class: center, middle, inverse, title-slide # Community assembly patterns of novel treeline ecosystems promoted by invasive pines ### Gabriel Muñoz ### Sep. 2018 --- ## Preliminary info: **PhD. proposal (in progress)** - Supervisor: [Dr. Jean-Phillipe Lessard](http://jeanphilippelessard.com/) <br> .center[  ] Link to the presentation: insert link here! --- class: inverse, center, middle # Background --- ## What is R? .pull-left[ R is an open source programming language designed for statistical analysis, data mining, and data visualization. ] .pull-right[  ] --- ## Why use R? **It's open source** Improved **by** the public, **for** the public! **Free!** .right[  ] --- ## Why use R? .center[  ] **It's compatible** R works on most existing operating systems --- ## Why use R? What people have traditionally done to analyze their data: <div id="htmlwidget-53764d0d84ded28b0e8f" style="width:480px;height:480px;" class="grViz html-widget"></div> <script type="application/json" data-for="htmlwidget-53764d0d84ded28b0e8f">{"x":{"diagram":"\n digraph {\n\n node [shape = oval, fillcolor = PaleTuruoise]\n Data; Graphs; Tables; Statistics\n\n node [shape = box]\n Sigmaplot; Excel; SAS\n\n ##add arrows\n edge [arrowhead = none]\n Data -> Sigmaplot; Data -> Excel; Data -> SAS;\n\n edge [arrowhead = normal]\n Sigmaplot -> Graphs; Excel -> Tables; SAS -> Statistics;\n\n }","config":{"engine":"dot","options":null}},"evals":[],"jsHooks":[]}</script> --- ## Why use R? R allows you to do everything with one program, which is nice! <div id="htmlwidget-771c2c8b5a94b666791c" style="width:480px;height:480px;" class="grViz html-widget"></div> <script type="application/json" data-for="htmlwidget-771c2c8b5a94b666791c">{"x":{"diagram":"\n digraph {\n\n node [shape = oval, fillcolor = PaleTuruoise]\n Data; Graphs; Tables; Statistics\n\n node [shape = box]\n R\n\n ##add arrows\n edge [arrowhead = none]\n Data -> R;\n\n edge [arrowhead = normal]\n R -> Graphs; R -> Tables; R -> Statistics;\n\n }","config":{"engine":"dot","options":null}},"evals":[],"jsHooks":[]}</script> --- ## Why use R? - More and more scientists use it every year! - Increasing capacities .center[] --- ## Challenge .pull-left2[ - Throughout these workshops you will be presented with a series of challenges that will be indicated by these rubik's cubes - During challenges, collaborate with your neighbours! ] .pull-right2[  ] --- ## Challenge 1 ![:cube]() .center[Open Rstudio] <br> .center[  ] --- ## The Rstudio console  --- ## Note for Windows user If the restriction `unable to write on disk` appears when you try to open R-Studio, .alert[don't worry!] We have the solution! Right-click on your R-Studio icon and chose: "Execute as administrator" to open the program. --- ## Note for Windows user **Common problem** installation process of some packages .comment[(especially a problem for permission when installing libraries)] --- ## Note for Mac user Please install the developer package https://developer.apple.com/downloads/index.action# --- ## How to read the console Text in the console typically looks like this: .comment[You always have to push "enter" for the input to run in the console.] ```r output # [1] "This is the output" ``` --- ## How to read the console ```r output # [1] "This is the output" ``` What does this bracket `[]` in the output means? --- ## How to read the console ```r output # [1] "This is the output" ``` The bracket help you to locate *where* you are in the output ``` # [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 # [24] 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 ``` --- ## Error and Warning - .alarm[Warning message] happens with unexpected behavior in your process. You can continue to proceed your process. - .alarm[Error message] will stop the current execution. It indicates a problem in your code .center[ **To solve *error*, google is your bestfriend!