Cara menggunakan seaborn cheat sheet github

User guide and tutorial

  • An introduction to seaborn

API Overview

  • Overview of seaborn plotting functions

  • Data structures accepted by seaborn

Objects interface

  • The seaborn.objects interface

  • Properties of Mark objects

Plotting functions

  • Visualizing statistical relationships

  • Visualizing distributions of data

  • Visualizing categorical data

Statistical operations

  • Statistical estimation and error bars

  • Estimating regression fits

Multi-plot grids

  • Building structured multi-plot grids

Figure aesthetics

  • Controlling figure aesthetics

  • Choosing color palettes

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For learners who feel at ease when steps are visually explained, you may check my YouTube channel. You may opt reading for a written/article mode preview on my Medium publication. My algorithms shall try to ensure that these notebooks are well synchronized with video streaming but do not guarantee perfect Speech to Text.

Agenda:

With this series of Seaborn notebooks, aspirants shall achieve or be able to upgrade their skills on:

  • Learn to use Pandas to have a brief overview of dataset.
  • Learn to use various Seaborn plots.
  • Learn to infer the representation of data distribution on any plot.
  • Utilize underlying Matplotlib arguments to tweak Seaborn plots.
  • Statistical interpretation of plotted data.
  • In-depth usage & explanation of each available plotting parameter.
  • Advanced customization as to satisfy complex real-world business problems.
  • Custom codes for enhancing data visualization experience.

Series Curriculum:

  • Introduction to Data Visualization Fundamentals
  • Setting up Tools & Resources (Jupyter Notebook)
  • Overview of NumPy and Pandas
  • Elementary Statistical Terms : Part-1, Part-2 and Part-3.
  • Plot styling with Seaborn (With Tableau flavour)
  • Linearly spread Data Plots
  • Categorical Data Plots
  • Visualization on Grids

Please note that the content of each Curriculum topic might get segregated into multiple videos on YouTube OR multiple articles on Medium Publication so I would recommend opening it up as a playlist for better experience.

Note:

I could've made a Udemy course out of this and earned money but I believe in contributing to our open-source arena, so my only expectation from learners is for them to also contribute whichever way they can in due course of time. If there is any issue with the code or explanation that you would like me to look into or advice/suggest/recommend, please feel free to reach out. If the content is useful, a better idea would be to Star or Fork this repository for your future reference. If the content on publication seems well explained, I would really be glad to get notified about your applause on the story. - Alok Kumar

Edit: I am aware of the changes brought in with Seaborn v0.9 and shall add a Notebook in accordance very soon. Appreciate your time!