Python-Old-Version/C3/Data-Types-Numbers/English
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.
$ ipython
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)
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!
