Tutorial Playlist
200 Lessons1. Introduction to Python
2. Features of Python
3. How to install python in windows
4. How to Install Python on macOS
5. Install Python on Linux
6. Hello World Program in Python
7. Python Variables
8. Global Variable in Python
9. Python Keywords and Identifiers
10. Assert Keyword in Python
11. Comments in Python
12. Escape Sequence in Python
13. Print In Python
14. Python-if-else-statement
15. Python for Loop
16. Nested for loop in Python
17. While Loop in Python
18. Python’s do-while Loop
19. Break in Python
20. Break Pass and Continue Statement in Python
21. Python Try Except
22. Data Types in Python
23. Float in Python
24. String Methods Python
25. List in Python
26. List Methods in Python
27. Tuples in Python
28. Dictionary in Python
29. Set in Python
30. Operators in Python
31. Boolean Operators in Python
32. Arithmetic Operators in Python
33. Assignment Operator in Python
34. Bitwise operators in Python
35. Identity Operator in Python
36. Operator Precedence in Python
37. Functions in Python
38. Lambda and Anonymous Function in Python
39. Range Function in Python
40. len() Function in Python
41. How to Use Lambda Functions in Python?
42. Random Function in Python
43. Python __init__() Function
44. String Split function in Python
45. Round function in Python
46. Find Function in Python
47. How to Call a Function in Python?
48. Python Functions Scope
49. Method Overloading in Python
50. Method Overriding in Python
51. Static Method in Python
52. Python List Index Method
53. Python Modules
54. Math Module in Python
55. Module and Package in Python
56. OS module in Python
57. Python Packages
58. OOPs Concepts in Python
59. Class in Python
60. Abstract Class in Python
61. Object in Python
62. Constructor in Python
63. Inheritance in Python
64. Multiple Inheritance in Python
65. Encapsulation in Python
66. Data Abstraction in Python
67. Opening and closing files in Python
68. How to open JSON file in Python
69. Read CSV Files in Python
70. How to Read a File in Python
71. How to Open a File in Python?
72. Python Write to File
73. JSON Python
74. Python JSON – How to Convert a String to JSON
75. Python JSON Encoding and Decoding
76. Exception Handling in Python
77. Recursion in Python
78. Python Decorators
79. Python Threading
80. Multithreading in Python
81. Multiprocеssing in Python
82. Python Regular Expressions
83. Enumerate() in Python
84. Map in Python
85. Filter in Python
86. Eval in Python
87. Difference Between List, Tuple, Set, and Dictionary in Python
88. List to String in Python
89. Linked List in Python
90. Length of list in Python
91. Reverse a List in Python
92. Python List remove() Method
93. How to Add Elements in a List in Python
94. How to Reverse a List in Python?
95. Difference Between List and Tuple in Python
96. List Slicing in Python
97. Sort in Python
98. Merge Sort in Python
99. Selection Sort in Python
100. Sort Array in Python
101. Sort Dictionary by Value in Python
102. Datetime Python
103. Random Number in Python
104. 2D Array in Python
105. Abs in Python
106. Advantages of Python
107. Anagram Program in Python
108. Append in Python
109. Applications of Python
110. Armstrong Number in Python
111. Assert in Python
112. Binary Search in Python
113. Binary to Decimal in Python
114. Bool in Python
115. Calculator Program in Python
116. chr in Python
117. Control Flow Statements in Python
118. Convert String to Datetime Python
119. Count in python
120. Counter in Python
Now Reading
121. Data Visualization in Python
122. Datetime in Python
123. Extend in Python
124. F-string in Python
125. Fibonacci Series in Python
126. Format in Python
127. GCD of Two Numbers in Python
128. How to Become a Python Developer
129. How to Run Python Program
130. In Which Year Was the Python Language Developed?
131. Indentation in Python
132. Index in Python
133. Interface in Python
134. Is Python Case Sensitive?
135. Isalpha in Python
136. Isinstance() in Python
137. Iterator in Python
138. Join in Python
139. Leap Year Program in Python
140. Lexicographical Order in Python
141. Literals in Python
142. Matplotlib
143. Matrix Multiplication in Python
144. Memory Management in Python
145. Modulus in Python
146. Mutable and Immutable in Python
147. Namespace and Scope in Python
148. OpenCV Python
