📊 Exploratory Data Analysis (EDA) in R 💡 | Visualize, Summarize🔍

Описание: 📊 Exploratory Data Analysis (EDA) – Master the First Step in Data Science!

Welcome to this complete guide on EDA (Exploratory Data Analysis) – an essential part of Data Analytics and Data Science. In this video, you’ll learn how to analyze, visualize, and understand your dataset before applying any machine learning algorithm.

Whether you're working in R or Python, this video explains everything you need to know to get started with cleaning, summarizing, and visualizing data effectively.

🧠 Topics Covered: ✅ What is EDA?
✅ Importance of EDA in Data Science
✅ Univariate, Bivariate & Multivariate Analysis
✅ Summary Statistics (mean, median, mode, std)
✅ Data Distribution (histograms, boxplots, KDE)
✅ Handling Outliers & Missing Values
✅ Correlation & Pairplots
✅ Visualizations using matplotlib, seaborn, ggplot2

💻 Tools Used:

Python (Pandas, Seaborn, Matplotlib)

R (dplyr, ggplot2, summary stats)

📁 Dataset: Sample sales dataset (CSV)

📚 This video is a part of Data Analytics Playlist (Chapter 5)
🎥 Playlist Link:    • Data Analytics Chapter 5 playlist: Framewo...  


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🚀 Why EDA is Important? EDA helps you detect:

Anomalies & Outliers

Data Distribution

Relationships & Trends

Data Quality Issues

👉 Without EDA, your machine learning models might fail!

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