**Problem Statement:** Ankit is always excited about sunday. It is favourite day, when he used to play all day And goes to cycling with his group. So every time when the months starts he counts the number of sundays he will get to enjoy. Considering the month can start with any day, be it Sun, Mon…. Or so on. Count the number of Sundays Ankit will get within n number of days.

# Author: Ankit Rai

## TCS NQT Coding Question-2: toggling all bits

**Problem Statement:** Joseph is learning digital logic subject which will be for his next semester. He usually tries to solve unit assignment problems before the lecture. Today he got one tricky question. The problem statement is “A positive integer has been given as an input.Convert decimal value to binary representation. Print the positive integer value after toggling all bits”.

## TCS NQT Coding Question-1: Factory empty packets

**Problem Statement:** A factory is packing candies into the packets. The candies packets here represent an array of N number of integer values. The task is to find the empty packets(0) of candies and push it to the end of the conveyor belt(array).

## Python | How to read a csv file using pandas?

CSV (Comma-Separated Values) files are a popular format for storing tabular data, and Python’s Pandas library provides powerful tools for reading, manipulating, and analyzing such data. In this article, we’ll explore how to read CSV files using Pandas, covering different cases and options to efficiently load data into a pandas DataFrame.

## Python | Introduction to numpy

NumPy, short for **Numerical Python**, is a open-source library in Python for numerical computation. It provides a powerful array object and a collection of functions for manipulating and processing arrays efficiently. NumPy is widely used in fields such as data science, machine learning, signal processing, and scientific computing. In this article, we’ll explore the basics of NumPy, its key features, and how it revolutionizes numerical computation in Python.

## Python | Introduction to pandas

Pandas is an open-source data manipulation and analysis library for Python. It provides easy-to-use data structures and functions to efficiently manipulate structured data, making it an essential tool for data scientists, analysts, and developers alike. In this article, we’ll provide a comprehensive introduction to Pandas, covering its key features, data structures, and basic operations, along with practical examples to get you started on your data analysis journey.

## Python | map() function

**Introduction:** The map() is a type of higer order function which is used to apply a given function to each item of an iterable (such as a list, tuple, or set) and returns an iterator that yields the results. In this article, we’ll explore the concept of map() function in Python, explore its syntax, usage, and provide practical examples to illustrate its functionality.

## Python | *args and **kwargs

In Python, ***args** and ****kwargs** are special syntax used in function definitions to accept an arbitrary number of **positional arguments** and **keyword arguments**, respectively. They provide flexibility and convenience in function design, allowing developers to create functions that can handle a variable number of inputs. In this article, we’ll explore the concept of *args and **kwargs in Python functions, explore their syntax, features, and demonstrate their usage through practical examples.

## Python | Dictionary Comprehension

Python’s **dictionary comprehension** is an elegant way to create dictionaries from iterable objects such as lists, tuples, or even other dictionaries. It offers a simple syntax for generating dictionaries with ease and flexibility. In this article, we’ll explore the concept of dictionary comprehension in Python, explore its syntax, features, and demonstrate its usage through practical examples.

## Python | List Comprehension

**Introduction:** List comprehension is a powerful and simple technique in Python for creating lists in a more readable way. It provides a short syntax to generate lists by applying an expression to each item in an iterable. In this article, we’ll explore the concept of list comprehension in Python, explore its syntax, features, and demonstrate its usage through practical examples.