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Seaborn with Python
8 students

Seaborn with Python

Learn how to use seaborn library for data visualization in python
Created byDATAhill Solutions Srinivas Reddy
Last updated 1/2020
English

What you'll learn

  • Learn to use Seaborn for statistical plots
  • Seaborn Plotting Functions
  • Plotting with Categorical Data
  • Multi-Plot Grids
  • Plot Aesthetics
  • Use Plotly for interactive dynamic visualizations
  • Statistical Skills

Course content

1 section • 14 lectures • 2h 59m total length

  • Session 1. Seaborn Plotting Functions0:56

    Explore Seaborn plotting functions and learn to visualize data with categorical data and multiple plot grids using Seaborn’s graphical representations for basic statistical analysis.

  • Seaborn Plotting Functions30:49

    Unlock seaborn plotting functions in Python to visualize data distributions and relationships, using built-in datasets like iris and tips, with scatter, line, and 3D plots and subplots.

  • Session 2. Plotting with Categorical Data0:42

    Install and import seaborn in Python to begin plotting with categorical data. Learn to visualize data distributions and perform basic statistical analysis using seaborn's categorical plots.

  • Plotting with Categorical Data15:40

    Explore seaborn plotting functions to visualize statistical relationships between variables, including scatter plots and line plots, with emphasis on categorical data, data distribution, and iris dataset examples.

  • Session 3. Multi-Plot Grids0:24

    Build and arrange a structure of multiple plot grids in seaborn with Python, using custom functions to explore and manage data relationships.

  • Multi-Plot Grids33:55

    Explore seaborn multi-plot grids by importing packages, loading datasets, and building relational and scatter plots to compare car features such as price, mileage, model, and transmission.

  • Session 4. Plot Aesthetics0:28

    Explore Seaborn's plot aesthetics by applying figure styles, removing axis spines, adjusting temporary settings, overriding style elements, and selecting color patterns.

  • Plot Aesthetics17:38

    Master seaborn with Python to visualize numerical and categorical data using scatter plots, line plots, and diverse plot aesthetics with color and multiple plots.

  • Session 5. Data Visualization using Pandas0:45

    Learn data visualization in pandas by using library functions to create visuals such as bar charts and box plots, and inspect the functions and models available in these libraries.

  • Data Visualization using Pandas19:33
  • Data Science1:43

    Explore the foundations of data science, the data scientist role, and real-time data workflows. Learn to analyze and visualize data with Python, data mining, and statistics.

  • What is Data Science30:42

    Explore what data science is—its roots in statistics, artificial intelligence, and machine learning—and the end-to-end process from data collection to modeling and visualization.

  • Machine Learning1:27

    Contrast traditional programming with machine learning, and outline how statistics, data collection, processing, deployment, and reporting underpin the main types of machine learning.

  • What is Machine Learning25:06

    Explore how machine learning differs from traditional programming, learns like humans, and relies on data science and statistics to develop and evaluate models.

Requirements

  • Some programming experience
  • No Programming Skills Needed

Description

Are you ready to embark on your journey to becoming a Data Scientist?

This comprehensive course will be your ultimate guide to mastering the power of Python for data analysis, creating stunning visualizations, and implementing powerful machine-learning algorithms. Whether you’re a beginner with some programming experience or an experienced developer looking to transition into Data Science, this course is designed to cater to your needs.

Data Science has been consistently ranked as one of the top jobs, with Glassdoor naming it the number one job, and Indeed reporting an average salary of over $120,000 for Data Scientists in the United States. It's a rewarding career that not only offers lucrative financial prospects but also the opportunity to solve some of the world's most intriguing and complex problems.

Our course is structured to provide you with a strong foundation and progressively build your skills. Here’s what you can expect:

  1. Seaborn Plotting Functions: Learn how to use Seaborn, a powerful Python visualization library, to create a variety of plots. This module will introduce you to the essential plotting functions that will help you visualize data effectively.

  2. Plotting with Categorical Data: Understand how to handle and visualize categorical data. This section will teach you techniques to create insightful plots that reveal patterns and relationships within your data.

  3. Multi-Plot Grids: Discover how to create complex visualizations by combining multiple plots. Learn to use multi-plot grids to display data more comprehensively and organized, allowing for deeper insights.

  4. Plot Aesthetics: Enhance the appearance of your plots by mastering plot aesthetics. This module will guide you through customizing the look and feel of your visualizations to make them more appealing and easier to understand.

By the end of this course, you will have developed the skills to analyze data, create professional-quality visualizations, and apply machine-learning algorithms to solve real-world problems. Join us and take the first step towards a fulfilling and exciting career in Data Science.

Who this course is for:

  • Beginner Python developers curious about Data Science
  • Beginner to advanced level

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