Key Aspects of R Exercise - Revision history

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Rf: Rf moved page Key Aspects of R to Key Aspects of R Exercise

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Rf moved page Key Aspects of R to Key Aspects of R Exercise

@@ Line 87: / Line 87: @@
   ?ls
-As you can see the parentheses are not required. The documentation is also available online: http://cran.r-project.org/doc/manuals/r-release/fullrefman.pdf.
+As you can see the parentheses are not required. R's help is mostly the same as our friend the pager <code>less</code> and also the editor <code>vim</code>: i.e. <code>q</code> to quit, <code>G</code> to go to the bottom (useful, because that's where the examples are), <code>g</code> to go to the top, <code>ctrl+f</code> to go forwards, <code>ctrl+b</code> to go backwards, <code>/</code> to search for a term. Those keybinding should be getting familiar now, and hopefully you should also recognise that they are quite fast. The documentation is also available online: http://cran.r-project.org/doc/manuals/r-release/fullrefman.pdf.
 = Data types =

@@ Line 123: / Line 123: @@
 Data frames are the most common data type in R. A data frame is basically a table that contains vectors of equal length, usually though of as the rows or observations. The columns are usually thought of as the measurement, or the values of certain attributes of the obsveration. The top line called the header, contains the column names, which can be simple indices, or proper names. Each horizontal line afterward denotes a data row, which begins with the name of the row, followed by the actual data.
-= Creating a data frame =
+== Creating a data frame ==
 In the following example you will create a data frame from a comma-separated (<code>.csv</code>) file. The <code>genomes.csv</code> file (which is in the directory <code>~/i2rda_data/06_R_Usage_Refresher</code>) contains information about a number of animal genomes from the Animal Genome Size Database, i.e.  the scientific (Latin) name of the species, the taxonomic class it belongs to, the number of chromosomes and its size:

@@ Line 187: / Line 187: @@
 = Retrieving data =
-The column vectors can be retrieved in several ways ways, i.e. using double brackets [[]], the $ operator, or single brackets []:
+The column vectors can be retrieved in several ways ways, i.e. using double brackets, the <code>$</code> operator, or single brackets <code>[]</code>, liek the following (the double bracket method is omitted).
   genomes$chromosomes
@@ Line 207: / Line 199: @@
   genomes[,"chromosomes"]
-Note that when using single brackets, the column number (or name) is prepended with a comma character, which signals a wildcard match for the
+Note that when using single brackets, the column number (or name) has what you may decide is an empty row specification, followed by a comma, and then the column specification, meaning that we retrieve the value for the column indicated for every row.
 Column slices can be retrieved using single brackets []:

@@ Line 97: / Line 97: @@
 As analysis get complicated, many packages assemble their own data types made up of multiple vectors and multiple data frames often of different sizes. R often calls these objects, but they can also be called data structures, which is more descriptive, as they really are structures of data. Using that analogy we could call vectors apartments, data-frame buildings of apartments, and data structures apartment building complexes.
-== Vectors ==
+= Vectors =
 A vector is a sequence of data elements of the same basic type (e.g. numbers or character strings). The elements of a vector are called components.
@@ Line 116: / Line 116: @@
 Multiple indices need to be wrapped in a <code>c()</code>.
-> z[c(2,4)]
+ z[c(2,4)]
-[1] 12 30
+ [1] 12 30
 = Data frames =
@@ Line 123: / Line 123: @@
 Data frames are the most common data type in R. A data frame is basically a table that contains vectors of equal length, usually though of as the rows or observations. The columns are usually thought of as the measurement, or the values of certain attributes of the obsveration. The top line called the header, contains the column names, which can be simple indices, or proper names. Each horizontal line afterward denotes a data row, which begins with the name of the row, followed by the actual data.
-== Creating a data frame ==
+= Creating a data frame =
 In the following example you will create a data frame from a comma-separated (<code>.csv</code>) file. The <code>genomes.csv</code> file (which is in the directory <code>~/i2rda_data/06_R_Usage_Refresher</code>) contains information about a number of animal genomes from the Animal Genome Size Database, i.e.  the scientific (Latin) name of the species, the taxonomic class it belongs to, the number of chromosomes and its size:
@@ Line 172: / Line 172: @@
 You retrieve the dimensions of the data frame using dim():
-  > dim(genomes)
+  dim(genomes)
   [1] 20 4
@@ Line 189: / Line 189: @@
 The column vectors can be retrieved in several ways ways, i.e. using double brackets [[]], the $ operator, or single brackets []:
-  genomes[[3]]
+  genomes\[[3]\]
 or

