This lesson will teach you about the different data you can use in Python, with a few examples to understand the topic better.
In Python, each value has a datatype, and everything is an object; hence variables and data types are both instances (and objects) of the same classes.
The following list includes a few of the key data types.
Python numbers include complex numbers, floating point numbers, and integers. In Python, they are referred to as int, float, and complicated classes. Also, you can use the type() method to determine the class to which a variable or value belongs. Similarly, an object’s class membership can be determined using the isinstance() function.
Example
mathMarks = 70 print (mathMarks, 'is of type', type(mathMarks)) mathMarks = 70.0 print (mathMarks, 'is of type', type(mathMarks)) mathMarks = 1 + 2j print (mathMarks, 'is it a complex number?', isinstance(1 + 2j,complex))
Output
70 is of type70.0 is of type (1+2j) is it a complex number? True
Let’s look at a few instances.
Example
mathMarks = 701352132145761132 engMarks = 0.701352132145761132 hisMarks = 1+2j > engMarks 0.7013521321457611 > mathMarks 701352132145761132 > hisMarks (1+2j)
A list is an orderly collection of things; a list does not necessarily need to include just items of the same type. It is a highly flexible datatype and one of the most popular in Python. Declaring a list is a relatively simple process, and commas delimit the spaces between items.
Example
Python: a = [1, 2.2]
In Python, you can utilize the slicing operator [] to extract one or more items from a list.
Example
mathMarks = [5,10,15,20,25,30,35,40]
# mathMarks[2] = 15
print("mathMarks[2] = ", mathMarks[2])
# mathMarks[0:3] = [5, 10, 15]
print("mathMarks[0:3] = ", mathMarks[0:3])
# mathMarks[5:] = [30, 35, 40]
print("mathMarks[5:] = ", mathMarks[5:])
Output
mathMarks[2] = 15
mathMarks[0:3] = [5, 10, 15]
mathMarks[5:] = [30, 35, 40]
You can change the value of a list's elements since lists are mutable.
mathMarks = [5,10,15]
mathMarks[2] = 150
print("mathMarks[2] = ", mathMarks[2])
Similar to a list, a tuple is an ordered series of elements. The fact that tuples are immutable is the only distinction. Once formed, you can’t change the tuples. Because they cannot alter dynamically, tuples are used to write-protect data and are typically faster than lists.
It is defined between parentheses (), with commas between each component.
total = (5,'Six', 1+3j)
In Python, you can utilize the slicing operator [] to remove objects but cannot alter their value.
Example
total = (5,'Six', 1+3j)
# total[1] = 'Six'
print("total[1] = ", total[1])
# total[0:3] = (5, 'Six', (1+3j))
print("total[0:3] = ", total[0:3])
# Generatotales error
# totaluples are immutable
total[0] = 10
Output
total[1] = Six total[0:3] = (5, 'Six', (1+3j)) Traceback (most recent call last): File "", line 9, in TypeError: 'tuple' object does not support item assignment
Now let’s move to another Data type in Python, string!
An array of Unicode characters is a string. To represent strings, You can use single or double quotations, and triple quotes” or “” can indicate multiline strings.
Example
stringVar = "String Example" print(stringVar) stringVar = '''A multiline string''' print(stringVar)
Output
String Example A multiline string
The slicing operator [] can be applied to strings like lists and tuples. But you can never change strings.
Example
stringVar = 'Hellu world!'
# stringVar[4] = 'u'
print("stringVar[4] = ", stringVar[4])
# stringVar[6:11] = 'world'
print("stringVar[6:11] = ", stringVar[6:11])
# Generate string Var error
# string are immutable in Python
stringVar[5] ='f'
Output
stringVar[4] = u stringVar[6:11] = world Traceback (most recent call last): File "", line 10, in TypeError: 'str' object does not support item assignment
Now, let’s move to the Set data type in Python.
A set is a grouping of distinct elements that are not arranged. A set’s components don’t follow any particular order, and values separated by commas are used to define sets.
Example
set = {50,42,53,81,4}
# printing set variable
print("set = ", set)
# data type of variable set
print(type(set))
Output
set = {4, 42, 81, 50, 53}
>
On two sets, we can perform set operations like union and intersection. Sets contain distinct values, and Duplicates are eliminated. See the example below:
Example
set = {50,42,53,81,4,50,42,53,81,4}
# printing set variable
print("set = ", set)
# data type of variable set
print(type(set))
Output
set = {4, 42, 81, 50, 53}
>
Sets are unordered collections, so indexing is useless. As a result, the slicing operator [] is useless.
Example
set = {50,42,53,81,4,50,42,53,81,4}
set[1]
Output
Traceback (most recent call last): File "", line 3, in TypeError: 'set' object is not subscriptable >
Dictionaries are designed with data retrieval in mind. A dictionary is a collection of key and value pairs that are not ordered. It is typically utilized when there is a ton of data. To retrieve the value back, we need to know the key.
Accessing Values in Python Dictionary
You can use the well-known square brackets and the key to access dictionary items. Here is a simple illustration:
Example
dict = {'Name': 'John', 'Age': 20}
print ("dict['Name'] ", dict['Name'])
print ("dict['Age'] ", dict['Age'])
Output
dict['Name'] John dict['Age'] 20
As shown in the simple example below, you can update a dictionary by adding a new item or key-value pair, changing an existing entry, or removing an existing one.
Example
dict = {'Name': 'John', 'Age': 20}
print ("dict['Name'] ", dict['Name'])
print ("dict['Age'] ", dict['Age'])
dict = {'Name': 'Humna', 'Age': 17}
print ("dict['Name'] ", dict['Name'])
print ("dict['Age'] ", dict['Age'])
Output
dict['Name'] John dict['Age'] 20 dict['Name'] Humna dict['Age'] 17
You can either erase individual dictionary entries or clear the dictionary’s complete contents. Additionally, you can erase an entire dictionary with a single operation.
To delete an entire dictionary, use the del statement. The following is a simple illustration:
Example
dict = {'Name': 'John', 'Age': 20}
print ("dict['Name'] ", dict['Name'])
print ("dict['Age'] ", dict['Age'])
del dict['Name']; # remove entry with key 'Name'
dict.clear(); # remove all entries in dict
del dict ;
print ("dict['Age']: ", dict['Age'])
Output
dict['Name'] John dict['Age'] 20 Traceback (most recent call last): File "", line 7, in TypeError: 'type' object is not subscriptable
No limitations apply to dictionary values, and they may be either standard Python objects or user-defined objects. However, the same cannot be said for the keys.
There are two essential considerations regarding dictionary keys.
Dictionary definitions in Python are enclosed in brackets. Each dictionary entry is a pair of the form key: value. Any type of value or key is acceptable.
dVar = {1:'value','key':2}
> type(dVar)
We use the key to retrieve the respective value. But not the other way around.
Example
dVar = {1:'value','key':2}
print(type(dVar))
print("dVar[1] = ", dVar[1])
print("dVar['key'] = ", dVar['key'])
# Generates error
print("dVar[2] = ", dVar[2])
Output
dVar[1] = value dVar['key'] = 2 Traceback (most recent call last): File " ", line 9, in KeyError: 2 >
This concludes the Python Data Type lesson. In the next lesson, you will learn the type conversion operations in Python.