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-* Data Types
-*** Outline
-***** Introduction
-******* What are we going to do?
-******* How are we going to do?
-******* Arsenal Required
-********* None
-*** Script
- 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