@@ Line 1: / Line 1: @@
 = Aims =
-R is a powerful programming language and software environment for statistical computing and graphics. It is also open source, meaning htat it is free to use and has a wide community of developers that have produced many add-on packages and libraries that be easily accessed.
+R is a powerful programming language and software environment for statistical computing and graphics. It is also open source, meaning that it is free to use and has a wide community of developers that have produced many scientific add-on packages and libraries that be easily accessed.
 In this part you will learn to:
-use basic R commands
+* use basic R commands
-You will use the following tools, which have been pre-installed on our bioinformatics training server at the University of
+* find your way around.
-Edinburgh:
-R: http://www.r-project.org
+We shall practice with the following toy file:
-You will use the following files:
+* <code>genomes.csv</code>: information about a number of animal genomes
 genomes.csv: information about a number of animal genomes
-> Type text like this in the terminal at the > command prompt, then press the
+= Finding one's location =
-Go to the directory 08_Introduction_to_r:
+OK, now go back in and let's check what the working directory we are in by using the <code>getwd()</code> function:
-  $ cd ~/Data/08_Introduction_to_r
+  getwd()
-= The basics =
+See what files and directories there are there:
-To start, type R and hit [Enter]:
+ dir()
+The working directory can be changed using setwd(), which also, liek the linux command-line, obeys tab-completion. Type
-First, check what the working directory of R is using the getwd() function:
+ setwd("i2rda_data
- > getwd()
+which you finish off with a <code>")</code>
-The working directory can be changed using setwd().
+= Calculator =
 R can be used as a glorified calculator:
-  > 5*5 + 10/2
+*5 + 10/2
   [1] 30
@@ Line 41: / Line 55: @@
 Values can be assigned to a variable using the <- assignment operator:
-> a <- 5
+ a <- 5
-Alternatively, it is also is possible to write 5 -> a or a = 5, but a <- 5 is the conventional and preferred way. It can be good to remind yourself that you are actually in the R environment.
-To print out a variable, just type it:
+Be aware that more complicated variables may throw out all their contents on the screen, so this simple method of seeing a variable is not always the best.
- > a
+= R Functions =
 R functions are invoked by their name, followed by parentheses that contain zero or more arguments.
@@ Line 54: / Line 72: @@
 All existing variables can be listed using the ls() function:
-  > ls()
+  ls()
   [1] "a"
 Variables can be removed using the rm() function:
   > rm(a)
-R contains extensive documentation, which can be accessed using the ? operator or help() function:
+If you have lots of variables you want to get rid of (i.e. maybe you are starting over):
-  > ?ls
+  rm(list=ls())
-The documentation is also available online: http://cran.r-project.org/doc/manuals/r-release/fullrefman.pdf.
+R contains extensive documentation for all its functions, which can be accessed using the ? operator or help() function:
 = Data types =
@@ Line 463: / Line 481: @@
 This saves the file genomes.txt in the working directory (/home/training).
 Useful resources

@@ Line 165: / Line 165: @@
 == Data frames ==
-Data frames are the most common data type in R. A data frame is basically a table that contains vectors of equal length. The key is that these
+Data frames are the most common data type in R. A data frame is basically a table that contains vectors of equal length. The key is that these vectors are what you would normally think of as the columns, not the rows, of the table. The top line of the table, called the header, contains the column names. Each horizontal line afterward denotes a data row, which begins with the name of the row, followed by the actual data. Each data member of a row is called a cell. The data in the columns of a data frame can be of various types., i.e. one column might contain numbers while another might contain text. The columns and rows of a data frame are also referred to as variables and observations, respectively.
-=== Creating a data frame ===
+== Creating a data frame ==
 In the following example you will create a data frame from a comma-separated (.csv) file. The genomes.csv file (which is in the directory /hom
@@ Line 210: / Line 206: @@
   : num 3.09 0.4 3.05 3.76 3.61 2.91 3.7 1.25 2.8 3.06 ...
-where:
+<code>where</code>:
 * Factor: a vector whose elements can take on one of a specific set of values ("levels")
 * int: integer (whole number)
@@ Line 225: / Line 221: @@
 To print the whole data frame just type its name:
-> genomes
+ > genomes
 To print only the first or last rows use head() and tail(), respectively:
-> head(genomes)
+ > head(genomes)
-Retrieving data
+= Retrieving data =
 The column vectors can be retrieved in various ways, i.e. using double brackets [[]], the $ operator, or single brackets []:
@@ Line 594: / Line 464: @@
 This saves the file genomes.txt in the working directory (/home/training).
-To quit R, use quit():
+To quit R, use <code>quit()</code>, or, shorter, <code>q()</code>
-  > quit()
+  > q()
 Useful resources
@@ Line 606: / Line 476: @@
 * Stack Overflow (forum): http://stackoverflow.com
 * Biostars (forum): http://www.biostars.org

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