Python Data Visualization Matplotlib Seaborn Masterclass
What you’ll learn
Master the essentials of Matplotlib & Seaborn, two of Python’s most powerful data visualization packages
Design and format 20+ chart types using Matplotlib & Seaborn, including line charts, bar charts, scatter plots, histograms, violin plots, heatmaps and more
Learn advanced customization options like subplots, gridspec, style sheets and parameters
Apply best practices for data visualization, storytelling, formatting and visual design
Build powerful, practical skills for modern analytics and business intelligence
Requirements
We’ll use Anaconda & Jupyter Notebooks (a free, user-friendly coding environment)
Familiarity with base Python is strongly recommended, but not a strict prerequisite
Description
This is a hands-on, project-based course designed to help you learn two of the most popular Python packages for data visualization: Matplotlib & Seaborn.We’ll start with a quick introduction to data visualization frameworks and best practices, and review essential visuals, common errors, and tips for effective communication and storytelling.From there we’ll dive into Matplotlib fundamentals, and practice building and customizing line charts, bar charts, pies & donuts, scatterplots, histograms and more. We’ll break down the components of a Matplotlib figure and introduce common chart formatting techniques, then explore advanced customization options like subplots, GridSpec, style sheets and parameters.Finally we’ll introduce Python’s Seaborn library. We’ll start by building some basic charts, then dive into more advanced visuals like box & violin plots, PairPlots, heat maps, FacetGrids, and more. Throughout the course you’ll play the role of a Consultant at Maven Consulting Group, a firm that provides strategic advice to companies around the world. You’ll practice applying your skills to a range of real-world projects and case studies, from hotel customer demographics to diamond ratings, coffee prices and automotive sales. COURSE OUTLINE:Intro to Data VisualizationLearn data visualization frameworks and best practices for choosing the right charts, applying effective formatting, and communicating clear, data-driven stories and insightsMatplotlib FundamentalsExplore Python’s Matplotlib library and use it to build and customize several essential chart types, including line charts, bar charts, pie/donut charts, scatterplots and histogramsPROJECT #1: Analyzing the Global Coffee MarketRead data into Python from CSV files provided by a major global coffee trader, and use Matplotlib to visualize volume and price data by countryAdvanced CustomizationApply advanced customization techniques in Matplotlib, including multi-chart figures, custom layout and colors, style sheets, gridspec, parameters and morePROJECT #2: Visualizing Global Coffee ProductionContinue your analysis of the global coffee market, and leverage advanced data visualization and formatting techniques to build a comprehensive report to communicate key insightsData Visualization with SeabornVisualize data with Python’s Seaborn library, and build custom visuals using additional chart types like box plots, violin plots, joint plots, pair plots, heatmaps and morePROJECT #3: Analyzing Used Car SalesUse Seaborn and Matplotlib to explore, analyze and visualize automotive auction data to help your client identify the best deals on used service vehicles for the businessJoin today and get immediate, lifetime access to the following:7.5 hours of high-quality videoMatplotlib & Seaborn PDF ebook (150+ pages)Downloadable project files & solutionsExpert support and Q&A forum30-day Udemy satisfaction guaranteeIf you’re a data scientist, BI analyst or data engineer looking to add Matplotlib & Seaborn to your Python skill set, this is the course for you!Happy learning!-Chris Bruehl (Python Expert & Lead Python Instructor, Maven Analytics)__________Looking for our full business intelligence stack? Search for “Maven Analytics” to browse our full course library, including Excel, Power BI, MySQL, Tableau and Machine Learning courses!See why our courses are among the TOP-RATED on Udemy:”Some of the BEST courses I’ve ever taken. I’ve studied several programming languages, Excel, VBA and web dev, and Maven is among the very best I’ve seen!” Russ C.”This is my fourth course from Maven Analytics and my fourth 5-star review, so I’m running out of things to say. I wish Maven was in my life earlier!” Tatsiana M.”Maven Analytics should become the new standard for all courses taught on Udemy!” Jonah M.
Overview
Section 1: Getting Started
Lecture 1 Course Structure & Outline
Lecture 2 READ ME: Important Notes for New Students
Lecture 3 DOWNLOAD: Course Resources
Lecture 4 Introducing the Course Project
Lecture 5 Setting Expectations
Lecture 6 Jupyter Installation & Launch
Section 2: Intro to Data Visualization
Lecture 7 Why Visualize Data?
