Seaborn Mastery: Comprehensive Data Visualization in Python
Seaborn Mastery: Comprehensive Data Visualization in Python, available at $44.99, has an average rating of 4.15, with 51 lectures, based on 38 reviews, and has 20155 subscribers.
You will learn about Introduction to Seaborn: Understand the basics of Seaborn, a powerful Python data visualization library. Scatter Plot and Line Plots: Learn how to create scatter plots and line plots to visualize relationships between variables. Categorical Scatterplots and Distributions: Explore different types of categorical scatterplots and distributions of observations within categories. Statistical Estimation and Countplot Examples: Dive into statistical estimation within categories and examples of countplot. Advanced Techniques: Discover intermediate and advanced techniques such as conditioning on other variables and fitting different kinds of models. Custom Functions and Pairwise Data Relationships: Use custom functions and plot pairwise data relationships with Seaborn. Case Study: Apply Seaborn to a real-world case study using Census dataset, performing exploratory data analysis and creating various visualizations. This course is ideal for individuals who are Python enthusiasts looking to enhance their data visualization skills using Seaborn. or Data analysts and scientists seeking to leverage Seaborn for exploring and presenting data insights effectively. or Students and professionals in fields like data science, statistics, and research who want to add Seaborn proficiency to their toolkit. or Anyone interested in learning advanced data visualization techniques in Python for insightful analysis and presentation of data. It is particularly useful for Python enthusiasts looking to enhance their data visualization skills using Seaborn. or Data analysts and scientists seeking to leverage Seaborn for exploring and presenting data insights effectively. or Students and professionals in fields like data science, statistics, and research who want to add Seaborn proficiency to their toolkit. or Anyone interested in learning advanced data visualization techniques in Python for insightful analysis and presentation of data.
Enroll now: Seaborn Mastery: Comprehensive Data Visualization in Python
Summary
Title: Seaborn Mastery: Comprehensive Data Visualization in Python
Price: $44.99
Average Rating: 4.15
Number of Lectures: 51
Number of Published Lectures: 51
Number of Curriculum Items: 51
Number of Published Curriculum Objects: 51
Original Price: $89.99
Quality Status: approved
Status: Live
What You Will Learn
- Introduction to Seaborn: Understand the basics of Seaborn, a powerful Python data visualization library.
- Scatter Plot and Line Plots: Learn how to create scatter plots and line plots to visualize relationships between variables.
- Categorical Scatterplots and Distributions: Explore different types of categorical scatterplots and distributions of observations within categories.
- Statistical Estimation and Countplot Examples: Dive into statistical estimation within categories and examples of countplot.
- Advanced Techniques: Discover intermediate and advanced techniques such as conditioning on other variables and fitting different kinds of models.
- Custom Functions and Pairwise Data Relationships: Use custom functions and plot pairwise data relationships with Seaborn.
- Case Study: Apply Seaborn to a real-world case study using Census dataset, performing exploratory data analysis and creating various visualizations.
Who Should Attend
- Python enthusiasts looking to enhance their data visualization skills using Seaborn.
- Data analysts and scientists seeking to leverage Seaborn for exploring and presenting data insights effectively.
- Students and professionals in fields like data science, statistics, and research who want to add Seaborn proficiency to their toolkit.
- Anyone interested in learning advanced data visualization techniques in Python for insightful analysis and presentation of data.
Target Audiences
- Python enthusiasts looking to enhance their data visualization skills using Seaborn.
- Data analysts and scientists seeking to leverage Seaborn for exploring and presenting data insights effectively.
- Students and professionals in fields like data science, statistics, and research who want to add Seaborn proficiency to their toolkit.
- Anyone interested in learning advanced data visualization techniques in Python for insightful analysis and presentation of data.
Welcome to the “Seaborn Python Mastery: From Beginner to Advanced” course! Seaborn is a powerful Python library for creating informative and visually appealing statistical graphics. Whether you’re a beginner or an experienced data scientist, this course will take you on a comprehensive journey through Seaborn, starting from the basics and gradually progressing to advanced topics.
Throughout this course, you will learn how to leverage Seaborn to visualize data distributions, relationships, and patterns effectively. From simple scatter plots to complex conditional small multiples, you will master a wide range of visualization techniques to extract meaningful insights from your data.
With hands-on exercises and real-world case studies, you’ll gain practical experience in applying Seaborn to real-world data analysis tasks. By the end of the course, you’ll be equipped with the skills and knowledge to create stunning visualizations that communicate your data insights effectively.
Join us on this exciting journey and unlock the full potential of Seaborn for your data visualization needs!
