152 Python Data Types

 2.0 Python Data Types

Python has five standard data types –

Numeric types:     Sequences:      Sets:                   Mappings:    Boolean:

Int                           str                      set                     dict

Long                       byte                   frozen set

Float                       list

Complex                 tuple 

 

1) Numeric types:

Integers: 

Integers are any numbers without decimals   

#Int assignment exmaple

a=1

print(a)

o/p:

1

                                           

Long: 

no long in python 3

                    

Float

# float

a = 1.0

type(a)

                       

Complex:

Complex literals can be created by using the notation x + yj

x =real component 

y = imaginary component.

                                    

2) Sequences

2.1 Strings

strings are sequence.

Strings are immutable.

[] are used for Indexing. Indexing starts at 0.

String literals can be defined with any of single quotes ('), double quotes (") or triple quotes (''' or """)

2.2 List

4 built-in data types in Python are List, Tuple Set and Dictionary.

List is a sequence, it can hold different objects. (no fixed type constraint )

Lists are mutable.

Lists are constructed with Square brackets0 - "[]"

We can use " : " to index string.

list1= [1, 'str', 1.2]

indexing:

    

2.3 Tuple:    

Tuples are constructed with Parentheses - '()' 

Immutable

Example usage of tuples, in days of week, dates in calendar.

For Data integrity, tuples are used.

Tuples are faster compared to list.   

tup1 = (1,2,3)  # tuple creation

print (tup1[:2]) # indexing tuple

O/p:

(1, 2)tuple

byte (binary type)

3) Sets:

set

frozen set

Sets are unordered collection of unique elements.

Built in data type which stores collections of data.

Items in set are unordered, unchangeable, unique.

Set items can be of any data type.

s = set()   # set creation
s.add(1)   # adding elemt to set
print(s)

Output:

{1}

set1= {'apple', 1, 2.3}           # set creaiton
print(set1)

Output:

{2.3, 'apple', 1}

set creation from list:

list1 = ['1', '2', '1','2','1','2']
set2 = set(list1)
print(set2)

Output:

{'2', '1'}

Access set items:

We, can't access items in a set by referring index or key. But, we can loop over. 

set1= {'apple', 1, 2.3}     # set creaiton

set1[0]

O/p:

TypeError: 'set' object is not subscriptable

set1= {'apple', 1, 2.3}     # set creaiton

for i in set1:

    print(i)

O/p:

1

2.3

apple

Add new item to set:

set1= {1, 2.3, 'Bng'}     # set creaiton

set1.add('new-item')    #adding item to set

print(set1)

O/p:

{1, 2.3, 'new-item', 'Bng'}

Joining Sets:

set1 = {'a', 'b', 'c'}

set2 = {1, 2, 3}

unioned_set = set1.union(set2)

print (unioned_set)

O/p:

{1, 2, 'a', 3, 'c', 'b'}

4)Mappings:

Dictionary 

2.5 Dictionaries:

Dictionary is a mapping.

Mappings are a collection of objects that are stored by a "key".

Mapping store objects by their relative position.

Dictionary consists of a key with an associated value. Value can be any python object

dict1 = {1:'key1', 'key2': 'value2', 'key3': 'value3'}

dict1

O/p:

{1: 'key1', 'key2': 'value2', 'key3': 'value3'}

Dictionary comprehension:

dict_comprehension = {x:x**2 for x in range(5)}

dict_comprehension

O/p:

{0: 0, 1: 1, 2: 4, 3: 9, 4: 16}

5) Boolean:

Boolean can be defined by typing True/False without quotes

# Boolean Example

bool1 = True

bool2 = False

print (type(bool1))

O/p:

<class 'bool'>

Note: Mutability:

int, float, bool, str, tuple, unicode  are immutable.

list, set, dict are mutable.