SanjAy R.’s Post

In R programming, understanding the scope of variables — global vs. local — is crucial for managing data and avoiding errors in your code. Here’s a quick breakdown: 🌐 Global Variables - Accessible from anywhere in your R script. - Defined in the main body of the script, outside of any functions. - Useful for values that need to be shared across multiple functions. 🔍 Local Variables - Exist only within the function they are defined in. - Not accessible outside their function, making your code more modular and less prone to errors due to variable name conflicts. - Automatically deleted once the function call is complete, which helps in managing memory efficiently. Understanding these differences helps in writing clearer, more efficient R code, and aids in debugging by limiting the scope of variables where necessary. I've created a tutorial explaining the difference between global and local variables in R. More details are available at this link: https://lnkd.in/evM5xcz #database #bigdata #analytics #rstudio #statisticians

https://lnkd.in/gXTpcj6U Takes you on a guided tour of software development with #R, from basic types and data structures to advanced topics like #closures, #recursion, and anonymous #functions. #rprogramming #statistics #datastructures #dataanalysis #datavisulization #datascience

Need assistance with Data Processing , Open-End Coding, SP and Analytics? Our in-house team of experts is here to help! Send your requirements to [email protected] or inbox #technology #management #dataprocessing #survey #506 #programming #openendcoding #analytics #srk #data #market #maketresearch #surveyprogramming #research #waqt #jbb #quality

What is the ARRAY_CONTAINS() Function in SQL and Why You Should Use It ? 🚀 The ARRAY_CONTAINS() function checks if a specific element is present within an array. It returns TRUE if the element exists and FALSE otherwise. This is especially useful when filtering data or searching for specific attributes within complex datasets. Why Use ARRAY_CONTAINS()? - Easily filter rows based on whether a particular value exists within an array. - Validates that essential values are present in arrays, ensuring cleaner and more reliable data. - Offers a straightforward way to query and search through arrays without complicated loops or procedures. #SQL #DataEngineering #BigData #DataManagement #TechTips #DataTransformation #ApacheSpark #Databricks #ETL #Programming #DataFiltering #ArrayOperations

Today, I dived into basic R programming concepts and learned a lot! 💻 💡 Topics Covered: - Vectors, Lists, and Variables - Data Types, Data Frames, and Matrices - Logical Operators for decision-making - Pipes (%>%) to streamline code Excited about how R makes data manipulation so smooth. Looking forward to applying these skills in real-world data projects! 🎯 #RProgramming #DataAnalysis #LearningJourney #DataScience #Analytics #ProgrammingSkills

Check out this certificate I got for R Programming : Data Analysis and Visualisations using R https://lnkd.in/gG5jGK-M

Data Structures in Programming: Essential Building Blocks 1. Arrays: A fixed-size collection of elements, useful for storing data in a linear order and great for indexed access. 2. Linked Lists: Elements linked via pointers, allowing efficient insertion/deletion, ideal for dynamic data handling. 3. Stacks: Follows the Last In, First Out (LIFO) principle, often used for managing function calls or undo operations. 4. Queues: Follows the First In, First Out (FIFO) principle, making it suitable for task scheduling or data streaming. 5. Trees: Hierarchical structures, excellent for representing data with parent-child relationships, like file systems. 6. Graphs: Nodes connected by edges, perfect for mapping networks like social connections or transport routes. 7. Hash Tables: Key-value pair storage, allowing fast data retrieval, commonly used in database indexing. Choosing the right data structure optimizes performance, enhances data handling, and simplifies code. #DataStructures #Programming #CodingLife #DeveloperJourney #TechSkills #SoftwareEngineering #CodeNewbie #interviewcafe #LearningToCode #Algorithm #TechStack #ProgrammingBasics #CodingCommunity #EfficientCoding

#3/365 Challenge Hey tech Community! Today Topic is Arrays "Arrays are Essential for Every Programmer!" ->Arrays are the fundamental data stractures in programming, used to store and manipulate collections of data. ->whether yo're a seasoned developer or just starting ou ,understanding array is crucial for success. ->To store the large volume of data efficiently we have to make use of arrays. How to create an Array 1.int arr[ ] =new int[ size ]; 2.int[ ] arr=new int[ size ]; 3.creating an array by defining elements of the array : int arr[ ] ={10, 20,30 }; Here are some key points of Array ->indexing: Accessing elements via indices(0 -based) ->length: Getting the number of elements (myArray.length) ->Operations : Sorting,Searching,Inserting,deleting Arraysare used in: ->Data storage and processing ->Algorithm design. ->Web development (eg.handling from web data) Drawbacks of Array 1.Arrays can store only homogeneous data that means data of same type. 2.It's size is static that means it's size remains fixed throught the entire execution of the program. 3.It expects contiguous memory allocations it cannot utilize the scattered memory available on the ram. Share your favourite array-related tips or resources in the comments! Let's master arrays and take out programming skills to the next level! #Arrays #Programming_fundamentals #DataStracutres #Code_like_A_PRo

--- CAN YOU SOLVE THIS - EXCEL CHALLENGE 472 --- -Daily Challenges @ 4am UTC | Excel: Mon to Fri | Power Query: Sat & Sun- (Solutions in any language are also welcome for Excel Challenges) All rows carry one mathematical operator (to simplify only 4 basic maths operators which are +, -, * and / ). Concat all cells to the left of operator and perform mathematical operation on concatenation of all cells to the right of operator. Ex. Row 2 - Left of operator concatenation: 1354 Right of operator concatenation: 15205 Mathematical operation for + = 1354 + 15205 = 16559 Row 3 = 191031019/9 = 21225668.78 Download Practice File - https://lnkd.in/dgvFc7Yz List of all Challenges posted so far with Challenge Links and Practice File Links https://lnkd.in/de5NybY7 All Challenge files in one place - https://lnkd.in/dmu5EHEv (Post answers in Comment. Your approach need not be different from others as long as you have worked out your approach independently) #excel, #challenge, #problem, #excelchallenge, #powerquerychallenge, #daxchallenge, #m, #dax, #powerbi, #powerquery, #powerpivot, #sheets, #googlesheets, #data, #analytics, #businessintelligence, #finance, #office365, #python, #r

Are you still stuck in the SQL world for data cleaning and manipulation? It's time to level up your game with R programming! By using R, you can streamline your data cleaning and manipulation processes, saving you time and effort. With its powerful packages like dplyr and tidyr, you can easily filter, sort, and reshape your data with just a few lines of code. Say goodbye to cumbersome SQL queries and hello to the flexibility and efficiency of R programming. Make the switch today and see the difference for yourself! 💪🔥 #RProgramming #DataManipulation #Efficiency #PowerOfR