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  • Mastering SQL Date Extraction and Monthly Trends Using LAG()

    Oct 14, 2025

    ·

    mysql, SQL
    Mastering SQL Date Extraction and Monthly Trends Using LAG()
  • DB2 Buffer Pools: A Comprehensive Look

    DB2 Buffer Pools are logical memory, used to speed up SQL queries, enhance database performance and control CPU resources usage. Read More ⇢

    DB2 Buffer Pools: A Comprehensive Look
  • Counting of String Elements: 2 Ways to Achieve in Python

    The post explains two Python methods to count string elements – using itertools and groupby, and for loops. Read More ⇢

    Counting of String Elements: 2 Ways to Achieve in Python
  • Python Strings: Program to Replace Second Occurrence with Input

    The content describes a Python example for finding and replacing specific elements in a string. Read More ⇢

    Python Strings: Program to Replace Second Occurrence with Input
  • Python List Reversal: Built-in and Custom Techniques Explained

    The content discusses two methods in Python for reversing lists: a custom-built function and the built-in reversed() method. Read More ⇢

    Python List Reversal: Built-in and Custom Techniques Explained
  • 2 Ways Converting List to String in Python

    Converting list to a string in Python is not hard. Here are two ways that you can use are for loop and join methods Read More ⇢

    2 Ways Converting List to String in Python
  • 2 Top SQL Queries to Update Table: Subquery and Join

    The content explains using update SQL query with tables EMP1 and EMP2 to update records in multiple tables concurrently. Read More ⇢

    2 Top SQL Queries to Update Table: Subquery and Join
  • Connecting Python to Oracle Database: 4 Neat Approaches

    Provides four methods (cx_Oracle, pyodbc, pyoracle, sqlalchemy) to establish Python to Oracle database connectivity, enabling data analysis. Read More ⇢

    Connecting Python to Oracle Database: 4 Neat Approaches
  • Python Interview Questions and Answers: Recently Asked in CGI

    The post discusses Python interview questions and answers for intermediate-level positions, covering topics like list comprehension, file handling and counting duplicates in Python, similarities and differences between Python and PySpark, parallel processing, and techniques to read large files in Pandas. Read More ⇢

    Python Interview Questions and Answers: Recently Asked in CGI
  • Exploring the Power of Vectorization in Numpy: A Comprehensive Guide

    NumPy’s vectorization allows efficient handling of complex calculations with large datasets in Python by eliminating traditional loops. Read More ⇢

    Exploring the Power of Vectorization in Numpy: A Comprehensive Guide
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