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[PyData Global 2021] Know Your Data First: An Introduction to Exploratory Data Analysis

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[PyData Global 2021] Know Your Data First: An Introduction to Exploratory Data Analysis

This is a hands-on tutorial that introduces comprehensive Exploratory Data Analysis (EDA) techniques to have better understandings about your data before doing serious tasks such as machine-learning or deep-learning.

Target Audience

  • Student who wants to be a data scientist
  • Junior data scientist
  • Machine-learning researcher

Prerequisite

Outline

  1. Introduction
  2. Data loading and preprocessing
    • Loading a csv file
    • Merging many csv files
    • Essential check: #Samples, Column Names, Unique Values, Missing Values, etc.
    • sidetable
    • Preprocessing & Feture Engineering
      • Handling missing values
      • Extracting features
  3. Statistical Visualizations
    • matplotlib: basic building block, essential for fine-tuning
    • pandas: data manipulation + plotting
    • seaborn: handy matplotlib wrapper for statistical visualizations
  4. (Easy Enough) Interactive Visualizations
    • ipywidgets
    • plot.ly and plot.ly express
    • bokeh
    • altair
  5. Automatic EDA Report
    • dtale
    • pandas-profiling
    • sweetviz
    • autoviz
  6. Wrap-up and Some Tips

Contact

Sin-seok SEO @Safran Tech, Safran SA

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[PyData Global 2021] Know Your Data First: An Introduction to Exploratory Data Analysis

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