Udemy - Python Data Visualization Matplotlib & Seaborn Masterclass

[0dayddl]

1.88 GB | 00:20:46 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English​

Files Included :

Spoiler

001 Course Structure & Outline (25.29 MB)
004 Introducing the Course Project (4.7 MB)
005 Setting Expectations (9.12 MB)
006 Jupyter Installation & Launch (22.17 MB)
001 Why Visualize Data (25.36 MB)
002 3 Key Questions (21.09 MB)
003 Essential Visuals (10.35 MB)
004 Chart Formatting & Storytelling (12.91 MB)
005 Common Visualization Mistakes (16.92 MB)
006 Key Takeaways (1.7 MB)
001 Intro to Matplotlib (16.83 MB)
002 Plotting Methods (15.26 MB)
003 Plotting DataFrames (14.92 MB)
004 ASSIGNMENT Plotting DataFrames (18.03 MB)
005 SOLUTION Plotting DataFrames (5.96 MB)
006 Anatomy of a Matplotlib Figure (20.91 MB)
007 Chart Titles & Font Sizes (47.13 MB)
008 Chart Legends (58.73 MB)
009 Line Styles (8.51 MB)
010 Axis Limits (17.26 MB)
011 Figure Sizes (17.19 MB)
012 Custom Axis Ticks (11.55 MB)
013 Vertical Lines (21.99 MB)
014 Adding Text (10.89 MB)
015 PRO TIP Text Annotations (13.52 MB)
016 Removing Borders (26.18 MB)
017 ASSIGNMENT Formatting Charts (6.93 MB)
018 SOLUTION Formatting Charts (9.72 MB)
019 Line Charts (6.9 MB)
020 Stacked Line Charts (20.94 MB)
021 Dual Axis Charts (26.42 MB)
022 ASSIGNMENT Dual Axis Line Charts (5.83 MB)
023 SOLUTION Dual Axis Line Charts (8.37 MB)
024 Bar Charts (27.91 MB)
025 ASSIGNMENT Bar Charts (4.33 MB)
026 SOLUTION Bar Charts (8.23 MB)
027 Stacked Bar Charts (23.4 MB)
028 Grouped Bar Charts (30.27 MB)
029 Combo Charts (47.02 MB)
030 ASSIGNMENT Advanced Bar Charts (4.42 MB)
031 SOLUTION Advanced Bar Charts (7.15 MB)
032 Pie & Donut Charts (26.29 MB)
033 ASSIGNMENT Pie & Donut Charts (6.57 MB)
034 SOLUTION Pie & Donut Charts (5.44 MB)
035 Scatterplots & Bubble Charts (10.35 MB)
036 Histograms (23.79 MB)
037 ASSIGNMENT Scatterplots & Histograms (3.97 MB)
038 SOLUTION Scatterplots & Histograms (11.59 MB)
039 Key Takeaways (4.46 MB)
001 Project #1 Introduction (48.9 MB)
002 Project #1 Solution Walkthrough (93.98 MB)
001 Intro to Advanced Customization (1.67 MB)
002 Subplots (42.97 MB)
003 ASSIGNMENT Subplots (7.04 MB)
004 SOLUTION Subplots (17.34 MB)
005 GridSpec (14.94 MB)
006 ASSIGNMENT GridSpec (9.35 MB)
007 SOLUTION GridSpec (19.82 MB)
008 Color Options (5.58 MB)
009 Color Palettes (19.57 MB)
010 ASSIGNMENT Colors (11.64 MB)
011 SOLUTION Colors (4.67 MB)
012 Style Sheets (17.3 MB)
013 ASSIGNMENT Style Sheets (3.09 MB)
014 SOLUTION Style Sheets (3.48 MB)
015 rcParameters (32.52 MB)
016 Saving Figures & Images (5.48 MB)
017 Key Takeaways (1.57 MB)
001 Project #2 Introduction (21 MB)
002 Project #2 Solution Walkthrough (23.37 MB)
001 Intro to Seaborn (6.41 MB)
002 Basic Formatting Options (24.72 MB)
003 Bar Charts & Histograms (35.96 MB)
004 ASSIGNMENT Bar Charts & Histograms (5.27 MB)
005 SOLUTION Bar Charts & Histograms (18.16 MB)
006 Box & Violin Plots (19.36 MB)
007 ASSIGNMENT Box & Violin Plots (3.4 MB)
008 SOLUTION Box & Violin Plots (20.44 MB)
009 Linear Relationship Charts (50.06 MB)
010 Jointplots (12.72 MB)
011 PairPlots (45.77 MB)
012 ASSIGNMENT Linear Relationship Charts (6.51 MB)
013 SOLUTION Linear Relationship Charts (31.09 MB)
014 Heatmaps (22.47 MB)
015 ASSIGNMENT Heatmaps (5.05 MB)
016 SOLUTION Heatmaps (20.69 MB)
017 FacetGrid (24.29 MB)
018 Matplotlib Integration (7.51 MB)
019 Key Takeaways (3.5 MB)
001 Project #3 Introduction (46.23 MB)
002 Project #3 Solution Walkthrough (112.44 MB)

