Pandas Data Manipulation with Python

Day 37 at Luminar Technolab Started with Pandas working with Series and DataFrames. Learned how to create, access, and manipulate data, along with basic indexing using iloc. Stepping into data analysis and EDA. #Python #Pandas #DataAnalysis #LearningJourney #Consistency

🔁 Exploring Sorting Algorithms in Python Today I practiced two fundamental sorting techniques: ✅ Bubble Sort ✅ Selection Sort 💡 Key Learnings: * Bubble Sort repeatedly swaps adjacent elements to push larger elements to the end * Selection Sort selects the minimum element and places it in the correct position * Understanding time complexity becomes clearer when you count operations manually #Python #DataStructures #Algorithms #CodingJourney #100DaysOfCode #LearningInPublic

Day 24/100 – DSA Journey Problem: Intersection of Two Arrays Initially thought of using loops, but that would increase time complexity. Then realized the problem requires only unique common elements, which makes sets a perfect fit. Converted both arrays into sets and used intersection to directly get the result in an efficient way. Key Learning: Choosing the right data structure can simplify the entire problem. #Day24 #100DaysOfCode #DSA #Python #LeetCode #ProblemSolving

Task 3(Intermediate Level): Clustering Analysis (K Means) Description: Implement K-Means clustering to group similar data points together based on feature similarities. Tools: Python, scikit-learn, matplotlib, seaborn I standardized the dataset (using StandardScaler). I applied K-Means clustering and determined the optimal number of clusters using the elbow method. I visualized the clusters using 2D scatter plots. #CodvedaAchievements #CodvedaProjects #CodvedaJourney #CodvedaExperience #FutureWithCodveda Codveda Technologies

Day 32 / #120DaysOfCode – LeetCode Challenge Today’s focus: Arrays & Majority Voting Algorithm ✅ Problem Solved: • Majority Element II 💻 Language: Python 📚 Key Learnings: • Applied Boyer-Moore Voting Algorithm (extended version) • Learned how to track two candidates for n/3 majority • Understood the importance of validation step after candidate selection • Improved ability to handle edge cases in frequency problems Consistency builds confidence 🚀 Every day = 1% better 💪 🔗 LeetCode Profile: https://lnkd.in/gbeMKcv5 #LeetCode #Python #DSA #Arrays #Algorithms #Consistency #CodingJourney #120DaysOfCode

Day 38 at Luminar Technolab Worked with Pandas DataFrame selection using iloc and explored different ways to access rows and columns. Getting more comfortable navigating structured data #Python #Pandas #DataAnalysis #LearningJourney

Day 43/100 – #100DaysOfCode 🚀 Solved LeetCode #2610 – Convert an Array Into a 2D Array With Conditions (Python). Today I practiced hashmap (frequency counting) to construct a 2D array based on given conditions. Approach: 1) Create a frequency map to count occurrences of each element. 2) Initialize an empty result list. 3) While the frequency map is not empty: 4)  Create a new row. 5)  Iterate through keys and add each number once to the row. 6)  Decrease its frequency and remove it if it becomes zero. 7) Add the row to the result. 8) Return the final 2D array. Time Complexity: O(n) Space Complexity: O(n) Learning how frequency maps help in structuring data efficiently 💪 #LeetCode #Python #DSA #HashMap #Arrays #ProblemSolving #100DaysOfCode

ops-code just hit 50 downloads on the VS Code marketplace—that is pretty cool! Version 0.1.0 introduces tools: users can create their own python scripts that will run automatically after analysis, consuming the fem-results and producing tabular output displayed in the viewer. See the demo at https://lnkd.in/euRXSNE2 #OpenSees #StructuralEngineering #VSCode #Python #AI #3DVisualization #CivilEngineering

🚀 Day 16: Insert & Delete Functions Today I learned how to modify arrays. 👉 insert(): add elements 👉 delete(): remove elements This helps in dynamic data manipulation. 💡 Key takeaway: Data can be updated easily in NumPy. #Python #NumPy #Coding

💧 Max Water Problem — Two Pointer Optimization Solved Container With Most Water using the Two Pointer technique in O(n) time. Key Idea: Move the pointer with the smaller height, since it limits the water capacity. 📈 Complexity: Time → O(n) Space → O(1) Small logic shift, big optimization. #DSA #Python #TwoPointers #CodingInterview #Algorithms