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Exploratory Data Analysis (EDA)
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      • EDA: Uncovering Insights and Patterns
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  1. Tools and Software
  2. Python Library

Seaborn

A library based on Matplotlib for creating visualizations with a higher-level interface

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Last updated 1 year ago

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Seaborn is a library for making statistical graphics in Python. It builds on top of matplotlib and integrates closely with pandas data structures.

Seaborn helps you explore and understand your data. Its plotting functions operate on dataframes and arrays containing whole datasets and internally perform the necessary semantic mapping and statistical aggregation to produce informative plots. Its dataset-oriented, declarative API lets you focus on what the different elements of your plots mean, rather than on the details of how to draw them.

Documentation

Online documentation is available at .

The docs include a , , , and other useful information.

Dependencies

Seaborn supports Python 3.7+ and no longer supports Python 2.

Installation requires , , and . Some functions will optionally use and/or if they are available.

Installation

The latest stable release (and required dependencies) can be installed from PyPI:

pip install seaborn

It is also possible to include the optional dependencies:

pip install seaborn[all]

You may instead want to use the development version from Github:

pip install git+https://github.com/mwaskom/seaborn.git

Seaborn is also available from Anaconda and can be installed with conda:

conda install seaborn

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