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Exercises/DataTypes.md

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+---
+title: "Data types in R"
+layout: default
+---
+
+# Data Types
+<div id="table-of-contents">
+<h2>Table of Contents</h2>
+<div id="text-table-of-contents">
+<ul>
+<li><a href="#orgheadline2">1. Introduction</a>
+<ul>
+<li><a href="#orgheadline1">1.1. Data types</a></li>
+</ul>
+</li>
+<li><a href="#orgheadline4">2. Exercise: Basic operations and data types in R</a>
+<ul>
+<li><a href="#orgheadline3">2.1. Create and retrieve information about variables in R</a></li>
+</ul>
+</li>
+</ul>
+</div>
+</div>
+
+
+# Introduction<a id="orgheadline2"></a>
+
+There are different data modes used in R. The mode of a variable will
+for example determine what kind of operators that can be done on it. At the end of
+this exercise you should know:
+
+-   What are the data types commonly used in R and how to create them
+-   Use some basic operators in R
+-   Understand how R coerce data if needed
+-   Basic text manipulations
+
+## Data types<a id="orgheadline1"></a>
+
+From the lecture you might remember that all elements in any data
+stuctures found in R will be of a certain type (or have a certain
+mode). The four most commonly used data types in R are: logical,
+integer, double (often called numeric), and character. The names hints
+at what they are.
+
+-   Logical = TRUE or FALSE (or NA)
+-   Integer = Numbers that can be represented without fractional component
+-   Numeric = Any number that is not a complex number.
+-   Character = Text
+
+In many cases the mode of on entry is determined by the content so if
+you save the value 5.1 as a variable in R, the variable will
+automatically be recognised as numeric. If you instead have a text
+string like "hello world" it will have the mode character. Below you
+will also see examples of how you can specify the mode and not rely on
+R inferring the right mode based on content.
+
+# Exercise: Basic operations and data types in R<a id="orgheadline4"></a>
+
+In all exercises on this course it is important that you prior to
+running the commands in R, try to figure out what you expect the
+result to be. You should then verify that this will indeed be the
+qresult by running the command in an R session. In case there is a
+discrepency between your expectations and the actual output make sure
+you understand why before you move forward. If you can not figure out
+how to, or which command to run you can click the key to reveal
+example code including expected output. If you after peaking at the
+code and trying out things on your own have a hard time understanding
+what is going on, ask the TAs or or your someone sitting next to you
+who might have wrapped their head around the issue.
+
+Also note that in many cases there multiple solutions that solve the
+problem equally well.
+
+We do recommend to write all code in a R markdown document in R-studio
+as that will at the end of the course be your own R tutorial with
+comments and code solutions. 
+
+## Create and retrieve information about variables in R<a id="orgheadline3"></a>
+
+Open R-studio and make sure to set your working directory. Double
+check that you do not have stored objects in your current session with
+the following command. This will list all objects that you have in
+your current R session.
+```
+ls()
+```
+In case you have objects that you want to remove from the current
+session you can do so with the rm function. NB! This command will
+remove all objects available in your current session.
+```
+rm(list = ls())
+```
+This command uses commands that we have not talked about yet. If you
+do not understand how it works now, you will do so after tomorrows
+lectures and exercises.
+
+1.  Create variables *var1* and *var2* and initialize them with two integers of choice.
+	<details>
+	<summary>:key: Click to see how</summary>
+	<pre>
+	var1 <- 11  
+	var2 <- 34  
+	</pre>
+	</details>
+<br>
+2.  Add the two variables and save them as a new variable named *var3*
+    and print the result.
+
+	<details> 
+	<summary>:key: Click to see how</summary> 
+	<pre>
+	var3 <- var1 + var2  
+	var3  
+
+	[1] 45  
+	</pre>
+	</details>
+	<br>
+3.  Check the class, mode, and type for var1, var2, var3 and &pi; (is
+	found under the variable name pi in R)
+	<details>
+	<summary>:key: Click to see how for var1</summary>
+	<pre>
+	mode(var1)  
+	class(var1)  
+	typeof(var1)  
+
+	[1] "numeric"  
+	[1] "numeric"  
+	[1] "double"  
+	</pre>
+	</details>
+
+	<details>
+	<summary>:key: Click to see how for &pi;</summary>
+	<pre>
+	mode(pi)  
+	class(pi)  
+	typeof(pi)  
+
+	[1] "numeric"  
+	[1] "numeric"  
+	[1] "double"  
+	</pre>
+	</details>
+<br>
+4.  Create two character variables containing a text of choice. 
+	-   check mode, class, and type of the first one
+		<details>
+		<summary>:key: Click to see how create character variables</summary>
+		<pre>
+		text1 <- "test1"  
+		text2 <- "test2"  
+		</pre>
+		</details>
+
+	-   add var1 to it and report the result
+		<details>
+		<summary>:key: Click to see how to add variables</summary>
+		<pre>
+		text1 + var1  
+
+		Error in text1 + var1 : non-numeric argument to binary operator  
+		</pre>
+		</details>
+<br>
+5.  Cast var3 to integer, cast an integer variable to double, cast a
+	string to a double.
