9.79 9.61 9.82 9.59 9.79 9.65 9.73 9.74 9.63 9.89 9.91 10.09
[25] 9.40 9.56 9.74 9.66 9.81 9.75 9.76 9.59 10.06 9.92 9.98 9.88
[37] 9.81 9.99 9.74 9.38 9.31 9.88 10.08 9.79 9.56 10.05 9.56 9.83
[49] 9.48 9.94 9.97 9.76 10.13 10.13 9.71 9.85 10.09 9.73 9.92 9.70
[61] 10.00 9.95 9.86 9.40 10.09 9.83 9.60 9.95 9.88 9.88 9.92 9.63
[73] 9.92 9.89 9.75 9.59 9.87 9.92 9.69 9.80 9.69 9.75 9.76 9.80
[85] 9.80 9.84 9.61 9.70 10.00 9.87 9.65 9.84 9.87 9.69 9.97 9.86
[97] 9.95 9.60 9.63 9.87apply(chaos_list$binom2, 2, FUN = mean) [1] 10.02 10.10 9.80 9.99 9.46 9.64 9.85 9.91 10.03 9.65 9.76 9.99
[13] 9.73 9.62 9.63 10.05 9.71 9.42 9.74 9.74 10.01 9.67 9.66 10.01
[25] 9.88 9.92 9.69 9.84 9.88 9.76 9.73 9.98 9.78 9.37 9.74 9.75
[37] 9.83 9.78 9.89 9.54 9.51 9.89 9.63 9.77 9.86 9.86 10.02 9.75
[49] 10.15 9.77 9.62 9.90 9.80 9.73 9.77 9.82 9.60 9.56 9.96 9.93
[61] 10.01 10.00 9.83 9.77 9.58 9.84 9.81 9.79 9.99 9.79 9.79 9.70
[73] 9.64 9.82 9.86 9.81 9.96 9.87 9.81 9.85 9.86 9.66 9.84 9.87
[85] 9.35 9.72 9.47 9.83 9.66 9.72 9.94 9.70 9.78 9.58 10.10 10.02
[97] 9.95 9.82 10.10 9.84colMeans(chaos_list$binom2) [1] 10.02 10.10 9.80 9.99 9.46 9.64 9.85 9.91 10.03 9.65 9.76 9.99
[13] 9.73 9.62 9.63 10.05 9.71 9.42 9.74 9.74 10.01 9.67 9.66 10.01
[25] 9.88 9.92 9.69 9.84 9.88 9.76 9.73 9.98 9.78 9.37 9.74 9.75
[37] 9.83 9.78 9.89 9.54 9.51 9.89 9.63 9.77 9.86 9.86 10.02 9.75
[49] 10.15 9.77 9.62 9.90 9.80 9.73 9.77 9.82 9.60 9.56 9.96 9.93
[61] 10.01 10.00 9.83 9.77 9.58 9.84 9.81 9.79 9.99 9.79 9.79 9.70
[73] 9.64 9.82 9.86 9.81 9.96 9.87 9.81 9.85 9.86 9.66 9.84 9.87
[85] 9.35 9.72 9.47 9.83 9.66 9.72 9.94 9.70 9.78 9.58 10.10 10.02
[97] 9.95 9.82 10.10 9.844.9.1 Data visualization (briefly)
For the last part of lab today, we are going to practice some data visualization. With the Macri et al. data, let’s recreate Figure 2A and 2B. I’m not 100% certain we can recreate them perfectly because I’m not sure if 2A is showing a modeled response or the raw data, but we’ll make an attempt!
