added matlab figures

Author: gordondavies

img/matlab-figure-4.png

@@ -261,6 +261,9 @@ legend([h1 h2],{'x^2','x^3'},'Location','northwest');
 set(gca,'FontSize',16);
 ```
 
+
+![Matlab figure 4](https://github.com/csmsoftware/Programming-for-data-analysis-tutorial-Matlab-R-Python/raw/master/img/matlab-figure-4.png "Matlab figure 4")
+
 Large amounts of numeric data are not suited for storage in a cell array. Instead, they should be stored in a regular array.  When dealing with a range of datatypes, such as patient metadata which contains text (ID, status, disease, etc) and numeric values (weight, height, age, etc) then cell arrays are ideally suited.
 
 ### Halting execution
@@ -280,6 +283,8 @@ The documentation for a particular function can be displayed in the Matlab comma
 help str2num
 ```
 
+![Matlab figure 5](https://github.com/csmsoftware/Programming-for-data-analysis-tutorial-Matlab-R-Python/raw/master/img/matlab-help.png "Matlab help")
+
 Alternatively, there is an interactive documentation browser which can be accessed by typing either:
 
 ```

img/matlab-figure-4png

@@ -6,8 +6,7 @@ In the introduction below, the syntax is python.
 ## Commands
 Python, Matlab, and R are interpreted languages. That means the code is interpreted at run time (there's no pre-compiling).
 Commands are given to the interpreter, either as a 'script', or in an interactive session.
-The interpreter 'interprets' the code, translate it to binary CPU instructions,
-executes these instructions, and returns the result (if any).
+The interpreter 'interprets' the code, translate it to binary CPU instructions, executes these instructions, and returns the result (if any).
 
 ## Variables & Datatypes
 During execution, the instructions often need to access and manipulate data stored in memory.
@@ -215,7 +214,12 @@ This is a way of grouping functions and variables of similar entities together i
 The definition of an object is a Class, and the instance of that Class is an object.
 An objects functions are known as 'methods' and the variables are known as 'properties'.
 
-## Accessing data
+## Control characters
+Different languages use different 'control characters' for defining seperate regions of executable code.
+In Matlab and R, some control characters used are the
+`{}()[]`. In Python, indentation is used to specify control characters.
+
+## Accessing data from disk
  Persistent data is data which when your program finishes (or crashes), still exists on disk.
  Persistent data can be read and written from various sources, including simple flat text files,
  including CSVs, XML or json, or more complex sources such as relational databases or online APIs.
@@ -231,7 +235,7 @@ import csv
 with open('eggs.csv') as csvfile:
   spamreader = csv.reader(csvfile)
   for row in spamreader:
-  print(', '.join(row))
+    print(', '.join(row))
 
 # > Spam, Spam, Spam, Spam, Spam, Baked Beans
 # Spam, Lovely Spam, Wonderful Spam

img/matlab-help.png

@@ -9,7 +9,37 @@
 Compared to Matlab and R, Python is fairly complicated to install and use, as it is general-purpose programming language.
 The situation is made more complicated by different versions (2.x vs 3.x), and different package managers.
 
-### Virtualenv
+Generally use python3.x for new projects, and only use python2.7 if a project you are using does not support Python3.
+
+### Windows installation
+- See Conda below
+
+### Mac installation
+- Install [Homebrew](https://brew.sh/)
+Install python3 via homebrew:
+```
+# bash mac
+
+brew install python
+```
+
+### Linux installation
+Use the system package management system, ie aptitude or yum.
+
+```
+# bash ubuntu
+
+sudo apt-get install python3-dev python3-setuptools
+```
+
+```
+# bash centos
+
+sudo yum -y install python36u python36u-pip python36u-devel
+```
+
+
+### Virtualenv (Mac/Linux)
 
 Virtualenv is the recommended approach to handling multiple installations of python on your system. Each python script or tool you use may require different versions of python, or different packages, or different versions of packages. Virtualenv is a way of seperating out these differences to resolve conflicts. Typically you would use a different virtual environment for each project you use. The following bash shell commands create a new virtual environment and then activate it for dynamic usage - all python commands entered after activate has run will use the python kernel from the virtual environment.