149. Operator Overloading in Python
150. ord in Python
151. Palindrome in Python
152. Pass in Python
153. Pattern Program in Python
154. Perfect Number in Python
155. Permutation and Combination in Python
156. Prime Number Program in Python
157. Python Arrays
158. Python Automation Projects Ideas
159. Python Frameworks
160. Python Graphical User Interface GUI
161. Python IDE
162. Python input and output
163. Python Installation on Windows
164. Python Object-Oriented Programming
165. Python PIP
166. Python Seaborn
167. Python Slicing
168. type() function in Python
169. Queue in Python
170. Replace in Python
171. Reverse a Number in Python
172. Reverse a string in Python
173. Reverse String in Python
174. Stack in Python
175. scikit-learn
176. Selenium with Python
177. Self in Python
178. Sleep in Python
179. Speech Recognition in Python
180. Split in Python
181. Square Root in Python
182. String Comparison in Python
183. String Formatting in Python
184. String Slicing in Python
185. Strip in Python
186. Subprocess in Python
187. Substring in Python
188. Sum of Digits of a Number in Python
189. Sum of n Natural Numbers in Python
190. Sum of Prime Numbers in Python
191. Switch Case in Python
192. Python Program to Transpose a Matrix
193. Type Casting in Python
194. What are Lists in Python?
195. Ways to Define a Block of Code
196. What is Pygame
197. Why Python is Interpreted Language?
198. XOR in Python
199. Yield in Python
200. Zip in Python
Counting is a basic process in programming, and Python is no different. Whether you're tallying items in a list, monitoring iterations in a loop, or analyzing data, Python offers a robust collection of tools for counting and enumeration. In this tutorial, we're going to speak about counting using Python in a fairly easy approach. Count in Python includes various built-in methods and utilities, making counting easy and handy for diverse programming activities. Let’s look at detailed insights on the Python count function.
Counter in Python is a library that counts the frequency of items in a sequence. It builds a dictionary-like object that calculates the number of items in a text or dataset. The Counter is a subclass of Dictionary and is used to keep track of items and their count. The count object comes packed with numerous built-in methods that let users identify how many components are contained in a string or mix several counter objects.
This Python count function is a valuable tool in Python for data analysts and coders across several sectors, including banking, retail, marketing, and more.
The count() function in Python is used to count the number of occurrences of a specified element in a list, tuple, or string. Here is the syntax for the count() function:
sequence.count(element)
In the above syntax:
Here are a few examples of how to use the count() function:
Code:
# Example 1: Counting occurrences in a list
my_list = [1, 0, 2, 2, 3, 2]
count = my_list.count(2)
print(count) # Output: 3 (because 2 appears 3 times in the list)
# Example 2: Counting occurrences in a tuple
my_tuple = (1, 4, 4, 4, 4, 2)
count = my_tuple.count(2)
print(count) # Output: 1 (because 2 appears 1 times in the tuple)
# Example 3: Counting occurrences in a string
my_string = "hello, world!"
count_of_l = my_string.count("l")
print(count_of_l) # Output: 3 (because "l" appears 3 times in the string)
In these examples, the count() function is applied to different types of sequences (list, tuple, and string) to count the occurrences of a specific element (2 and l) within each sequence.
Counters are devices in digital electronics that count the number of times a given event or process has happened, frequently about a clock signal. Counters are used for counting and monitoring frequency and time, incrementing memory locations, and recording the number of iterations that have happened.
Counters can count certain events occurring in the circuit, follow certain sequences based on design, and be constructed using flip-flops. They may also be utilized as frequency dividers where the frequency of a particular pulse waveform is split. Counters are utilized in numerous areas, including digital logic, digital signal processing, computer architectures, traffic control systems, medical and industrial applications, and retail outlets.
