Univariate vs Multivariate EDA for Data Analysis

🚀 AI/ML Journey – Day 1: Python Basics Started my AI/ML journey with the foundation — Python fundamentals🐍 🔹 Learned about: * Variables & data types (int, float, string, boolean) * Type checking using `type()` * Formatted output with f-strings * Taking user input & type conversion * Basic string operations 💡 Built a simple interactive program that: * Takes user input * Performs calculations * Displays formatted results This is a small step, but a strong foundation for Data Science & Machine Learning. 📂 GitHub Repo: [https://lnkd.in/gVkC_zCU) 🔥 Up next: Day 2 → Operators & Control Flow #AI #MachineLearning #Python #DataScience #LearningJourney #Freshers #OpenToWork #GitHub #100DaysOfCode

📊 Top 5 Matplotlib Codes Every Data Scientist Should Know Data is powerful—but visualization makes it meaningful With Matplotlib, you can transform raw data into clear, insightful visuals that help in better decision-making. 📌 What you’ll learn: • Line plots for trends • Bar charts for comparisons • Histograms for distributions • Scatter plots for relationships • Pie charts for proportions 💡 Strong visualization skills can set you apart in Data Science—because insights matter more than just numbers. Don’t just analyze data… tell a story with it. #DataScience #Python #Matplotlib #DataVisualization #MachineLearning #Analytics #Coding #LearnToCode #careergrowth #tech #linkedin #fresher

Just solved a Python coding challenge on checking whether two strings are almost equivalent by comparing character frequency differences. #Python #CodingChallenge #LeetCode #ProblemSolving #DataStructures #Algorithms #Programming #Developer #SoftwareEngineering #Code #100DaysOfCode #Tech #Coding #LearnToCode #DevelopersLife #CareerGrowth #InterviewPrep #TechCareers #DataStructuresAndAlgorithms #CodingLife #PythonDeveloper #SoftwareDeveloper #CodingJourney #Programmer #TechSkills #Upskilling #Reskilling #JobReady #TechCommunity #Developers #CodeNewbie #WomenInTech #AI #MachineLearning #DataScience #Analytics #BigData #CloudComputing #AWS #PowerBI #SQL #Excel #Automation #DigitalSkills #Innovation #FutureOfWork #ContinuousLearning #GrowthMindset #TechIndia #Freshers

Every dataset has a story — and I’m learning how to tell it better every day. From working with Python 🐍 and SQL 🗄️ to building insightful dashboards 📊, my journey into data analytics is getting more exciting with each step. 💡 What I’m focusing on right now: • Writing efficient SQL queries • Data cleaning with Pandas • Creating meaningful visualizations • Building real-world projects The goal isn’t just to analyze data, but to uncover insights that drive smart decisions. 📈 Consistency > Perfection If you're also on a data journey, let’s connect and grow together! #DataAnalytics #Python #SQL #LearningJourney #CareerGrowth #DataScience #Freshers

Hello Linkedin Family, 👋 I worked on an Employee Data Analysis project using Python and pandas, where I focused on data cleaning, preprocessing, and extracting meaningful insights. 🔍 Key Highlights: >Handled missing values using median imputation >Cleaned and filtered invalid data >Analyzed trends across departments and cities >Identified hiring trends over the years >Examined workforce distribution 📊 Tools Used: Python, Pandas This project helped me strengthen my understanding of data cleaning and exploratory data analysis (EDA). Looking forward to building more projects and growing in the field of data analytics 🚀 #DataAnalytics #Python #Pandas #LearningJourney #Freshers #EDA Github Link - https://lnkd.in/g8NzFQYe

Day 2 of my Generative AI learning journey 🚀 To build a strong foundation in AI, I started learning Python — and today I explored some core basics. 🔹 What I learned today: Variables in Python Data types (int, float, string, etc.) Working with strings Taking user input Typecasting (converting one data type to another) 💡 Example: I created a small program that takes user input and converts it into different data types to understand how Python handles data. 💡 Insight: Understanding how data works is the first step toward building real AI applications. 🔜 Next: Learning operators and functions in Python. #GenerativeAI #Python #LearningInPublic #AI #CareerGrowth #Freshers #OpenToWork

Most data analysts check what’s present… . . Very few check what’s missing. And that’s where real insights hide “Find missing dates in a dataset using Pandas.” This is a real-world problem 👇 import pandas as pd # convert to datetime df['sale_date'] = pd.to_datetime(df['sale_date']) # create full date range full_dates = pd.date_range( start=df['sale_date'].min(), end=df['sale_date'].max() ) # find missing dates missing_dates = full_dates.difference(df['sale_date']) print(missing_dates) How it works -- Create complete date range -- Compare with existing dates -- Extract missing ones -- Simple but powerful Why this matters Used for: -- Data quality checks -- Missing transaction detection -- Debugging pipelines Interview Tip “I generate a full date range and compare it with existing data to identify gaps.” Most people analyze data… Top analysts question what’s not there. Save this before your next interview #Python #Pandas #DataAnalytics #InterviewPreparation #DataScience #LearnPython #Freshers #TechCareers

🐍 Why is Python the Most Recommended Language for Beginners? Because Python is: ✅ Easy to Learn ✅ Beginner Friendly ✅ Powerful ✅ Used in AI, Data Science, Web Development & Automation 📌 Companies use Python for: 🔹 Data Analytics 🔹 AI & Machine Learning 🔹 Backend Development 🔹 Automation Scripts 🔹 Cloud Applications 💡 Even many freshers get their first tech job by learning: Python + SQL + Projects 🚀 Start small. Stay consistent. Success follows consistency. What are you learning currently? 👇 #Python #Programming #Coding #TechSkills #LearningJourney #OneQuestion-Ai

Understanding Data Cleaning in Data Analytics Today I worked on one important step in data analytics — Data Cleaning. Before analyzing any dataset, cleaning is very important because raw data contains: ❌ Missing values ❌ Duplicate data ❌ Incorrect formats 🔧 Tools I explored: - Excel (Removing duplicates, filtering) - Python (Pandas basics) 📊 Example: Clean data → Better insights → Better decisions 💡 Key takeaway: "Garbage in = Garbage out" — clean data is the foundation of good analysis. I’m currently improving my Data Analytics skills step by step. #DataAnalytics #Python #Excel #LearningJourney #Freshers #TechSkills

🚀 Day 1/25 – Python Interview Questions Series Today’s Questions 👇 💡 Q1: What is Python? Python is a high-level, interpreted programming language known for: ✔ Easy syntax ✔ Dynamic typing ✔ Huge standard library ✔ Platform independent ✔ Supports multiple paradigms (OOP, functional) 💡 Q2: Difference between List and Tuple? 📌 List: ✔ Mutable (can change) ✔ Uses [] ✔ Higher memory 📌 Tuple: ✔ Immutable (cannot change) ✔ Uses () ✔ Faster & efficient 🎯 Interview Tip: Use tuple when data should not change → improves performance 📅 I’ll be posting 2 questions daily  Follow for complete Python interview preparation 🚀 #Python #InterviewPreparation #Coding #AIML #Freshers #LearnPython #JobReady