🤕 Outlier part 1 of 2 - Visualization

‪@FunCodingIndonesia‬ Visit, Try, Like, and Subscribe! In this coding session, we explore Outlier Detection in Data Science using Python. Using a house dataset, we analyze the bedrooms variable and visualize potential outliers using several statistical plots. In this tutorial, we cover: 🔹Loading a dataset with Pandas 🔹Understanding the concept of outliers 🔹Detecting outliers using the IQR (Interquartile Range) method 🔹Calculating Q1, Q3, and IQR 🔹Determining lower and upper outlier boundaries 🔹Visualizing data with Boxplot 🔹Using Violin Plot and Strip Plot 🔹Exploring data distribution with Histogram 🔹Combining multiple visualizations for outlier analysis A practical introduction to Outlier Detection, Data Visualization, IQR, and Exploratory Data Analysis (EDA) using Python, Pandas, Matplotlib, and Seaborn.