** ] --- class: inverse, center, middle # Using R as a calculator --- ## Addition, substraction, etc. - Additions and Substractions ```r 1+1 # [1] 2 10-1 # [1] 9 ``` --- ## Additions, substractions, etc. - Multiplications and Divisions ```r 2*2 # [1] 4 8/2 # [1] 4 ``` --- ## Additions, substractions, etc. - Exponents ```r 2^3 # [1] 8 ``` --- ## Challenge 2 ![:cube]() Use R to calculate the following skill testing question: $$ 2+16*24-56 $$ <br> **Hints**: The `*` symbol is used to multiply --- ## Challenge 2: Solution ![:cube]() $$ 2+16*24-56 $$ ```r 2+16*24-56 # [1] 330 ``` --- ## Challenge 3 ![:cube]() Use R to calculate the following skill testing question: $$ 2+16*24-56 / (2+1)-457 $$ **Hints**: Think about the order of the operation. --- ## Challenge 3: Solution ![:cube]() Use R to calculate the following skill testing question: $$ 2+16*24-56 / (2+1)-457 $$ ```r 2+16*24-56/(2+1)-457 # [1] -89.66667 ``` .comment[Note that R follows the order of the operations] --- ## R command line tip Use the **Up** and **Down** arrow keys to reproduce previous commands. Give it a try! .center[  ] --- ## Challenge 4 ![:cube]() What is the area of this circle, with a radius of `\(5\ cm\)`? <img src="Workshop01_Slides_files/figure-html/unnamed-chunk-15-1.png" width="480" style="display: block; margin: auto;" /> --- ## Challenge 4: Solution ![:cube]() What is the area of a circle, with a radius of `\(5\ cm\)`? ```r 3.1416*5^2 # [1] 78.54 ``` .comment[**Tip**: Note that `R` has some built-in constant such as `\(\pi\)`, so you can write:] ```r pi*5^2 # [1] 78.53982 ``` --- class: inverse, center, middle # Objects --- ## Objects - One of the most useful concept in `R`! - You can store values as named objects using the assignement operator `<-` ```r object name <- assigned value ``` The value on the **right** is assigned to the name on the **left** with the assignement operator `<-` .comment[It is also possible to use the `=` sign, but it is better to **avoid it** as it is also used for other purposes.] --- ## Objects names - Objects names can only include: | Type | Symbol | |------------|:-------:| | Letters | a-z A-Z | | Numbers | 0-9 | | Period | . | | Underscore | _ | - Objects names should **always** begin with a letter. - `R` is **case sensitive**, the names `Data1` and `data1` are not the same. - You can **not** use special characters! (@, /, etc.) --- ## Object names: good practices - Try having short and explicit names for your variables. Naming a variable `var` is not very informative. - Adding spaces after and before the `<-` is recommended because it adds clarity. - When typing the object's name, `R` return its value. ```r mean.x <- (2+6)/2 mean.x # [1] 4 ``` --- ## Challenge 5 ![:cube]() <br> Create an object with a value of 1+1.718282 (Euler's number) and name it `euler.value`. --- ## Challenge 5: Solution ![:cube]() <br> Create an object with a value of 1+1.718282 (Euler's number) and name it `euler.value`. ```r euler.value <- 1+1.718282 euler.value # [1] 2.718282 ``` --- ## Challenge 6 ![:cube]() Create a second object (you decide the name) with a name that starts with a number. What happens? --- ## Challenge 6: Solution ![:cube]() Create a second object (you decide the name) with a name that starts with a number. What happens? Creating an object name that starts with a number returns the following error: ```r Error: unexpected symbol in "[your object name]" ``` --- ## R command line tip - Use the tab key to autocomplete scripts - This helps avoid spelling errors and speeds up command entering Let's try it! --- ## R command line tip - Enter `eu` - Push tab - Use the arrow keys