<\/span><\/h2>\n\n\n\nPython has the following data types built-in by default, in these categories:<\/strong><\/p>\n\n\n\nText Type:<\/td> Str<\/td><\/tr> Numeric Types:<\/td> int<\/code>, float<\/code>, complex<\/code><\/td><\/tr>Sequence Types:<\/td> list<\/code>, tuple<\/code>, range<\/code><\/td><\/tr>Mapping Type:<\/td> dict<\/code><\/td><\/tr>Set Types:<\/td> set<\/code>, frozenset<\/code><\/td><\/tr>Boolean Type:<\/td> bool<\/code><\/td><\/tr>Binary Types:<\/td> bytes<\/code>, bytearray<\/code>, memoryview<\/code><\/td><\/tr>None Type:<\/td> NoneType<\/code><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<\/span>Common Python Data Types<\/strong><\/span><\/h2>\n\n\n\nPython offers a range of built-in data types that cater to different needs. Let’s explore some of the most commonly used ones:<\/p>\n\n\n\n
\nInteger (int)<\/strong>: Represents whole numbers, both positive and negative.<\/li>\n\n\n\nFloat (float)<\/strong>: Represents decimal numbers, also known as floating-point numbers.<\/li>\n\n\n\nString (str)<\/strong>: Represents sequences of characters, such as text.<\/li>\n\n\n\nBoolean (bool)<\/strong>: Represents the truth values True<\/code> and False<\/code>.<\/li>\n\n\n\nList<\/strong>: Represents an ordered collection of items. Lists can contain elements of different data types.<\/li>\n\n\n\nTuple<\/strong>: Similar to a list but is immutable, meaning its elements cannot be changed after creation.<\/li>\n\n\n\nDictionary<\/strong>: Represents a collection of key-value pairs, allowing you to associate values with specific keys.<\/li>\n\n\n\nSet<\/strong>: Represents an unordered collection of unique elements.<\/li>\n<\/ol>\n\n\n\n<\/span>Examples of Python Data Types<\/strong><\/span><\/h3>\n\n\n\nLet’s delve into some examples to better understand these data types.<\/p>\n\n\n\n
<\/circle><\/circle><\/circle><\/g><\/svg><\/span><\/path><\/path><\/svg><\/span>#Integer (int):<\/span><\/span>\nage <\/span>=<\/span> <\/span>25<\/span><\/span>\n<\/span>\n#Float (float):<\/span><\/span>\ntemperature <\/span>=<\/span> <\/span>98.6<\/span><\/span>\n<\/span>\n#String (str):<\/span><\/span>\ngreeting <\/span>=<\/span> <\/span>"<\/span>Hello, world!<\/span>"<\/span><\/span>\n<\/span>\n#Boolean (bool):<\/span><\/span>\nis_valid <\/span>=<\/span> <\/span>True<\/span><\/span>\n<\/span>\n#List:<\/span><\/span>\nnumbers <\/span>=<\/span> [<\/span>1<\/span>, <\/span>2<\/span>, <\/span>3<\/span>, <\/span>4<\/span>, <\/span>5<\/span>]<\/span><\/span>\n<\/span>\n#Tuple:<\/span><\/span>\ncoordinates <\/span>=<\/span> (<\/span>10<\/span>, <\/span>20<\/span>)<\/span><\/span>\n<\/span>\n#Dictionary:<\/span><\/span>\nstudent <\/span>=<\/span> {<\/span>"<\/span>name<\/span>"<\/span>: <\/span>"<\/span>Alice<\/span>"<\/span>, <\/span>"<\/span>age<\/span>"<\/span>: <\/span>18<\/span>, <\/span>"<\/span>grade<\/span>"<\/span>: <\/span>"<\/span>A<\/span>"<\/span>}<\/span><\/span>\n<\/span>\n#Set:<\/span><\/span>\nunique_numbers <\/span>=<\/span> {<\/span>5<\/span>, <\/span>10<\/span>, <\/span>15<\/span>, <\/span>20<\/span>}<\/span><\/span>\n<\/span><\/code><\/pre>Python<\/span><\/div>\n\n\n\n<\/p>\n\n\n\n
<\/span>Using Data Types Effectively<\/strong><\/span><\/h3>\n\n\n\nProperly utilizing data types is essential for writing efficient and error-free code. Python’s built-in functions and methods often depend on the correct data type. For instance, you can’t concatenate a string and an integer directly. However, you can convert the integer to a string using the str()<\/span><\/code> function:<\/p>\n\n\n\n<\/circle><\/circle><\/circle><\/g><\/svg><\/span><\/path><\/path><\/svg><\/span>number <\/span>=<\/span> <\/span>42<\/span><\/span>\nmessage <\/span>=<\/span>