Market research, price monitoring, and content aggregation are just a few examples of the myriad of purposes for which web scraping is utilized and has gained widespread popularity. Although web scraping entails extracting data from websites, there are quite a few legal and ethical concerns surrounding this controversial practice, particularly when it is conducted without the consent of the website's owner. A number of website owners implement anti-scraping measures to thwart potential scrapers, while others even take legal action. In this article, we will learn how not to get caught while web scraping. Why Web Scraping can be Complicated? Web ... Read More

NumPy is a powerful library in Python for numerical computing that provides an array object for the efficient handling of large datasets. Often, it is necessary to normalize the values of a NumPy array to ensure they fall within a specific range. One common normalization technique is to scale the values between 0 and 1. In this article, we will learn how to normalize a NumPy array so the values range exactly between 0 and 1. We will see the different approaches that can be used to achieve this using NumPy, along with syntax and complete examples. Approaches There are ... Read More

Merging two Pandas DataFrames on index can be useful in many data analysis scenarios. For instance, you might have two datasets with different features or data points, but both share a common index. In this case, merging the two DataFrames can help you combine the data in a meaningful way. In this article, we will learn how to merge two Pandas DataFrames based on an index in Python. We will go through the complete steps involved in the merging process and illustrate each step with code examples. What is DataFrames in Pandas? One of Pandas library's most crucial data structures ... Read More

HTML (Hypertext Markup Language) is the foundation of the internet. Websites use HTML to create and display content in a structured manner. In many cases, it's necessary to modify HTML code to add new elements, remove unwanted elements, or make other changes. This is where BeautifulSoup comes in. BeautifulSoup is a Python library that allows you to parse HTML and XML documents. It provides a simple interface for navigating and searching the document tree, as well as for modifying the HTML code. In this article, we'll learn to modify HTML using BeautifulSoup. We will learn the steps of modifying HTML ... Read More

CSV (Comma Separated Values) files are widely used for storing and exchanging data in a simple format. In many data processing tasks, it is necessary to merge two or more CSV files based on a specific column. Fortunately, this can be easily achieved using the Pandas library in Python. In this article, we will learn how to merge two CSV files by a specific column using Pandas in Python. What is Pandas Library? Pandas is an open-source library for information control and examination in Python. It offers tools for working with structured data, such as tabular, time-series, and multidimensional data, ... Read More

Time series data is a crucial part of many business operations, especially those in the finance and manufacturing industries. These datasets often come in multiple tables or files, with each table containing a specific subset of the data. Merging these tables can be a challenging task, mainly when the tables contain data that does not match. In this article, we will learn how to merge time series data that does not match using Pandas. Pandas is a powerful data analysis library in Python that provides extensive tools for merging and manipulating data. We will also learn the different techniques to ... Read More

Python is a versatile programming language that offers programmers various modules and libraries to perform the required tasks. One such powerful function that Python offers is the “cbind”. This stands for column bind. The “cbind” is a powerful tool that allows programmers to combine, merge, and group the arrays, data frames, etc., in Python column-wise. In this article, we will learn how to use the “cbind” in Python. Using zip and list comprehension Zip and list comprehension are two very popular techniques used in many expressions in Python. The zip function can help to combine multiple elements from different iterables. ... Read More

As a programmer, when we need to deal with data, we may need to perform operations only in rows or columns, or both. In pandas, the axis refers to how a function or an operation is applied to the Data Frame or the series. Pandas only can take two values, either 0 or 1, as an argument to the axis property. In this article, we will learn how to use the axis=0 and axis=1 in Pandas. Understand the axis Before we move forward, let us brief you on the axis of pandas. As we know, the data frame in pandas ... Read More

Dictionaries are among the most powerful data structures in Python programming languages. This is a data structure consisting of key-value pairs. It has several advantages; for example, accessing the values occurs in O(1) time complexity, it is memory efficient, easy to update, delete and iterate, and offers many built functions for quick operations. Problem Associated When Lists Are Used Directly We are focusing on this topic because there is a problem associated with when we try to make the lists as the key. Lists are mutable data types in Python. Hence, we can delete, update, and append values inside the ... Read More

PyTorch is a popular open-source machine-learning library. Data scientists, researchers, and developers use this library widely to develop AI/ML products. One of the most important features of PyTorch is the Data Loader class. This class helps to load and batch the data for neural network training efficiently. This article will teach us how to use the Data Loader in PyTorch. Use Data Loader In PyTorch We can follow the following basic rules to perform the Data Loading operation in Python using the PyTorch library − Data Preparation − Create a custom Random Dataset class that generates a random dataset ... Read More