🔥
Exploratory Data Analysis (EDA)
WebsiteGithub
  • 👋Welcome!
  • Course Content
    • 1. Introduction
      • EDA: Uncovering Insights and Patterns
      • Why EDA?
      • Importance of EDA
      • The role of EDA in the data analysis process
      • A Comprehensive Examination
      • Code & Practice
      • Basic Concept
    • 2. Fundamentals
      • Lifecycle
        • Data Science
        • EDA
    • 3. Dataset Selection and Understanding
      • Kaggle
      • Github
    • 4. Data Cleaning and Preprocessing
    • 5. Techniques and Approaches
      • Types of EDA
    • 6. Data Visualization
    • 7. Statistical Measures and Hypothesis Testing
    • 9. Case Studies
    • 11. Best Practices and Tips for Effective EDA
    • 12. Future Trends and Emerging Technologies
  • Dataset
    • ℹ️Kaggle
  • Tools and Software
    • ✨Data Analysis Tools
    • 🐍Python Library
      • 🐼Pandas
      • 🧊Numpy
      • 📊Matplotlib
      • 📈Seaborn
      • 📶Plotly
      • 🤹SciPy
      • 💫Statsmodels
      • 👂Scikit-learn
      • 🗳️Yellowbrick
    • ⛏️Python tools
    • ®️® ® ® The R Project
    • 🌀Data Exploration
    • 🎯Data Quality
    • 📔Data Profiling
    • 📺Visualization
  • Tech Exploration
    • 🎬Youtube
    • ☁️Github
    • 🔬Lab
    • 💼Case Study
  • Reference
    • API Reference
      • Pets
      • Users
      • Quick Start
Powered by GitBook
On this page
  1. Course Content
  2. 1. Introduction

Basic Concept

PreviousCode & PracticeNext2. Fundamentals

Last updated 1 year ago

developers.google: Good Data Analysis
Datascience using Python: Exploratory_Data_Analysis
Towardsdatascience: What is Exploratory Data Analysis?
Wikipedia: Exploratory data analysis
r4ds: Exploratory Data Analysis
careerfoundry:What Is Exploratory Data Analysis?
How To Conduct Exploratory Data Analysis in 6 Steps
A Five-Step Guide for Conducting Exploratory Data Analysis
I asked ChatGPT to do Exploratory Data Analysis with Visualizations
Visitors