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Data Science - Wintersemester 24/25
  • Welcome
  • Whatโ€™s Data Science and How Do I Do It?
    • ๐Ÿ“†Timeline
    • ๐Ÿดโ€โ˜ ๏ธR Overview
      • ๐Ÿ“ฉInstallation
      • ๐Ÿˆโ€โฌ›GitHub Setup
      • ๐Ÿฅ—DataCamp Courses
    • ๐ŸPython Overview
      • ๐Ÿ“ฉInstallation
      • ๐Ÿˆโ€โฌ›GitHub Setup
      • ๐Ÿ“ฆVirtual Environment Setup
      • ๐Ÿฅ—DataCamp Courses
  • Introduction to Your Project
    • About the Project Guide
    • What is this Project About?
  • Exploratory Data Analysis (EDA)
    • Getting started
    • Discovering the Data ๐Ÿ”Ž
      • Initial Exploration Tasks
      • Initial Data Visualization
    • Data Cleaning and Transformation
      • Cleaning the Crime Dataset๐Ÿ‘ฎ๐Ÿผ
      • Cleaning the Weather Dataset๐ŸŒฆ๏ธ
    • Data Visualization
      • Crime Rate Over Time
      • Crime Types
    • Grouping and Merging Data
    • Linear Regression
    • Impress us!
    • Internship Complete!
  • Advanced
    • Introduction
    • K-Means Clustering
      • The Clustering Model
      • Visualize the clusters
    • Impress us!
  • โœ…Exercise Checklist
  • Legal Disclaimer
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  1. Exploratory Data Analysis (EDA)

Discovering the Data ๐Ÿ”Ž

Before diving into any analysis, it's crucial to take a closer look at the data itself. Exploring the dataset in detail helps you understand its structure, identify key variables, and spot any potential issues like missing values or incorrect data types. By doing this first, you'll have a clear understanding of what you're working with, which will make your analysis smoother and more accurate. Think of this step as setting the stage for everything that followsโ€”getting familiar with the data now will save you time and effort later!

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Last updated 6 months ago