+	<details>
+	<summary>:key: Click to see how</summary>
+	<pre>
+	as.integer(var3)  
+	i <- 175  
+	as.double(i)  
+	as.double(text1)  
+
+	[1] 45  
+	[1] 175  
+	[1] NA  
+	Warning message:  
+	NAs introduced by coercion  
+	</pre>
+	</details>
+<br>
+6.  Report floor and ceiling of &pi; and round &pi; to 3 decimal places.
+	<details>
+	<summary>:key: Click to see how</summary>
+	<pre>
+	floor(pi)  
+	ceiling(pi)  
+	round(pi, digits = 3)  
+
+	[1] 3  
+	[1] 4  
+	[1] 3.142  
+	</pre>
+	</details>
+<br>
+7.  Is floor of &pi; an integer?
+	<details>
+	<summary>:key: Click to see how</summary>
+	<pre>	
+	is.integer(floor(pi))  
+
+	[1] FALSE  
+	</pre>
+	</details>
+<br>
+8.  Treat '3.56437' string as number.
+	<details>
+	<summary>:key: Click to see how</summary>
+	<pre>	
+	as.numeric('3.56437')  
+	</pre>
+	</details>
+<br>
+9.  Divide &infin; by - &infin;
+	<details>
+	<summary>:key: Click to see how</summary>
+	<pre>	
+	-Inf/Inf  
+
+	[1] NaN  
+	</pre>
+	</details>
+<br>
+10. Create two freely chosen complex numbers. 
+	-   Check that they are complex indeed.
+	-   Add, multiply and divide one by another.
+	-   Add an integer to their sum.
+	<details>
+	<summary>:key: Click to see how</summary>
+	<pre>
+	c1 <- 23 + 4i  
+	c2 <- -15 - 7i  
+	is.complex(c1)  
+	is.complex(c2)  
+	c1 + c2  
+	c1 / c2  
+	c1 + c2 + 7  
+	[1] TRUE  
+	[1] TRUE  
+	[1] 8-3i  
+	[1] -1.361314+0.368613i  
+	[1] 15-3i  
+	</pre>
+	</details>
+<br>
+11. Print a truth table for OR (for three distinct logical
+    values). Read about truth tables here
+    https://en.wikipedia.org/wiki/Truth_table
+	<details>
+	<summary>:key: Click to see how</summary>
+	<pre>	
+	x <- c(NA, FALSE, TRUE)  
+	names(x) <- as.character(x)  
+	outer(x, x, "|")  
+
+	NA FALSE TRUE  
+	NA      NA    NA TRUE  
+	FALSE   NA FALSE TRUE  
+	TRUE  TRUE  TRUE TRUE  
+	</pre>
+	</details>
+<br>
+12. Multiply a logical TRUE by a logical FALSE.
+	Rise the logical true to the 7-th power.
+	<details>
+	<summary>:key: Click to see how</summary>
+	<pre>
+	TRUE * FALSE  
+	T^7  
+	[1] 0  
+	[1] 1  
+	</pre>
+	</details>
+<br>
+13. Create two character variables containing two verses of your favorite song.  
+	-  concatenate the two variables,  
+	-  paste the variables with '\*' as separator.  
+	-  find if 'and' occurs in the second line,  
+	-  substitute a word for another,  
+	-  extract substring starting at the 5th character and 5 characters long.  
+	<details>
+	<summary>:key: Click to see how</summary>
+	<pre>	
+	line1 <- "Hello darkness my old friend"  
+	line2 <- "I've come to talk to you again"  
+	paste(line1, line2, sep = "")  
+	paste(line1, line2, sep = "*")  
+	grep('and', line2)  
+	sub('Hello', 'Goodbye', line1)  
+	substr(line1, 5, 5 + 5)  
+
+	[1] "Hello darkness my old friendI've come to talk to you again"  
+	[1] "Hello darkness my old friend*I've come to talk to you again"  
+	integer(0)  
+	[1] "Goodbye darkness my old friend"  
+	[1] "o dark"  
+	</pre>
+	</details>
+<br>
+
+## R Environment
+- get help for the *t.test*, *table*, *locator* and *identify* functions,
+- check for all occurences of *fisher.test* in the docs,
+- which package contains the *plot.ecdf* function. What does it do?
+- find package 'reshaape'-related questions on StackOverflow,
+- *google* how to load an XML file into R,
+- install the 'cgmisc' package from GitHub,
+- look up the 'cgmisc' vignette,
+- see all the demos available for you and run one you like,
+- run examples for the *fisher.test*,
+- check out CRANs view for genetics,
+- install a CRAN package of choice,
+- install the R-Forge pckage 'bigRR'