Code:
from collections import Counter
# Create a list of items
my_list = [1, 2, 2, 3, 4, 2, 1, 3, 5, 4, 1]
# Create a Counter object
counter = Counter(my_list)
# Count the occurrences of specific elements
count_of_2 = counter[2]
count_of_1 = counter[1]
count_of_5 = counter[5]
# Print the counts
print("Count of 2:", count_of_2) # Output: Count of 2: 3
print("Count of 1:", count_of_1) # Output: Count of 1: 3
print("Count of 5:", count_of_5) # Output: Count of 5: 1
# Get a dictionary of counts for all elements
counts_dict = dict(counter)
# Print the counts as a dictionary
print("Counts Dictionary:", counts_dict)
Code:
from collections import Counter
p = [11, 2, 3, 5, 6, 10, 11, 8, 9]
n = Counter(p)
print(n)
for k in n.keys():
print(k, ":", n[k])
n_keys = list(n.keys())
n_values = list(n.values())
print(n_keys)
print(n_values)
Code:
from collections import Counter
w = Counter("upGradTutorial!")
for i in w.elements():
print ( i, end = " ")
print()
x = Counter({'up' : 1 , 'Grad' : 2,
'Tutorial' : 2, 'python' : 3})
for i in x.elements():
print ( i, end = " ")
print()
y = Counter([1, 2, 21, 12, 2, 44, 5,
13, 15, 5, 19, 21, 5])
for i in y.elements():
print ( i, end = " ")
print()
z = Counter( a = 2, b = 3, c = 6, d = 1, e = 5)
for i in z.elements():
print ( i, end = " ")
Code:
from collections import Counter
x = Counter ("upGradTutorial")
print(x.elements())
Code:
from collections import Counter
# Create a Counter object
counter = Counter()
# Add elements to the Counter
counter.update([1, 2, 2, 3, 4, 2, 1, 3, 5, 4, 1])
# Print the initial counts
print("Initial Counts:", counter)
# Add more elements to the Counter
counter.update([2, 3, 3, 3, 4, 4, 4, 5, 5])
# Print the updated counts
print("Updated Counts:", counter)
# Subtract elements from the Counter
elements_to_subtract = [1, 2, 3, 4]
counter.subtract(elements_to_subtract)
# Print the subtracted counts
print("Subtracted Counts:", counter)
Code:
from collections import Counter
# Create a Counter object
counter = Counter([1, 2, 2, 3, 4, 2, 1, 3, 5, 4, 1])
# Access counts of specific elements
count_of_1 = counter[1]
count_of_2 = counter[2]
count_of_5 = counter[5]
# Print the counts
print("Count of 1:", count_of_1) # Output: Count of 1: 3
print("Count of 2:", count_of_2) # Output: Count of 2: 3
print("Count of 5:", count_of_5) # Output: Count of 5: 1
Code:
from collections import Counter
d = {'x': 2, 'y': 4, 'z': 6}
del d["y"]
print("Dictionary After Deletion:", Counter(d))
Code:
from collections import Counter
# Create two Counter objects
counter1 = Counter([1, 2, 2, 3, 4, 2, 1, 3, 5, 4, 1])
counter2 = Counter([2, 3, 3, 3, 4, 4, 4, 5, 5])
# Addition: Combine counts of elements from both counters
result_add = counter1 + counter2
print("Addition Result:", result_add)
# Subtraction: Subtract counts of elements in counter2 from counter1
result_sub = counter1 - counter2
print("Subtraction Result:", result_sub)
# Intersection: Calculate the minimum counts of common elements
result_intersection = counter1 & counter2
print("Intersection Result:", result_intersection)
# Union: Calculate the maximum counts of all elements
result_union = counter1 | counter2
print("Union Result:", result_union)
Code:
from collections import Counter
# Create a Counter for characters in a string
my_string = "hello, world!"