Lecture 8 3 Key Questions
Lecture 9 Essential Visuals
Lecture 10 Chart Formatting & Storytelling
Lecture 11 Common Visualization Mistakes
Lecture 12 Key Takeaways
Section 3: Matplotlib Fundamentals
Lecture 13 Intro to Matplotlib
Lecture 14 Plotting Methods
Lecture 15 Plotting DataFrames
Lecture 16 ASSIGNMENT: Plotting DataFrames
Lecture 17 SOLUTION: Plotting DataFrames
Lecture 18 Anatomy of a Matplotlib Figure
Lecture 19 Chart Titles & Font Sizes
Lecture 20 Chart Legends
Lecture 21 Line Styles
Lecture 22 Axis Limits
Lecture 23 Figure Sizes
Lecture 24 Custom Axis Ticks
Lecture 25 Vertical Lines
Lecture 26 Adding Text
Lecture 27 PRO TIP: Text Annotations
Lecture 28 Removing Borders
Lecture 29 ASSIGNMENT: Formatting Charts
Lecture 30 SOLUTION: Formatting Charts
Lecture 31 Line Charts
Lecture 32 Stacked Line Charts
Lecture 33 Dual Axis Charts
Lecture 34 ASSIGNMENT: Dual Axis Line Charts
Lecture 35 SOLUTION: Dual Axis Line Charts
Lecture 36 Bar Charts
Lecture 37 ASSIGNMENT: Bar Charts
Lecture 38 SOLUTION: Bar Charts
Lecture 39 Stacked Bar Charts
Lecture 40 Grouped Bar Charts
Lecture 41 Combo Charts
Lecture 42 ASSIGNMENT: Advanced Bar Charts
Lecture 43 SOLUTION: Advanced Bar Charts
Lecture 44 Pie & Donut Charts
Lecture 45 ASSIGNMENT: Pie & Donut Charts
Lecture 46 SOLUTION: Pie & Donut Charts
Lecture 47 Scatterplots & Bubble Charts
Lecture 48 Histograms
Lecture 49 ASSIGNMENT: Scatterplots & Histograms
Lecture 50 SOLUTION: Scatterplots & Histograms
Lecture 51 Key Takeaways
Section 4: PROJECT #1: Analyzing the Global Coffee Market
Lecture 52 Project #1 Introduction
Lecture 53 Project #1 Solution Walkthrough
Section 5: Advanced Customization
Lecture 54 Intro to Advanced Customization
Lecture 55 Subplots
Lecture 56 ASSIGNMENT: Subplots
Lecture 57 SOLUTION: Subplots
Lecture 58 GridSpec
Lecture 59 ASSIGNMENT: GridSpec
Lecture 60 SOLUTION: GridSpec
Lecture 61 Color Options
Lecture 62 Color Palettes
Lecture 63 ASSIGNMENT: Colors
Lecture 64 SOLUTION: Colors
Lecture 65 Style Sheets
Lecture 66 ASSIGNMENT: Style Sheets
Lecture 67 SOLUTION: Style Sheets
Lecture 68 rcParameters
Lecture 69 Saving Figures & Images
Lecture 70 Key Takeaways
Section 6: PROJECT #2: Visualizing Global Coffee Production
Lecture 71 Project #2 Introduction
Lecture 72 Project #2 Solution Walkthrough
Section 7: Visualization with Seaborn
Lecture 73 Intro to Seaborn
Lecture 74 Basic Formatting Options
Lecture 75 Bar Charts & Histograms
Lecture 76 ASSIGNMENT: Bar Charts & Histograms
Lecture 77 SOLUTION: Bar Charts & Histograms
Lecture 78 Box & Violin Plots
Lecture 79 ASSIGNMENT: Box & Violin Plots
Lecture 80 SOLUTION: Box & Violin Plots
Lecture 81 Linear Relationship Charts
Lecture 82 Jointplots
Lecture 83 PairPlots
Lecture 84 ASSIGNMENT: Linear Relationship Charts
Lecture 85 SOLUTION: Linear Relationship Charts
Lecture 86 Heatmaps
Lecture 87 ASSIGNMENT: Heatmaps
Lecture 88 SOLUTION: Heatmaps
Lecture 89 FacetGrid
Lecture 90 Matplotlib Integration
Lecture 91 Key Takeaways
Section 8: PROJECT #3: Analyzing Used Car Sales
Lecture 92 Project #3 Introduction
Lecture 93 Project #3 Solution Walkthrough
Section 9: BONUS LESSON
Lecture 94 BONUS LESSON
Analysts or BI professionals looking to learn data visualization with Matplotlib and Seaborn,Aspiring data scientists who want to build or strengthen their Python data visualization skills,Anyone interested in learning one of the most popular open source programming languages in the world,Students looking to learn powerful, practical skills with unique, hands-on projects and course demos
Course Information:
Udemy | English | 7h 31m | 2.60 GB
Created by: Maven Analytics
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