๐Ÿ”ฅ
Exploratory Data Analysis (EDA)
WebsiteGithub
  • ๐Ÿ‘‹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
    • โ„น๏ธKaggle
  • Tools and Software
    • โœจData Analysis Tools
    • ๐ŸPython Library
      • ๐ŸผPandas
      • ๐ŸงŠNumpy
      • ๐Ÿ“ŠMatplotlib
      • ๐Ÿ“ˆSeaborn
      • ๐Ÿ“ถPlotly
      • ๐ŸคนSciPy
      • ๐Ÿ’ซStatsmodels
      • ๐Ÿ‘‚Scikit-learn
      • ๐Ÿ—ณ๏ธYellowbrick
    • โ›๏ธPython tools
    • ยฎ๏ธยฎ ยฎ ยฎ The R Project
    • ๐ŸŒ€Data Exploration
    • ๐ŸŽฏData Quality
    • ๐Ÿ“”Data Profiling
    • ๐Ÿ“บVisualization
  • Tech Exploration
    • ๐ŸŽฌYoutube
    • โ˜๏ธGithub
    • ๐Ÿ”ฌLab
    • ๐Ÿ’ผCase Study
  • Reference
    • API Reference
      • Pets
      • Users
      • Quick Start
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Plotly

An interactive data visualization library

PreviousSeabornNextSciPy

Last updated 1 year ago

๐Ÿ”— |

is an interactive, open-source, and browser-based graphing library for Python

Built on top of , plotly.py is a high-level, declarative charting library. plotly.js ships with over 30 chart types, including scientific charts, 3D graphs, statistical charts, SVG maps, financial charts, and more.

plotly.py is . Plotly graphs can be viewed in Jupyter notebooks, standalone HTML files, or integrated into .

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plotly.py
plotly.js
MIT Licensed
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