Jagdeesh

SQL LIKE – Simplified Guide to understanding the SQL ‘LIKE’ Operator

You’re going to delve into an essential yet often overlooked operator in the SQL toolkit – the ‘LIKE’ operator What Is the SQL ‘LIKE’ Operator? The ‘LIKE’ operator in SQL is a logical operator that you can use in the WHERE clause to search for specific patterns in a column. This operator becomes particularly useful …

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SQL Count(), Avg(), Sum() – Unraveling SQL Aggregation Functions Count(), Avg(), Sum()

Let’s delve into the wonderful world of SQL (Structured Query Language), focusing on three pivotal functions: COUNT, AVG, and SUM. If you’re managing databases, these functions are crucial for data analysis and manipulation. But don’t worry if you’re a beginner; we’ll guide you through with easy-to-understand examples and sample data. Before we begin, let’s set …

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SQL MIN and MAX Functions – Unleashing Your Data’s Extremes

Let’s dive into the world of SQL (Structured Query Language) to explore two incredibly valuable aggregate functions: MIN() and MAX(). These functions allow you to discover the smallest and largest values in a particular column of your data set, respectively. Understanding and properly leveraging these functions can be a game-changer when dealing with massive datasets …

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SQL SELECT TOP – Diving Deep into the ‘SELECT TOP’ Clause

SELECT TOP is an essential clause for developers and database administrators, allowing for the efficient and strategic handling of voluminous data. Understanding SELECT TOP The SELECT TOP clause is a SQL command used to limit the number of rows returned from a query. This is particularly useful when you’re dealing with large databases, and you …

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SQL Null Values – Understanding SQL Null Values with Detailed Examples

Let’s explore an important, yet often misunderstood concept in SQL: NULL values. We’ll also include hands-on examples with a sample dataset. What is Null in SQL? NULL in SQL represents missing or unknown values. It is not zero, not an empty string, or not any other default value. It’s simply a representation of ‘no data’. …

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SQL INSERT INTO – A Comprehensive Guide to master SQL INSERT INTO Statement

In the realm of SQL, learning how to insert data into tables is a fundamental skill for anyone aspiring to manipulate databases effectively. The SQL INSERT INTO statement is the command you need for this task, allowing you to add new rows of data into a table. Let’s delve deeper into this key statement with …

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SQL AND, OR, and NOT

SQL AND, OR, and NOT – A Deep Dive into the AND, OR, and NOT Operators

The logical operators AND, OR, and NOT are the most fundamental tools in our SQL toolkit. Operators AND, OR, and NOT are incredibly useful in refining our queries to extract the precise information you need from our databases. Without further ado, let’s dive right into it. SQL Logical Operators SQL logical operators offer a way …

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SQL Select Distinct

SQL Select Distinct – A Comprehensive Guide

Let’s delve deep into one of SQL’s fundamental operations – the ‘Select Distinct’ statement. Defining SQL Select Distinct In SQL, the SELECT DISTINCT statement is used to return only distinct (different) values. It comes in handy when dealing with large databases where data duplications are common. The primary function of the SELECT DISTINCT statement is …

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SQL Select

SQL Select Statement – An Essential Guide to the SQL Select Statement

SQL SELECTstatement is a crucial starting point. Let’s dive into this fundamental command that brings data out of the shadows and into your view. SQL Select Statement: What Is It? The SELECT statement is used to select data from a database. The results are returned as a table of data called a result set. It’s …

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PySpark Exercises – 101 PySpark Exercises for Data Analysis

101 PySpark exercises are designed to challenge your logical muscle and to help internalize data manipulation with python’s favorite package for data analysis. The questions are of 3 levels of difficulties with L1 being the easiest to L3 being the hardest. You might also like to practice the 101 Pandas Exercises for Data Analysis, they …

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PySpark OneHot Encoding – Mastering OneHot Encoding in PySpark and Unleash the Power of Categorical Data in Machine Learning

Let’s dive deep into OneHot Encoding in PySpark, exploring its benefits in machine learning and walking you through practical example with code. As machine learning continues to gain traction in the world of data science, the need for efficient data preprocessing has never been more crucial. One such preprocessing technique is OneHot Encoding, which allows …

PySpark OneHot Encoding – Mastering OneHot Encoding in PySpark and Unleash the Power of Categorical Data in Machine Learning Read More »

PySpark StringIndexer

PySpark StringIndexer – A Comprehensive Guide to master PySpark StringIndexer

Deep understanding of PySpark’s StringIndexe, how it works, and how to effectively use it in your PySpark workflow Machine learning practitioners often encounter categorical data that needs to be transformed into a numerical format. We will delve into PySpark’s StringIndexer, an essential feature that converts categorical string columns into numerical indices. This guide will provide …

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PySpark Outlier Detection and Treatment

PySpark Outlier Detection and Treatment – A Comprehensive Guide How to handle Outlier in PySpark

Let’s dive deep into how to identify and treat outliers in PySpark, a popular open-source, distributed computing system that provides a fast and general-purpose cluster-computing framework for big data processing. Outliers are unusual data points that do not follow the general trend of a dataset. They can heavily influence the results of data analysis, predictive …

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PySpark Missing Data Imputation

PySpark Missing Data Imputation – How to handle missing values in PySpark

Handling missing data is an essential step in the data preprocessing pipeline. let’s explore various methods to impute missing values in PySpark, a popular distributed data processing framework. We will discuss different techniques, such as mean, median, mode imputation, and using machine learning algorithms to fill in missing values. By the end of this post, …

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PySpark Variable type Identification

PySpark Variable type Identification – A Comprehensive Guide to Identifying Discrete, Categorical, and Continuous Variables in Data

Let’s Explore what are discrete, categorical, and continuous variables, their identification techniques, and their importance in machine learning and statistical modeling. Data preprocessing is a critical step in machine learning and statistical modeling. Before diving into model building, it is essential to understand and identify the types of variables present in the dataset. Furthermore, I …

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Machine Learning A-Z™: Hands-On Python & R In Data Science

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Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science