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Connect with us on Social Media! 📸 Instagram: https://www.instagram.com/algorithm_a... 🧵 Threads: https://www.threads.net/@algorithm_av... 📘 Facebook: / algorithmavenue7 🎮 Discord: / discord 👉 Timestamps: 00:00 –What is univariate analysis? 01:42 – Numerical and categorical columns 07:49 – Count plot 10:54 – Pie chart 12:08 – Histogram 19:36 – Dist plot 24:28 – Box plot LINK:https://colab.research.google.com/dri... Dataset link:https://www.kaggle.com/datasets/alexh... In this video, we explore Univariate Analysis, an important step in Exploratory Data Analysis (EDA) where we analyze one variable at a time to understand its distribution, pattern, and behavior. I explain each plot visually and intuitively, making it easy for beginners to understand how data behaves before applying any machine learning models. 🔍 Topics Covered in This Video: ✔ What is EDA and why it is important ✔ What is Univariate Analysis ✔ Understanding data distribution using visualizations ✔ Identifying skewness, spread, and outliers 📈 Plots Explained in This Video: ✅ Histogram – Understand data distribution ✅ Distplot – Smooth distribution using KDE ✅ Count Plot – Frequency of categorical variables ✅ Box Plot – Detect outliers and percentiles ✅ Pie Chart – Percentage contribution of categories Each plot is explained with real examples so you can easily apply them in your own projects. 👉 If you found this useful, don’t forget to Like , Share , and Subscribe for more awesome content! #eda #univariateanalysis #exploratorydataanalysis #datavisualization #datascience #machinelearning #python #pythoneda #seaborn #matplotlib #histogram #boxplot #countplot #distplot #piechart #statisticalanalysis #dataanalytics #dataanalysis #beginnerdatascience #datasciencetutorial #mlbeginners #pythonvisualization #datapreprocessing #featureanalysis #outlierdetection #datainsights #learnpython #dsprojects #edatutorial