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Data Science - Wintersemester 24/25
  • Welcome
  • What’s Data Science and How Do I Do It?
    • 📆Timeline
    • 🏴‍☠️R Overview
      • 📩Installation
      • 🐈‍⬛GitHub Setup
      • 🥗DataCamp Courses
    • 🐍Python Overview
      • 📩Installation
      • 🐈‍⬛GitHub Setup
      • 📦Virtual Environment Setup
      • 🥗DataCamp Courses
  • Introduction to Your Project
    • About the Project Guide
    • What is this Project About?
  • Exploratory Data Analysis (EDA)
    • Getting started
    • Discovering the Data 🔎
      • Initial Exploration Tasks
      • Initial Data Visualization
    • Data Cleaning and Transformation
      • Cleaning the Crime Dataset👮🏼
      • Cleaning the Weather Dataset🌦️
    • 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!
  • ✅Exercise Checklist
  • Legal Disclaimer
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  1. Exploratory Data Analysis (EDA)
  2. Data Cleaning and Transformation

Cleaning the Weather Dataset🌦️

PreviousCleaning the Crime Dataset👮🏼NextData Visualization

Last updated 5 months ago

Now, examine your weather dataset to ensure that each variable is in the correct format (e.g., dates as dates, numeric values as numerics, etc.).

After having cleaned up the crime dataset, this step should be straightforward!

🏴‍☠️: If you're unsure how to do this in R, as in the previous task, try using the as.Date() function to convert the date column to the correct format.

: No tips here, you can do this!

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