The number data types are used to store the numeric values.
Python supports integers, floating-point numbers and complex numbers. They are defined as
complex classes in Python.
int- holds signed integers of non-limited length.
float- holds floating decimal points and it's accurate up to 15 decimal places.
complex- holds complex numbers.
Python Numeric Data Type
Integers and floating points are separated by the presence or absence of a decimal point. For instance,
- 5 is an integer
- 5.42 is a floating-point number.
Complex numbers are written in the form,
x + yj, where
x is the real part and
y is the imaginary part.
We can use the
type() function to know which class a variable or a value belongs to.
Let's see an example,
num1 = 5 print(num1, 'is of type', type(num1)) num2 = 5.42 print(num2, 'is of type', type(num2)) num3 = 8+2j print(num3, 'is of type', type(num3))
5 is of type <class 'int'> 5.42 is of type <class 'float'> (8+2j) is of type <class 'complex'>
In the above example, we have created three variables named num1, num2 and num3 with values 5, 5.42, and
We have also used the
type() function to know which class a certain variable belongs to. Since,
- 5 is an integer value,
intas the class of num1 i.e
- 5.42 is a floating value,
type()returns float as the class of num2 i.e
1 + 2jis a complex number,
type()returns complex as the class of num3 i.e
The numbers we deal with every day are of the decimal (base 10) number system.
But computer programmers need to work with binary (base 2), hexadecimal (base 16) and octal (base 8) number systems.
In Python, we can represent these numbers by appropriately placing a prefix before that number. The following table lists these prefixes.
Here are some examples
print(0b1101011) # prints 107 print(0xFB + 0b10) # prints 253 print(0o15) # prints 13
Type Conversion in Python
In programming, type conversion is the process of converting one type of number into another.
Operations like addition, subtraction convert integers to float implicitly (automatically), if one of the operands is float. For example,
print(1 + 2.0) # prints 3.0
Here, we can see above that 1 (integer) is converted into 1.0 (float) for addition and the result is also a floating point number.
Explicit Type Conversion
We can also use built-in functions like
complex() to convert between types explicitly. These functions can even convert from strings.
num1 = int(2.3) print(num1) # prints 2 num2 = int(-2.8) print(num2) # prints -2 num3 = float(5) print(num3) # prints 5.0 num4 = complex('3+5j') print(num4) # prints (3 + 5j)
Here, when converting from float to integer, the number gets truncated (decimal parts are removed).
Similarly when converting from integer to float,
.0 is postfixed to the number.
Python Random Module
Python offers the
random module to generate random numbers or to pick a random item from an iterator.
First we need to import the
random module. For example,
import random print(random.randrange(10, 20)) list1 = ['a', 'b', 'c', 'd', 'e'] # get random item from list1 print(random.choice(list1)) # Shuffle list1 random.shuffle(list1) # Print the shuffled list1 print(list1) # Print random element print(random.random())
15 a ['d', 'b', 'c', 'e', 'a'] 0.6716121217631744
To learn more about the
random module, visit Python Random Module.
Python offers the
math module to carry out different mathematics like trigonometry, logarithms, probability and statistics, etc. For example,
import math print(math.pi) print(math.cos(math.pi)) print(math.exp(10)) print(math.log10(1000)) print(math.sinh(1)) print(math.factorial(6))
3.141592653589793 -1.0 22026.465794806718 3.0 1.1752011936438014 720
Here is the full list of functions and attributes available in the Python math module.