* Data Types

*** Outline

***** Introduction

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    Welcome friends. 

    This session is about numbers and mathematical operations

    In this tutorial we shall be covering data types, operators and

    type conversion.

    To represent 'Numbers' in python, we have int, float, complex

    datatypes     

    For conditional statements, we have 'Bool' datatype

    type ipython on terminal to start the interpreter.

    Lets start with  'numbers'

    Now we will create a variable, say

    x = 13 lets confirm the value of x by

    print x

    To check the data type of any variable Python provides 'type' function

    type(x)

    which tells us that the x is of type 'int'

    lets create one more variable

    y = 999999999999

    print y

    Python can store any integer however big it is.    

    Floating point numbers come under 'float' datatype

    p = 3.141592

    type(p)

    Python by default provides support for complex numbers also.

    c = 3+4j 

    creates a complex number c with real part 3 and imaginary part 4.

    Please note that here 'j' is used to specify the imaginary 

    part and not i.

    type(c)

    Python also provides basic functions for their manipulations like

    abs(c) will return the absolute value of c.

    c.imag returns imaginary part and c.real gives the real part. 

    All the basic operators work with Python data types, without any

    surprises. When we try to add two numbers like x and y Python takes 

    cares of returning 'right' answer 

    print x + y gives sum of x and y

    Same as additions multiplication also works just right:

    123 * 4567

    gives you the product of both numbers

    Integer division in Python truncates, which means, when we divide an integer 

    with another integer result is also integer and decimal 

    value is truncated. So

    17 / 2 returns 8 and not 8.5

    but int and float value operations like

    17 / 2.0 will return the correct 8.5, similarly

    17.0 / 2 will also give correct answer.

    in python x ** y returns x raised to power y. For example lets try:

    2 ** 3 and we get 2 raised to power 3 which is 8

    now lets try power operation involving a big number

    big = 1234567891234567890 ** 3

    As we know, any number irrespective of its size can be represented in python.

    hence big is a really big number and print big prints the value of big.

    % operator is for modulo operations

    1786 % 12 gives 10

    45 % 2 returns 1

    Other operators which comes handy are:

    += 

    lets create one variable a with

    a =  7546

    now

    a += 1 will increment the value of 'a' by 1

    similarly 

    a -= 1 will decrement.

    we can also use 

    a *= a

    a 

    a is multiplied by itself.

    a /= 5    

    a is divided by 5

    Next we will look at Boolean datatype:

    Its a primitive datatype having one of two values: True or False.

    t = True

    print t

    Python is case sensitive language, so True with 'T' is boolean type but

    true with 't' would be a variable. 

    f = not True

    we can do binary operations like 'or', 'and', 'not' with these variables

    f or t is false or true and hence we get true

    f and t is flase and true which gives false

    in case of multiple binary operations to make sure of precedence use

    'parenthesis ()'

    a = False

    b = True

    c = True

    if we need the result of a and b orred with c, we do

    (a and b) or c

    first a and b is evaluated and then the result is orred with c

    we get True

    but if we do 

    a and (b or c)

    there is a change in precedence and we get False

    Python also has support for relational and logical operators. Lets try some

    examples:

    We start with initializing three variables by typing

    p, z, n = 1, 0, -1 

    To check equivalency of two variables use '=='

    p == z checks if 1 is equal to 0 which is False

    p >= n checks if 1 is greater than or equal to -1 which is  True

    We can also check for multiple logical operations in one statement itself.

    n < z < p gives True.

    This statement checks if 'z' is smaller than 'p' and greater than 'n'

    For inequality testing we use '!'

    p + n != z will add 'p' and 'n' and check the equivalence with z

    We have already covered conversion between datatypes  in some of the previous sessions, briefly.

    Lets look at converting one data type to another

    lets create a float by typing z = 8.5

    and convert it to int using

    i = int(z)

    lets see what is in i by typing print i

    and we get 8

    we can even check the datatype of i by typing type(i)

    and we get int

    similarly float(5) gives 5.0 which is a float

    type float_a = 2.0 and int_a = 2

    17 / float_a gives 8.5

    and int( 17 / float_a ) gives you 8 since int function truncates the decimal value of the result

    float(17 / int_a ) we get 8.0 and not 8.5 since 17/2 is already truncated to 8

    and converting that to float wont restore the lost decimal digits.

    To get correct answer from such division try    

    17 / float(a)

    To round off a float to a given precision 'round' function can be

    used. 

    round(7.5) returns 8.

    This brings us to the end of tutorial on introduction to Data types 

    related to numbers in Python. In this tutorial we have learnt what are 

    supported data types for numbers, operations and operators and how to 

    convert one data type to other. 

    Hope you have enjoyed the tutorial and found it useful.Thank you!

*** Notes