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Spoiler

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[0dayddl]

Python Data Visualization: Matplotlib & Seaborn Masterclass
Duration: 7h 30m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 2.67 GB
Genre: eLearning | Language: English​

Bring your data to LIFE and master Python's most popular data analytics & visualization libraries: Matplotlib & Seaborn

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 Visualization
Learn data visualization frameworks and best practices for choosing the right charts, applying effective formatting, and communicating clear, data-driven stories and insights

Matplotlib Fundamentals
Explore 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 histograms

PROJECT #1: Analyzing the Global Coffee Market
Read data into Python from CSV files provided by a major global coffee trader, and use Matplotlib to visualize volume and price data by country

Advanced Customization
Apply advanced customization techniques in Matplotlib, including multi-chart figures, custom layout and colors, style sheets, gridspec, parameters and more

PROJECT #2: Visualizing Global Coffee Production
Continue your analysis of the global coffee market, and leverage advanced data visualization and formatting techniques to build a comprehensive report to communicate key insights

Data Visualization with Seaborn
Visualize 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 more

PROJECT #3: Analyzing Used Car Sales
Use 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 business

Join today and get immediate, lifetime access to the following:

7.5 hours of high-quality video
Matplotlib & Seaborn PDF ebook (150+ pages)
Downloadable project files & solutions
Expert support and Q&A forum
30-day satisfaction guarantee

If 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)

Who this course is for:
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

Bitte Anmelden oder Registrieren um Links zu sehen.

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[0dayddl]

Python Data Visualization: Matplotlib & Seaborn Masterclass
Duration: 7h 30m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 2.67 GB
Genre: eLearning | Language: English​

Bring your data to LIFE and master Python's most popular data analytics & visualization libraries: Matplotlib & Seaborn

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 Visualization
Learn data visualization frameworks and best practices for choosing the right charts, applying effective formatting, and communicating clear, data-driven stories and insights

Matplotlib Fundamentals
Explore 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 histograms

PROJECT #1: Analyzing the Global Coffee Market
Read data into Python from CSV files provided by a major global coffee trader, and use Matplotlib to visualize volume and price data by country

Advanced Customization
Apply advanced customization techniques in Matplotlib, including multi-chart figures, custom layout and colors, style sheets, gridspec, parameters and more

PROJECT #2: Visualizing Global Coffee Production
Continue your analysis of the global coffee market, and leverage advanced data visualization and formatting techniques to build a comprehensive report to communicate key insights

Data Visualization with Seaborn
Visualize 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 more

PROJECT #3: Analyzing Used Car Sales
Use 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 business

Join today and get immediate, lifetime access to the following:

7.5 hours of high-quality video
Matplotlib & Seaborn PDF ebook (150+ pages)
Downloadable project files & solutions
Expert support and Q&A forum
30-day satisfaction guarantee

If 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)

Who this course is for:
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

Bitte Anmelden oder Registrieren um Links zu sehen.

Please check out others courses in your favourite language and bookmark them
- - - -

RapidGator

Bitte Anmelden oder Registrieren um Code Inhalt zu sehen!

NitroFlare

Bitte Anmelden oder Registrieren um Code Inhalt zu sehen!

UsersDrive
​