1 * Data Types

     2 *** Outline

     3 ***** Introduction

     4 ******* What are we going to do?

     5 ******* How are we going to do?

     6 ******* Arsenal Required

     7 ********* None

     8 *** Script

     9     Welcome friends. 

    10     

    11     This session is about numbers and mathematical operations

    12 

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

    14     type conversion.

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

    16     datatypes     

    17     For conditional statements, we have 'Bool' datatype

    18        

    19     type ipython on terminal to start the interpreter.

    20     Lets start with  'numbers'

    21     Now we will create a variable, say

    22     x = 13 lets confirm the value of x by

    23     print x

    24 

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

    26     type(x)

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

    28     

    29     lets create one more variable

    30     y = 999999999999

    31     print y

    32 

    33     Python can store any integer however big it is.    

    34     

    35     Floating point numbers come under 'float' datatype

    36     p = 3.141592

    37     type(p)

    38 

    39     Python by default provides support for complex numbers also.

    40     c = 3+4j 

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

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

    43     part and not i.

    44     type(c)

    45     Python also provides basic functions for their manipulations like

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

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

    48     

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

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

    51     cares of returning 'right' answer 

    52      

    53     print x + y gives sum of x and y

    54     

    55     Same as additions multiplication also works just right:

    56     123 * 4567

    57     gives you the product of both numbers

    58     

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

    60     with another integer result is also integer and decimal 

    61     value is truncated. So

    62     17 / 2 returns 8 and not 8.5

    63 

    64     but int and float value operations like

    65     17 / 2.0 will return the correct 8.5, similarly

    66     17.0 / 2 will also give correct answer.

    67     

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

    69     2 ** 3 and we get 2 raised to power 3 which is 8

    70 

    71     now lets try power operation involving a big number

    72     big = 1234567891234567890 ** 3

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

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

    75 

    76     % operator is for modulo operations

    77     1786 % 12 gives 10

    78     45 % 2 returns 1

    79 

    80     Other operators which comes handy are:

    81     += 

    82     lets create one variable a with

    83     a =  7546

    84     now

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

    86     similarly 

    87     a -= 1 will decrement.

    88     we can also use 

    89     a *= a

    90     a 

    91     a is multiplied by itself.

    92     

    93     a /= 5    

    94     a is divided by 5

    95     

    96     Next we will look at Boolean datatype:

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

    98     t = True

    99     print t

   100 

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

   102     true with 't' would be a variable. 

   103     

   104     f = not True

   105     

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

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

   108     f and t is flase and true which gives false

   109     

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

   111     'parenthesis ()'

   112     a = False

   113     b = True

   114     c = True

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

   116     (a and b) or c

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

   118     we get True

   119     but if we do 

   120     a and (b or c)

   121     there is a change in precedence and we get False

   122 

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

   124     examples:

   125     We start with initializing three variables by typing

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

   127     To check equivalency of two variables use '=='

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

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

   130     

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

   132     n < z < p gives True.

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

   134 

   135     For inequality testing we use '!'

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

   137 

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

   139 

   140     Lets look at converting one data type to another

   141     lets create a float by typing z = 8.5

   142     and convert it to int using

   143     i = int(z)

   144     lets see what is in i by typing print i

   145     and we get 8

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

   147     and we get int

   148 

   149     similarly float(5) gives 5.0 which is a float

   150     

   151     type float_a = 2.0 and int_a = 2

   152     17 / float_a gives 8.5

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

   154 

   155 

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

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

   158 

   159     To get correct answer from such division try    

   160     17 / float(a)

   161 

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

   163     used. 

   164     round(7.5) returns 8.

   165     

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

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

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

   169     convert one data type to other. 

   170 

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

   172 

   173 *** Notes