and push enter to select the correct autocomplete --- class: inverse, center, middle # Types of data structures in R --- ## Types of data structures in R - Vectors - Data frames - Matrices, arrays and lists --- ## Vectors - An entity consisting of a list of related values - A single value is called an *atomic value* - All values of a vector must have the **same mode** (or class). * Numeric: only numbers * Logical: True/False entries * Character: Text, or a mix of text and other modes --- ## Vectors - Creating vectors usually require the `c` function .comment[`c` stands for *combine* or *concatenate*.] - The syntax is: ```r vector <- c(value1, value2, ...) ``` --- ## Vectors - Numeric vectors ```r num.vector <- c(1, 4, 3, 98, 32, -76, -4) num.vector # [1] 1 4 3 98 32 -76 -4 ``` - Character vectors ```r char.vector <- c("blue", "red", "green") char.vector # [1] "blue" "red" "green" ``` --- ## Vectors - Logical vectors ```r bool.vector <- c(TRUE, TRUE, FALSE) bool.vector # [1] TRUE TRUE FALSE ``` You can just write T for TRUE and F for FALSE, it's exactly the same ```r bool.vector2 <- c(T, T, F) bool.vector2 # [1] TRUE TRUE FALSE ``` --- ## Challenge 7 ![:cube]() Create a vector containing the first 5 odd numbers, starting from 1, and name it `odd.n` --- ## Challenge 7: Solution ![:cube]() Create a vector containing the first 5 odd numbers, starting from 1, and name it `odd.n` ```r odd.n <- c(1,3,5,7) ``` --- ## Vectors We can use vectors for calculations ```r x <- c(1:5) y <- 6 ``` .comment[The semicolon symbol `:` is use to combine all values between the first and the second provided numbers. `c(1:5)` returns `1, 2, 3, 4, 5`] ```r x+y # [1] 7 8 9 10 11 x*y # [1] 6 12 18 24 30 ``` --- ## Data Frames - Used to store data tables - A list of vectors of the same length - Columns = variables - Rows = observations, sites, cases, replicates, ... - Differents columns can have different modes --- ## Data Frames Let's say you want to store this table in `R`: |ID of the site|soil pH|# of species|treatment| |---|---|---|---| |A1.01|5.6|17|Fert| |A1.02|7.3|23|Fert| |B1.01|4.1|15|No Fert| |B1.02|6.0|7|No Fert| --- ## Data Frames One way of doing it is: - Start by creating vectors ```r siteID <- c("A1.01", "A1.02", "B1.01", "B1.02") soil_pH <- c(5.6, 7.3, 4.1, 6.0) num.sp <- c(17, 23, 15, 7) treatment <- c("Fert", "Fert", "No_fert", "No_fert") ``` - We then combine them using the function `data.frame` ```r my.first.df <- data.frame(siteID, soil_pH, num.sp, treatment) ``` .comment[We will come back to the `data.frame` function later.] --- ## Data Frames ```r my.first.df # siteID soil_pH num.sp treatment # 1 A1.01 5.6 17 Fert # 2 A1.02 7.3 23 Fert # 3 B1.01 4.1 15 No_fert # 4 B1.02 6.0 7 No_fert ``` --- ## Matrices, Arrays and Lists .center[  ] --- ## Indexing objects Sometimes, we only want to look at or extract part of our data. This is done using **brackets:** `[]` We indicate the **position** of the values we want to see between the brackets. It's called *indexing*. --- ## Indexing vectors You can use indexing to chose a particular position, let's say we want to see the second value of our `odd.n` vector ```r odd.n[2] # [1] 3 ``` It also work with multiple position: ```r odd.n[c(2,4)] # [1] 3 7 ``` It can be used to remove some values at particular positions ```r odd.n[-c(1,2)] # [1] 5 7 ``` --- ## Indexing vectors If you select a position that is not in the vector it will return: ```r odd.n[c(1,5)] # [1] 1 NA ``` You can also use conditions to select values: ```r odd.n[odd.n > 4] # [1] 5 7 ``` ```r char.vector[char.vector == "blue"] # [1] "blue" ``` .comment[Logical statements such as `>` will be described in more details later.] --- ## Challenge 8 ![:cube]() Using the vector `num.vector` - Extract the 4th value - Extract the 1st and 3rd values - Extract all values except for the 2nd and the 4th --- ## Challenge 8: Solution ![:cube]() - Extract the 4th value ```r num.vector[4] # [1] 98 ``` - Extract the 1st and 3rd values ```r num.vector[c(1,3)] # [1] 1 3 ``` - Extract all values except for the 2nd and the 4th ```r num.vector[c(-2,-4)] # [1] 1 3 32 -76 -4 ``` --- ## Challenge 9 ![:cube]() Explore the difference between these 2 lines of code: ```r char.vector == "blue" char.vector[char.vector == "blue"] ``` --- ## Challenge 9: Solution ![:cube]() ```r char.vector == "blue" # [1] TRUE FALSE FALSE ``` In this line of code, you **test a logical statement**. For each entry in the `char.vector`, `R` checks whether the entry is equal to `"blue"` or not. ```r char.vector[char.vector == "blue"] # [1] "blue" ``` In this line of code, you ask `R` to extract all values within the `col.vector` vector that are exactly equal to `"blue"`. --- ## A quick note on logical statements `R` allows testing of logical statements, *i.e.* testing whether a statement is true or false. You need to use logical operators for that. |Operator|Description|Example| |-------------|-------------------------|-------------------------------| |`<` and `>` |less than or greater than|`odd.n > 3` | |`<=` and `>=`|less/greater or equal to |`odd.n >= 3` | |`==` |exactly equal to |`odd.n == 3` | |`!=` |not equal to |`odd.n != 3` | |`x`&#124;`y` |x OR y |`odd.n[odd.n >= 5` &#124; `odd.n < 3]`| |`x & y` |x AND y |`odd.n[odd.n >=3 & odd.n < 7]` | --- ## Indexing data frames To index a data frame you must specify two dimensions: row and column number, using the following syntax: ```r data.frame.name[row, column] ``` --- ## Indexing data frames: examples `my.first.df[1,]`  Extracts the first line .comment[Note that an empty index select **all** the values.] `my.first.df[,3]`  Extracts the third column `my.first.df[2,4]`  Extracts the second element of the fourth column --- ## Indexing data frames: examples `my.first.df[c(2,4),]`  Extracts lines 2 to 4 .comment[The examples given so far are also valid for indexing matrices, this is not the case for the following examples.] `my.first.df$siteID`  Extracts the variable `siteID` from the data frame `my.first.df$siteID[2]`  Extracts the second value of the variable `siteID` from the data frame `my.first.df[c("siteID", "soil_pH")]`  Extracts the `siteID` and `soil_pH` variables from the data frame. --- ## Challenge 10 ![:cube]() 1. Extract the `num.sp` column from `my.first.df` and multiply its value by the first four values of `num.vec`. 2. After that, write a statement that checks if the values you obtained are greater than 25. --- ## Challenge 10: Solution ![:cube]() 1. Extract the `num.sp` column from `my.first.df` and multiply its value by the first four values of `num.vec`. ```r my.first.df$num.sp * num.vector[c(1:4)] # [1] 17 92 45 686 # or my.first.df[,3] * num.vector[c(1:4)] # [1] 17 92 45 686 ``` 2. After that, write a statement that checks if the values you obtained are greater than 25. ```r (my.first.df$num.sp * num.vector[c(1:4)]) > 25 # [1] FALSE TRUE TRUE TRUE ``` --- class: inverse, center, middle # Functions --- ## Functions .pull-left2[ A function is a tool to simplify your life. It allows you to quickly execute operations on objects without having to write every mathematical step. A function needs entry values called **arguments** (or parameters). It then performs hidden operations using these arguments and gives a **return value**. ] .pull.right2[  ] --- ## Functions To use (call) a function, the command must be structured properly, following the "grammar rules" of the `R` language: the syntax. ```r function_name(argument 1, argument 2) ``` --- ## Arguments Arguments are **values** and **instructions** the function needs to run. Objects storing these values and instructions can be used in functions: ```r a <- 3 b <- 5 sum(a,b) # [1] 8 ``` --- ## Challenge 11 ![:cube]() - Create a vector `a` that contains all the numbers from 1 to 5 - Create an object `b` with a value of 2 - Add `a` and `b` together using the basic `+` operator and save the result in an object called `result_add` - Add `a` and `b` together using the `sum` function and save the result in an object called `result_sum` - Compare `result_add` and `result_sum`. Are they different? - Add 5 to `result_sum` function using the `sum` function --- ## Challenge 11: Solution ![:cube]() ```r a <- c(1:5) b <- 2 result_add <- a + b result_sum <- sum(a,b) ``` ```r result_add # [1] 3 4 5 6 7 result_sum # [1] 17 sum(result_sum, 5) # [1] 22 ``` --- ## Challenge 11: Solution ![:cube]() The operation `+` on the vector `a` adds 2 to each element. The result is a vector. The function `sum` concatenates all the values provided and then sum them. It is the same as doing 1+2+3+4+5+2. --- ## Arguments Arguments each have a **name** that can be provided during a function call. If the name is not present, the order of the arguments does matter. If the name is present, the order does not matter. --- ## Challenge 12 ![:cube]() `plot` is a function that draws a graph of y as a function of x. It requires two arguments names *x* and *y*. What are the differences between the following lines? ```r a <- 1:100 b <- a^2 plot(a,b) plot(b,a) plot(x = a, y = b) plot(y = b, x = a) ``` --- ## Challenge 12: Solution ![:cube]() <img src="Workshop01_Slides_files/figure-html/unnamed-chunk-52-1.png" width="480" style="display: block; margin: auto;" /> --- ## Challenge 12: Solution ![:cube]() .pull-left[ ```r plot(a,b) ``` <img src="Workshop01_Slides_files/figure-html/unnamed-chunk-54-1.png" width="345.6" style="display: block; margin: auto;" /> ] .pull-right[ ```r plot(b,a) ``` <img src="Workshop01_Slides_files/figure-html/unnamed-chunk-56-1.png" width="345.6" style="display: block; margin: auto;" /> ] The shape of the plot changes, as we did not provided the arguments names, the order is important. --- ## Challenge 12: Solution ![:cube]() .pull-left[ ```r plot(x = a, y = b) ``` <img src="Workshop01_Slides_files/figure-html/unnamed-chunk-58-1.png" width="345.6" style="display: block; margin: auto;" /> ] .pull-right[ ```r plot(y = b, x = a) ``` <img src="Workshop01_Slides_files/figure-html/unnamed-chunk-60-1.png" width="345.6" style="display: block; margin: auto;" /> ] Same as `plot(a,b)`. The argument names are provided, the order is not important. --- ## Packages Packages are a **grouping of functions** and/or **datasets** that share a similar **theme**, e.g. statistics, spatial analysis, plotting, etc. **Everyone** can develop packages and make them available to others. They are usually available through the *Comprehensive R Archive Network* or CRAN: http://cran.r-project.org/web/packages/ Currently, more than 5877 packages are publicly availables. --- ## Packages To install packages on your computer, use the function `install.packages`. ```r install.packages("package name") ``` Installing a package is not enough to use it. You need to load it into your workspace before using it using the `library` function. ```r library(package name) ``` --- ## Package: an example ```r install.packages("ggplot2") ``` ```r Installing package into '/home/labo/R/x86_64-redhat-linux-gnu-library/3.3' (as 'lib' is unspecified) ``` ```r qplot(1:10, 1:10) ``` ```r ## Error: could not find function "qplot" ``` --- ## Package name: an example ```r library(ggplot2) qplot(1:10, 1:10) ``` <img src="Workshop01_Slides_files/figure-html/unnamed-chunk-65-1.png" width="384" style="display: block; margin: auto;" /> --- class: inverse, center, middle # Getting help --- ## Searching for functions WOW! `R` is so great! So many functions to do what I want! But... how do I find them? --- ## Searching for functions To find a function that does something specific in your installed packages, you can use `??