Section 1: Seaborn Python – Beginners
In this introductory section, students will familiarize themselves with Seaborn, a Python library built on top of Matplotlib that facilitates the creation of informative and visually appealing statistical graphics. They will start by understanding the fundamental concepts of Seaborn and its advantages over other visualization libraries. The lectures will cover essential plot types such as scatter plots, line plots, and categorical scatterplots. Students will learn how to create these plots using Seaborn and gain insights into their interpretation and usage in data analysis tasks. Additionally, they will explore more advanced visualization techniques like box plots, violin plots, and bar plots, enabling them to effectively represent data distributions and relationships.
Section 2: Seaborn Python – Intermediate
Building upon the foundational knowledge from the beginner section, students will delve deeper into Seaborn’s capabilities in the intermediate section. They will learn how to visualize univariate and bivariate distributions using functions like DISTPLOT and JOINTPLOT. Additionally, students will explore the use of regression plots to understand the relationships between variables and how to customize them using different parameters. The lectures will also cover advanced topics such as conditional small multiples, where students will learn to create multiple plots based on different conditions, providing deeper insights into the data.
Section 3: Seaborn Python – Advanced
In the advanced section, students will further enhance their proficiency in Seaborn by mastering more complex visualization techniques. They will learn how to use custom functions to create specialized plots and effectively visualize pairwise relationships between variables. The lectures will also cover advanced styling options such as setting different color palettes and themes to enhance the aesthetic appeal of the visualizations. Additionally, students will explore the use of PairGrid to create a grid of subplots for visualizing multiple pairwise relationships simultaneously.
Section 4: Seaborn Python Case Study – Data Visualization using Seaborn on Census Dataset
In this practical section, students will apply their knowledge of Seaborn to a real-world case study involving the visualization of census data. They will gain hands-on experience in performing exploratory data analysis (EDA) to gain insights into the dataset’s structure and characteristics. Students will learn how to preprocess the data, add new columns, and perform various visualizations using Seaborn. By the end of this section, students will have the skills to effectively visualize complex datasets and communicate their findings through compelling visualizations.
Course Curriculum
Chapter 1: Seaborn Python – Beginners
Lecture 1: Introduction of Seaborn
Lecture 2: Scatter Plot Part 1
Lecture 3: Scatter Plot Part 2
Lecture 4: Line Plots Part 1
Lecture 5: Line Plots Part 2
Lecture 6: Showing Multiple Relationships with Facets
Lecture 7: Categorical Scatterplots
Lecture 8: Distributions of Observations within Categories
Lecture 9: Statistical Estimation within Categories
Lecture 10: Countplot Examples
Lecture 11: Pointplot Examples
Lecture 12: Boxenplot Examples
Lecture 13: Violenplot Examples
Lecture 14: Barplot Examples
Lecture 15: Swarmplot Examples
Lecture 16: Stripplot Examples
Lecture 17: Catplot Examples
Chapter 2: Seaborn Python – Intermediate
Lecture 1: Introduction to Seaborn Intermediate
Lecture 2: Plotting Univariate Distributions
Lecture 3: Plotting Bivariate Distributions
Lecture 4: Functions to Draw linear Regression Models
Lecture 5: Fitting Different Kinds of Models
Lecture 6: Conditioning on Other Variables
Lecture 7: Examples on KDEPLOT
Lecture 8: Examples on PAIRPLOT
Lecture 9: JOINTPLOT and LMPLOT
Chapter 3: Seaborn Python – Advanced
Lecture 1: Introduction to Seaborn Advance
Lecture 2: Conditional Small Multiples
Lecture 3: Conditional Small Multiples Continue
Lecture 4: Using Custom Functions
Lecture 5: Plotting Pairwise Data Relationships
Lecture 6: Extra Examples Part 1
Lecture 7: Extra Examples Part 2
Lecture 8: Using Diff Seaborn Figure Styles
Lecture 9: Setting Different Color Palettes
Lecture 10: Setting Different Color Palettes Continue
Chapter 4: Seaborn Python Case Study – Data Visualization using Seaborn on Census Dataset
Lecture 1: Introduction of Project
Lecture 2: Installation of Tools
Lecture 3: Libraries
Lecture 4: Exploratory Data Analysis
Lecture 5: Add Columns to Dataset
Lecture 6: Data Visualization Scatterplot
Lecture 7: Multiple Line Plot
Lecture 8: Swarm plot
Lecture 9: X and Y Tick Label Setting
Lecture 10: Violin Plot and Bar plot
Lecture 11: Point plot
Lecture 12: Heat map
Lecture 13: Pair plot
Lecture 14: lmplot
Lecture 15: Pair grid
Instructors
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EDUCBA Bridging the Gap
Learn real world skills online
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 2 votes
- 3 stars: 7 votes
- 4 stars: 10 votes
- 5 stars: 19 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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