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Computational Statistics in Python
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Computational Statistics in Python

From: Computational Statistics in Python

Contents:

Introduction to Python

This lecture is based loosely on the online tutorial :http://www.afterhoursprogramming.com/tutorial/Python/Introduction/

We will be using Python a fair amount in this class. Python is ahigh-level scripting language that offers an interactive programmingenvironment. We assume programming experience, so this lecture willfocus on the unique properties of Python.

Programming languages generally have the following common ingredients:variables, operators, iterators, conditional statements, functions(built-in and user defined) and higher-order data structures. We willlook at these in Python and highlight qualities unique to this language.

Variables

Variables in Python are defined and typed for you when you set a valueto them.

my_variable = print ( my_variable ) type ( my_variable )

int

This makes variable definition easy for the programmer. As usual,though, great power comes with great responsibility. For example:

my_varible = my_variable + print ( my_variable )

If you leave out word, spell-check will not put the word in you Taylor Mali, The the impotence of proofreading

If you accidentally mistype a variable name, Python will not catch itfor you. This can lead to bugs that can be hard to track - so beware.

Types and Typecasting

The usual typecasting is available in Python, so it is easy to convertstrings to ints or floats, floats to ints, etc. The syntax is slightlydifferent than C:

a = "1" b = print ( a + b )

---------------------------------------------------------------------------TypeError Traceback (most recent call last) in () 1 a = "1" 2 b = 5----> 3 print(a+b)TypeError: cannot concatenate 'str' and 'int' objects

a = "1" b = print ( int ( a ) + b )

Note that the typing is dynamic. I.e. a variable that was initally sayan integer can become another type (float, string, etc.) viareassignment.

a = "1" type ( a ) print ( type ( a )) a = 1.0 print ( type ( a ))

Python has some other special data types such as lists, tuples anddictionaries that we will address later.

Operators

Python offers the usual operators such as +,-,/,*,=,>,<,==,!=,&,|,(sum, difference, divide, product, assignment, greater than, lessthan, equal - comparison,not equal, and, or, respectively).

Additionally, there are %,// and ** (modulo, floor division and tothe power). Note a few specifics:

print ( / ) print ( 3.0 / 4.0 ) print ( % ) print ( // ) print ( ** )

Note the behavior of / when applied to integers! This is similar to thebehavior of other strongly typed languages such as C/C++. The result ofthe integer division is the same as the floor division //. If you wantthe floating point result, the arguments to / must be floats as well (orappropriately typecast).

a = b = print ( a / b ) print ( float ( a ) / float ( b ))

Iterators

Python has the usual iterators, while, for, and some other constructionsthat will be addressed later. Here are examples of each:

for i in range ( , ): print ( i )

The most important thing to note above is that the range function givesus values up to, but not including, the upper limit.

i = while i < : print ( i ) i +=

This is unremarkable, so we proceeed without further comment.

Conditional Statements

a = if a >= : print ( "if" ) elif a >= : print ( "elif" ) else : print ( "else" )

Again, nothing remarkable here, just need to learn the syntax. Here, weshould also mention spacing. Python is picky about indentation - youmust start a newline after each conditional statemen (it is the same forthe iterators above) and indent the same number of spaces for everystatement within the scope of that condition.

a = 23if a >= 22: print("if") print("greater than or equal 22")elif a >= 21: print("elif")else: print("else")

a = if a >= : print ( "if" ) print ( "greater than or equal 22" ) elif a >= : print ( "elif" ) else : print ( "else" )

Four spaces are customary, but you can use whatever you like.Consistency is necessary.

Python has another type of conditional expression that is very useful.Suppose your program is processing user input or data from a file. Youdont always know for sure what you are getting in that case, and thiscan lead to problems. The try/except conditional can solve them!

a = "1" try : b = a + except : print ( a , " is not a number" )

Here, we have tried to add a number and a string. That generates anexception - but we have trapped the exception and informed the user ofthe problem. This is much preferable to the programming crashing withsome cryptic error like:

a = "1" b = a +

Functions

def Division ( a , b ): print ( a / b ) Division ( , ) Division ( 3.0 , 4.0 ) Division ( , 4.0 ) Division ( 3.0 , )

Notice that the function does not specify the types of the arguments,like you would see in statically typed languages. This is both usefuland dangerous. For example:

def Division ( a , b ): print ( a / b ) Division ( , "2" )

In a statically typed language, the programmer would have specified thetype of a and b (float, int, etc.) and the compiler would havecomplained about the function being passed a variable of the wrong type.This does not happen here, but we can use the try/except construction.

def Division ( a , b ): try : print ( a / b ) except : if b == : print ( "cannot divide by zero" ) else : print ( float ( a ) / float ( b )) Division ( , "2" ) Division ( , )

Strings and String Handling

One of the most important features of Python is its powerful and easyhandling of strings. Defining strings is simple enough in mostlanguages. But in Python, it is easy to search and replace, convertcases, concatenate, or access elements. Well discuss a few of thesehere. For a complete list, see:http://www.tutorialspoint.com/python/python_strings.htm

a = "A string of characters, with newline \n CAPITALS, etc." print ( a ) b = 5.0 newstring = a + " \n We can format strings for printing %.2f " print ( newstring % b )

Now lets try some other string operations:

a = "ABC DEFG" print ( a [ : ]) print ( a [ : ])

There are several things to learn from the above. First, Python hasassociated an index to the string. Second the indexing starts at 0, andlastly, the upper limit again means up to but not including (a[0:5]prints elements 0,1,2,3,4).

a = "ABC defg" print ( a . lower ()) print ( a . upper ()) print ( a . find ( 'd' )) print ( a . replace ( 'de' , 'a' )) print ( a ) b = a . replace ( 'def' , 'aaa' ) print ( b ) b = b . replace ( 'a' , 'c' ) print ( b ) b . count ( 'c' )

This is fun! What else can you do with strings in Python? Pretty muchanything you can think of!

Lists, Tuples, Dictionaries

Lists

Lists are exactly as the name implies. They are lists of objects. Theobjects can be any data type (including lists), and it is allowed to mixdata types. In this way they are much more flexible than arrays. It ispossible to append, delete, insert and count elements and to sort,reverse, etc. the list.

a_list = [ , , , "this is a string" , 5.3 ] b_list = [ "A" , "B" , "F" , "G" , "d" , "x" , "c" , a_list , ] print ( b_list )

print ( b_list [ : ])

a = [ , , , , , , ] a . insert ( , ) print ( a ) a . append ( ) print ( a ) a . reverse () print ( a ) a . sort () print ( a ) a . pop () print ( a ) a . remove ( ) print ( a ) a . remove ( a [ ]) print ( a )

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