Python has four built-in numeric data types they are
integer, long integer, floating point numbers and imaginary numbers.
Let under them in details:
Integers
Integers are whole numbers in the range of -2147483648 to
3147483647 (that is, they are signed, 32-bit numbers).
To check Maximum positive value use sys module has maxint
value for example.
>>> import sys
>>> sys.maxint
2147483647
In addition to writing integers in the
default decimal (base 10) notation, we can also write integer literals in
hexadecimal (base 16) and octal (base 8) notation by preceding the number with
a 0x or 0 respectively:
>>> 300 #
300 in decimal
300
>>> 0x12c #
300 in hex
300
>>> 0454 #
300 in octal
300
We need to understand that for decimal
numbers, valid digitis are 0 through 9.
For hexadecimal, it’s 0 through 9 and A through F, and for octal its 0
through 7. If we are not familiar with
hexadecimal and octal numbering systems then we will go through in our next
option Long integers.
Long integers
Long integers are similar to integers,
except that the maximum and minimum values of long integers are restricted only
by how much memory we have. To
differentiate between the two types of integers we append an “L” to the end of
long integers:
>>> 200L #
A long integer literal with a value of 200
200L
>>> 11223344
* 55667788 # Too big for normal integers...
Traceback (innermost
last):
File “<interactive
input>”, line 1, in ?
OverflowError:
integer multiplication
>>>
11223344L * 55667788L # ...but works with long integers
624778734443072L
Note: The “L” on long integers can be
uppercase or lowercase, but we make sure to use uppercase version always.
Floating point numbers
Floating point numbers let us express
fractional numeric values such as 3.14159.
We can also include an optional exponent. If we include neither an exponent nor a
decimal point, Python interprets the number as an integer, so to express the
floating point number two hundred we need to write as 200.0 and not just
200. Let see sample below:
>>> 0.3
0.29999999999999999
The
valid values for floating point numbers and the accuracy with which Python uses
them is implementation-dependent, although it is at least 64-bit, double precision
math and is often IEEE 754 compliant.
Imaginary numbers
Python has language-level support for imaginary numbers,
making it trivial to use them in our programs.
We form an imaginary number by appending a “j” to decimal number.
3j
2.5e-3j
When
we add a real and an imaginary number together, Python recognizes the result as
a complex number and handles it accordingly:
>>> 2 + 5j
(2+5j)
>>> 2 * (2 +
5j)
(4+10j)
0 Comments