` followed by a search term. Let's say we want to create a *sequence* of odd numers between 0 and 10 as we did earlier. We can search in our packages all the functions with the word "sequence" in them: ```r ??sequence ``` --- ## Search results  --- ## Search results  --- ## Search results  --- ## Getting help with functions OK! SO let's use the `seq` function!! But wait... how does it work? What arguments does it need? To find information about a function in particular, use `?` ```r ?seq ``` --- ## Help pages  --- ## Description - `function_name {package_name}` - Description: a short description of what the function does.  --- ## Usage - How to call the function - If `name = value` is present, a default value is provided if the argument is missing. The argument becomes optional. - Other related functions described in this help page  --- ## Arguments - Description of all the arguments and what they are used for  --- ## Details - A detailed description of how the functions work and their characteristics  --- ## Value - A description of the return value  --- ## See Also - Other related functions that can be useful  --- ## Examples - Reproducibles examples  --- ## Challenge 13 ![:cube]() 1. Create a sequence of even numbers from 0 to 10 using the `seq` function. 2. Create a unsorted vector of your favourite numbers, then sort your vector in reverse order. --- ## Challenge 13: Solutions ![:cube]() 1. Create a sequence of even numbers from 0 to 10 using the `seq` function. .pull-left[ ```r seq(from=0, to=10, by=2) # [1] 0 2 4 6 8 10 ``` ] .pull-right[ ```r seq(0,10,2) # [1] 0 2 4 6 8 10 ``` ] 2. Create a unsorted vector of your favourite numbers, then sort your vector in reverse order. ```r numbers <- c(2,4,22,6,26) sort(numbers, decreasing = T) # [1] 26 22 6 4 2 ``` --- ## Other ways to get help Usually, your best source of information will be your favorite search engine! Here are some tips on how to use them efficiently: - Search in English - Use the keyword "R" at the beginning of your search - Define precisely what you are looking for - Learn to read discussion forums. Chances are other people already had your problem and asked about it. - Don't hesitate to search again using different keywords! --- ## Challenge 14 ![:cube]() Find the appropriate functions to perform the following operations: - Square root - Calculate the mean of numbers - Combine two data frames by columns - List availables objects in your workspace --- ## Challenge 14: Solutions ![:cube]() - `sqrt` - `mean` - `cbind` - `ls` --- class: inverse, center, middle # Additional resources --- ## Cheat 4ever Lot of cheatsheets are available: https://www.rstudio.com/resources/cheatsheets/ Open it directly from **Rstudio** --- ## Cheat 4ever  --- ## Some useful R books <img style="float: right; width: 170px;" src="images/Book6.jpg"> <img style="float: right; width: 151px;" src="images/Book5.jpg"> <img style="float: right; width: 180px;" src="images/Book4.jpg"> <img style="float: right; width: 150.5px;" src="images/Book3.jpg"> <img style="float: right; width: 150px;" src="images/Book2.jpg"> <img style="float: right; width: 150px;" src="images/Book1.jpg"> --- ## Some useful R websites - http://stats.stackexchange.com - https://www.zoology.ubc.ca/~schulter/R/ - http://statmethods.net/ - http://rseek.org/ - http://cookbook-r.com/ - http://cran.r-project.org/doc/contrib/Baggott-refcard-v2.pdf --- class: inverse, center, bottom # Thank you for attending!