Seaborn Exercise and solution Tutorial

Seaborn Exercise and solution Tutorial(python crash course_10):

Want to learn Seaborn?
Hello friends, my previous blog post is all related about Seaborn. Today we will try for the Seaborn exercise and solution. before going to start we see some basic concept related to seaborn. Let's start:
Basic Introduction:
Seaborn is a library for making statistical graphic in Python. It's built on top of Matplotlib and closely integrated with pandas data structure.
Seaborn Exercise and solution Tutorial

Here is some of the functionality that seaborn offer:
  1. A dataset-oriented API for examining relationship between multiple variable
  2. Specialized support for using categorical variable to show observations or aggregate statistics
  3. Option for visualizing univariate or bivariate distributions and for comparing them between subsets of data
  4. Automatic estimation and plotting of linear regression models for different kind dependent variables.
  5. Convenient view onto the overall structure of complex dataset
  6. abstractions for structuring multi-plot grid that let you easily build complex visualization
  7. Concise control over matplotlib figures styling with several built-in themes.
  8. Tools for choosing color palette that faithfully reveal patterns in your data
 Seaborn aims to make visualizations a central part of exploring and understanding data.
 It's dataset-oriented plotting functions operate on dataframes and arrays containing whole dataset.
 internally perform the necessary semantic mapping and statistical aggregation to produce informative plot.

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