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diff --git a/numbers.org b/numbers.org deleted file mode 100644 index e596267..0000000 --- a/numbers.org +++ /dev/null @@ -1,173 +0,0 @@ -* 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 |