Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
XML (eXtensible Markup Language) stands tall as a widely embraced format for storing and exchanging structured information. In the realm of efficient data storage and retrieval, MySQL has earned its reputation as a go-to relational database management system (RDBMS). Python, blessed with its versatile libraries, presents an exquisite union for seamlessly handling XML and MySQL. Embark on a journey with us as we dive into the art of storing XML data in a MySQL database using Python, unraveling each step with intricacy and flair. Step 1: Importing the Essential Libraries Let us kickstart our endeavor by importing the ... Read More
While working with Pandas DataFrames, situations may arise where arithmetic operations between attributes are necessary. One such operation is deducting two attributes. In this guide, we will delve into three distinct techniques to deduct two attributes in a Pandas DataFrame: employing the `sub` method, utilizing the `apply` method combined with a lambda function, and leveraging the `subtract` function. Examples will aid in understanding these approaches. Method 1: Employing the `sub` method The `sub` method is an intrinsic Pandas function that facilitates direct deduction of one attribute from another. This technique is straightforward and effective for performing deductions between ... Read More
In the vast expanse of data exploration, the art of standardization, sometimes referred to as feature scaling, assumes a paramount role as a preparatory step. It involves the transformation of disparate data elements into a harmonized range or scale, enabling fair analysis and comparison. Python's extraordinary library, Pandas, seamlessly facilitates this endeavor. Picture Pandas DataFrames as two-dimensional, ever-shifting, heterogeneous tabular data arrays, meticulously crafted to streamline the manipulation of data. With intuitive syntax and dynamic capabilities, it has emerged as the structure of choice for data enthusiasts worldwide. Let us delve deeper into the methods we can employ to ... Read More
The vast universe of Python includes a shining constellation named Pandas. Recognized globally for its might in data management and manipulation, it empowers data analysts with tools that act as an extension of their thoughts, transforming ideas into reality. The crux of this discussion lies in a particular feature of Pandas, the fusion of DataFrames along an axis. When the challenge is to blend information from diverse origins or conglomerate data for a comprehensive analysis, Pandas offers a basket of functions like concat(), append(), and merge(). The onus is on us to pick the tool that aligns with our ... Read More
Embarking on the vast domains of machine learning and data science, one encounters tasks that might appear inconsequential but hold a crucial position in the broader perspective. One such vital task is the division of data into training and validation sets - a foundational step for creating an effective predictive model. Scikit-learn, a prominent Python library for machine learning, boasts a versatile function, train_test_split(), crafted to address this task with remarkable ease. This treatise aims to steer you through the process of partitioning your data using scikit-learn's train_test_split() function. Syntax from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = ... Read More
In the domain of machine learning or artificial intelligence models, data stands as the backbone. The way this data gets handled shapes the holistic performance of the model. This includes the indispensable task of segregating the dataset into learning and verification sets. While sklearn's train_test_split() is a frequently employed method, there could be instances when a Python aficionado might not have it at their disposal or is curious to grasp how to manually attain a similar outcome. This discourse delves into how one can segregate data into learning and verification sets without leaning on sklearn. We will bank on Python's ... Read More
It is sometimes necessary to insert a line break in Excel to show the entire string inside the cell because the texts are too long to fit inside a cell without spilling out the ends, which looks messy and unattractive. Representing the contents of the particular in various lines instead of one long line is known as "wrapping text". With the help of wrapping text, the users would be capable to eliminate the "truncated column" impact and enhance the readability of the text and printing compatibility. It also assures the users in managing a column that have constant value in ... Read More
Cell formatting is wonderful feature of Microsoft excel where cell value or text font size, type, color, background color may be formatted based on different criteria. In this, methods for format cell value font color based on a given condition have discussed. Here, a default color of cell value is changed in red color when value is negative and green color when cell value is positive. Further section presents, methods of cell value color formatting with suitable examples. Format cell value red if it is negative or green ... Read More
In this article, we are going to find the different ways to find the frequency of numbers present in an array []. These methods are very useful in doing competitive programming for different problems for different cases. Sometimes, calculating the frequency of elements whether it is numbers or alphabets presented in the array is a complicated task. Various algorithms like Searching, array, divide and conquer can be used to find the repeated elements defined in the array. Note- Take an integer array. Let's explore the article, to know how it can be solved by using Java programming ... Read More
The problem statement includes using Vantieghems theorem for primality test i.e. we will check for a positive number N which will be user input and print if the number is a prime number or not using the Vantieghems theorem. Vantieghem’s Theorem The Vantieghems theorem for primality states that a positive number, N is a prime number if the product of $\mathrm{2^{i}−1}$ where the value of i ranges from 1 to N−1 is congruent to N modulo $\mathrm{2^{N}−1}$ If both the values are congruent then the number N is a prime number else it is not a prime number. Congruent ... Read More