In python, a dictionary is an unordered collection of data which is used to store data values such as map unlike other datatypes that store only single values. Keys of a dictionary must be unique and of immutable data type such as Strings, Integers, and tuples, but the key values can be repeated and be of any type. Dictionaries are mutable, therefore keys can be added or removed even after defining a dictionary in python. They are many ways to remove a key from a dictionary, following are few ways. Using pop(key, d) The pop(key, d) method returns the value ... Read More

Dictionary is an unordered collection of key-value pairs. Each element is not identified by positional index. Moreover, the fact that key can’t be repeated, we simply use a new key and assign a value to it so that a new pair will be added to dictionary. >>> D1 = {1: 'a', 2: 'b', 3: 'c', 'x': 1, 'y': 2, 'z': 3} >>> D1[10] = 'z' >>> D1 {1: 'a', 2: 'b', 3: 'c', 'x': 1, 'y': 2, 'z': 3, 10: 'z'}

Built-in dictionary class has update() method which merges elements of argument dictionary object with calling dictionary object. >>> a = {1:'a', 2:'b', 3:'c'} >>> b = {'x':1,'y':2, 'z':3} >>> a.update(b) >>> a {1: 'a', 2: 'b', 3: 'c', 'x': 1, 'y': 2, 'z': 3} From Python 3.5 onwards, another syntax to merge two dictionaries is available >>> a = {1:'a', 2:'b', 3:'c'} >>> b = {'x':1,'y':2, 'z':3} >>> c = {**a, **b} >>> c {1: 'a', 2: 'b', 3: 'c', 'x': 1, 'y': 2, 'z': 3}

Any built-in data type converted into its string representation by str() function >>> str(10) '10' >>> str(11.11) '11.11' >>> str(3+4j) '(3+4j)' >>> str([1,2,3]) '[1, 2, 3]' >>> str((1,2,3)) '(1, 2, 3)' >>> str({1:11, 2:22, 3:33}) '{1: 11, 2: 22, 3: 33}' For a user defined class to be converted to string representation, __str__() function needs to be defined in it. >>> class rectangle: def __init__(self): self.l=10 self.b=10 def __str__(self): return 'length={} breadth={}'.format(self.l, self.b) >>> r1=rect() >>> str(r1) 'length = 10 breadth = 10'

Type conversion is the transformation of a Python data type into another data type. Implicit type conversion and explicit type conversion are the two basic categories of type conversion procedures in Python. We will cover the following topics in this article − Implicit Type Conversion in Python is carried out by the Python interpreter automatically. In Python, explicit type conversion must be performed directly by the programmer. Let's study more about these two approaches in depth and with some illustrations. Implicit Type conversions Implicit type conversion occurs when the Python interpreter automatically changes an object's data type without ... Read More

When used with strings, plus (+) is defined as concatenation operator. It appends second string to the first string. >>> s1 = 'TutorialsPoint ' >>> s2 = 'Hyderabad' >>> print (s1+s2) TutorialsPoint Hyderabad

When used with strings, asterisk (*) is defined as repetition operator. It concatenates given string as many times as number followed by asterisk. >>> string = 'abcdefghij' >>> print (string*2) abcdefghijabcdefghij

The following code splits given string by a period and a line break as followsExampleimport re s = """Hi. It's nice meeting you. My name is Jason.""" result = re.findall(r'[^\s\.][^\.]+', s) print resultOutputThis gives the following output['Hi', "It's nice meeting you", 'My name is Jason']

Have you ever come across situations where you had to determine if a string starts or ends with a particular pattern in Python? If so, you don’t need to worry, for Python's regular expressions provide a solution in such cases. With the power of regex, you can easily check whether a string begins or concludes with a specific sequence of characters. In this comprehensive article, we will explore various code examples that demonstrate how to use Python's regex to accomplish this task effortlessly. Before taking a plunge into the examples, let's take a break and understand what regular expressions are ... Read More

Have you ever encountered a situation where you needed to compare strings in Python but wanted to ignore the differences in letter casing? Worry not, for Python provides straightforward solutions to achieve case−insensitive string comparisons. In this comprehensive guide, we will explore five different code examples, each showcasing a unique method for conducting case−insensitive string comparisons. So, let's dive in and discover the wonders of Python's string comparison versatility! Before we delve into the examples, let's briefly understand what a case−insensitive string comparison entails. When comparing strings, a case−insensitive approach treats uppercase and lowercase letters as equal, thereby disregarding the ... Read More