Python Data Types Explained

Computer is a data processing device. Computer stores the data in its memory and processes it as per the given program. Data is a representation of facts about a certain object.

Some examples of data −

• Data of students − name, gender, class, marks, age, fee etc.

• Data of books in library − title, author, publisher, price, pages, year of publication etc.

• Data of employees in an office − name, designation, salary, department, branch, etc.

Python - Data Types

Python data type represents a kind of value and determines what operations can be done on it. Numeric, non-numeric and Boolean (true/false) data are the most obvious data types. However, each programming language has its own classification largely reflecting its programming philosophy.

Python identifies the data by different data types as per the following diagram −

Python's data model defines four main data types. They are Number, Sequence, Set and Dictionary (also called Mapping)

Python - Number Type

Any data item having a numeric value is a number. There are Four standard number data types in Python. They are integer, floating point, Boolean and Complex. Each of them have built-in classes in Python library, called int, float, bool and complex respectively.

In Python, a number is an object of its corresponding class. For example, an integer number 123 is an object of int class. Similarly, 9.99 is a floating point number, which is an object of float class.

Python's standard library has a built-in function type(), which returns the class of the given object. Here, it is used to check the type of an integer and floating point number.

The fractional component of a float number can also be represented in scientific format. A number -0.000123 is equivalent to its scientific notation 1.23E-4 (or 1.23e-4).

A complex number is made up of two parts - real and imaginary. They are separated by '+' or '-' signs. The imaginary part is suffixed by 'j' which is the imaginary number. The square root of -1 (√−𝟏), is defined as imaginary number. Complex number in Python is represented as x+yj, where x is the real part, and y is the imaginary part. So, 5+6j is a complex number.

A Boolean number has only two possible values, as represented by the keywords, True and False. They correspond to integer 1 and 0 respectively.

With Python's arithmetic operators you can perform operations such as addition, subtraction etc.

Python - Sequence Types

Sequence is a collection data type. It is an ordered collection of items. Items in the sequence have a positional index starting with 0. It is conceptually similar to an array in C or C++. There are three sequence types defined in Python. String, List and Tuple.

Python - Strings

A string is a sequence of one or more Unicode characters, enclosed in single, double or triple quotation marks (also called inverted commas). As long as the same sequence of characters is enclosed, single or double or triple quotes don't matter. Hence, following string representations are equivalent.

A string in Python is an object of str class. It can be verified with type() function.

You want to embed some text in double quotes as a part of string, the string itself should be put in single quotes. To embed a single quoted text, string should be written in double quotes.

Since a string is a sequence, each character in it is having a positional index starting from 0. To form a string with triple quotes, you may use triple single quotes, or triple double quotes – both versions are similar.

Triple quoted string is useful to form a multi-line string.

A string is a non-numeric data type. Obviously, we cannot perform arithmetic operations on it. However, operations such as slicing and concatenation can be done. Python's str class defines a number of useful methods for string processing. We shall learn these methods in the subsequent chapter on Strings.

Python - Lists

In Python, List is an ordered collection of any type of data items. Data items are separated by comma (,) symbol and enclosed in square brackets ([]). A list is also a sequence, hence.

each item in the list has an index referring to its position in the collection. The index starts from 0.

The list in Python appears to be similar to array in C or C++. However, there is an important difference between the two. In C/C++, array is a homogenous collection of data of similar types. Items in the Python list may be of different types.

A list in Python is an object of list class. We can check it with type() function.

As mentioned, an item in the list may be of any data type. It means that a list object can also be an item in another list. In that case, it becomes a nested list.

A list item may be a tuple, dictionary, set or object of user defined class also.

List being a sequence, it supports slicing and concatenation operations as in case of string. With the methods/functions available in Python's built-in list class, we can add, delete or update items, and sort or rearrange the items in the desired order. We shall study these aspects in a subsequent chapter.

Python - Tuples

In Python, a Tuple is an ordered collection of any type of data items. Data items are separated by comma (,) symbol and enclosed in parentheses or round brackets (). A tuple is also a sequence, hence each item in the tuple has an index referring to its position in the collection. The index starts from 0.

In Python, a tuple is an object of tuple class. We can check it with the type() function.

As in case of a list, an item in the tuple may also be a list, a tuple itself or an object of any other Python class.

To form a tuple, use of parentheses is optional. Data items separated by comma without any enclosing symbols are treated as a tuple by default.

The two sequence types list and tuple appear to be similar except the use of delimiters, list uses square brackets ([]) while tuple uses parentheses. However, there is one major

difference between list and tuple. List is mutable object, whereas tuple is immutable. An object is immutable means once it is stored in the memory, it cannot be changed.

Let us try to understand the mutability concept. We have a list and tuple object with same data items.

Both are sequences, hence each item in both has an index. Item at index number 1 in both is 2.

Let us try to change the value of item index number 1 from 2 to 20 in list as well as tuple.

The error message 'tuple' object does not support item assignment tells you that a tuple object cannot be modified once it is formed. This is called an immutable object.

Immutability of tuple also means that Python's tuple class doesn't have the functionality to add, delete or sort items in a tuple. However, since it is a sequence, we can perform slicing and concatenation.

Python - Dictionary Type

Python's dictionary is example of mapping type. A mapping object 'maps' value of one object with another. In a language dictionary we have pairs of word and corresponding meaning. Two parts of pair are key (word) and value (meaning). Similarly, Python dictionary is also a collection of key:value pairs. The pairs are separated by comma and put inside curly brackets {}. To establish mapping between key and value, the semicolon':' symbol is put between the two.

Each key in a dictionary must be unique, and should be a number, string or tuple. The value object may be of any type, and may be mapped with more than one keys (they need not be unique)

In Python, dictionary is an object of the built-in dict class. We can check it with the type() function.

Python's dictionary is not a sequence. It is a collection of items but each item (key:value pair) is not identified by positional index as in string, list or tuple. Hence, slicing operation cannot be done on a dictionary. Dictionary is a mutable object, so it is possible to perform add, modify or delete actions with corresponding functionality defined in dict class. These operations will be explained in a subsequent chapter.

Python - Set Type

Set is a Python implementation of set as defined in Mathematics. A set in Python is a collection, but is not an indexed or ordered collection as string, list or tuple. An object cannot appear more than once in a set, whereas in List and Tuple, same object can appear more than once.

Comma separated items in a set are put inside curly brackets or braces. Items in the set collection may be of different data types.

Note that items in the set collection may not follow the same order in which they are entered. The position of items is optimized by Python to perform operations over set as defined in mathematics.

Python's Set is an object of built-in set class, as can be checked with the type() function.

A set can store only immutable objects such as number (int, float, complex or bool), string or tuple. If you try to put a list or a dictionary in the set collection, Python raises a TypeError.

Hashing is a mechanism in computer science which enables quicker searching of objects in computer's memory. Only immutable objects are hashable.

Even if a set doesn't allow mutable items, the set itself is mutable. Hence, add/delete/update operations are permitted on a set object, using the methods in built-in set class. Python also has a set of operators to perform set manipulation. The methods and operators are explained in a latter chapter

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