char_counter = Counter(my_string)
# Print the character counts
print("Character Counts:", char_counter)
# Access the count of a specific character
count_of_l = char_counter['l']
print("Count of 'l':", count_of_l)
Code:
from collections import Counter
# Create a dictionary
my_dict = {'apple': 3, 'banana': 2, 'cherry': 1, 'date': 4, 'fig': 2}
# Create a Counter for dictionary keys
key_counter = Counter(my_dict)
# Print the key counts
print("Key Counts:", key_counter)
# Access the count of a specific key
count_of_apple = key_counter['apple']
print("Count of 'apple':", count_of_apple)
Code:
from collections import Counter
# Create a tuple
my_tuple = (1, 2, 2, 3, 4, 2, 1, 3, 5, 4, 1)
# Create a Counter for elements in the tuple
tuple_counter = Counter(my_tuple)
# Print the element counts
print("Element Counts:", tuple_counter)
# Access the count of a specific element
count_of_2 = tuple_counter[2]
print("Count of 2:", count_of_2)
The Python Counter class from the collections module provides several important methods for working with counted elements. Here are some of the most commonly used methods:
Returns an iterator over the elements in the Counter. Elements are repeated as many times as their count.
Example:
Code:
from collections import Counter
my_counter = Counter("abracadabra")
elements_iterator = my_counter.elements()
for element in elements_iterator:
print(element)
Returns a list of the n most common elements and their counts as tuples.
If n is not specified, it returns all elements.
Example:
Code:
from collections import Counter
my_counter = Counter("abracadabra")
most_common_items = my_counter.most_common(3)
print(most_common_items)
Subtracts counts from the Counter using elements from an iterable (e.g., list, tuple, or another Counter).
Example:
Code:
from collections import Counter
my_counter = Counter("abracadabra")
my_counter.subtract("banana")
print(my_counter)
The Counter class in Python, part of the collections module, is used for counting the occurrences of elements in an iterable. It's a powerful tool for various data analysis and manipulation tasks. Here are some common use cases for Counter in Python:
from collections import Counter
data = [1, 2, 2, 3, 3, 3, 4, 4, 4, 4]
counts = Counter(data)
print(counts)
from collections import Counter
text = "Hello, World!"
char_counts = Counter(text)
print(char_counts)
data = [1, 2, 2, 3, 3, 3, 4, 4, 4, 4]
counts = Counter(data)
most_common = counts.most_common(2) # Get the top 2 most common elements
print(most_common)
from collections import Counter
c1 = Counter(a=3, b=2, c=1)
c2 = Counter(a=1, b=2, c=3)
# Addition
c3 = c1 + c2 # Adds counts for each element
print(c3)
# Subtraction
c4 = c1 - c2 # Subtracts counts for each element
print(c4)
The count function in Python is a powerful tool that simplifies the work of counting elements in iterable objects, such as lists, strings, or dictionaries. Its simplicity, speed, and adaptability make it essential for data analysis, text processing, and many other programming tasks.
1. What is an example of using the collections Counter in Python?
A collections counter Python example is to count the frequency of elements in a list. For example, my_list = [1][2][3][1][2][1][4] and my_counter = Counter(my_list) would create a Counter object with the keys 1, 2, 3, and 4, and their corresponding values of 3, 2, 1, and 1. You can then access the count of a specific element using the syntax my_counter[element].
2. How do I use the count function in Python with strings?
To use the Python counter string function, you can call the count method on a string object with the element you want to count as the argument. For example, "hello".count('l') would return 2 since the letter 'l' appears twice in the string "hello".
3. What is Python Counter Class?
Python Counter Class is a built-in class in Python's Collections module. It is a subclass of Dictionary and is used to keep track of items and their count. It is an unordered collection whose items are kept as dictionary keys and their counts are recorded as dictionary values. The objective of the Python Counter Class is to count the frequency of items in an iterable object, such as a list, tuple, or string. It offers an effective approach to counting the frequency of items in a collection.
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Director of Engineering
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upGrad does not grant credit; credits are granted, accepted or transferred at the sole discretion of the relevant educational institution offering the diploma or degree. We advise you to enquire further regarding the suitability of this program for your academic, professional requirements and job prospects before enr...